WO2011058367A2 - Diagnostic test for predicting responsiveness to treatment with poly(adp-ribose) polymerase (parp) inhibitor - Google Patents

Diagnostic test for predicting responsiveness to treatment with poly(adp-ribose) polymerase (parp) inhibitor Download PDF

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WO2011058367A2
WO2011058367A2 PCT/GB2010/051888 GB2010051888W WO2011058367A2 WO 2011058367 A2 WO2011058367 A2 WO 2011058367A2 GB 2010051888 W GB2010051888 W GB 2010051888W WO 2011058367 A2 WO2011058367 A2 WO 2011058367A2
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parp
biomarker
expression
cancer
protein
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WO2011058367A3 (en
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Jonathan Richard Dry
Christopher George Harbron
Darren Richard Hodgson
Alan Yin Kai Lau
Mark James O'connor
John Edward Prime
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Astrazeneca Ab
Astrazeneca Uk Limited
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
    • G01N33/57407—Specifically defined cancers
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6813—Hybridisation assays
    • C12Q1/6816—Hybridisation assays characterised by the detection means
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/106—Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/90—Enzymes; Proenzymes
    • G01N2333/91—Transferases (2.)
    • G01N2333/91091—Glycosyltransferases (2.4)
    • G01N2333/91142—Pentosyltransferases (2.4.2)
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/90—Enzymes; Proenzymes
    • G01N2333/914—Hydrolases (3)
    • G01N2333/924—Hydrolases (3) acting on glycosyl compounds (3.2)
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/52—Predicting or monitoring the response to treatment, e.g. for selection of therapy based on assay results in personalised medicine; Prognosis

Definitions

  • the invention relates generally to methods for treating cancer and to methods of predicting the responsiveness of a cancer cell to therapeutic treatment.
  • the invention provides the identities of biomarkers (genes) that may be used to identify populations or individuals of cancer sufferers that are likely to respond favourably to treatment with PARP inhibitors, such as olaparib (4-[3-(4- cyclopropanecarbonyl-piperazine-1 -carbonyl)-4-fluoro-benzyl]-2H-phthalazin-1 - one).
  • PARP inhibitors such as olaparib (4-[3-(4- cyclopropanecarbonyl-piperazine-1 -carbonyl)-4-fluoro-benzyl]-2H-phthalazin-1 - one).
  • This invention also relates to the use of particular biomarkers to assess or determine the suitability of certain cells, in particular cancer cells, to treatment with a Poly(ADP-Ribose) polymerase (PARP) inhibitor.
  • PARP Poly(A
  • PARP Poly(ADP-Ribose) polymerase
  • BER Base Excision Repair
  • WO2005/012524 (The University of Sheffield) teach that cells deficient in homologous recombination (HR) are hypersensitive to PARP inhibitors as compared to wild type cells, and thus that PARP inhibitors are useful in the treatment of cancer cells defective in the expression of a gene involved in HR.
  • HR genes identified therein include XRCC1 , ADPRT (PARP-1 ), ADPRTL2 (PARP-2), CTPS, RPA, RPA1 , RPA2, RPA3, XPD, ERCC1 , XPF, MMSI9, RAD51 , RAD51 B, RAD51 C, RAD51 D, DMC1 , XRCC2, XRCC3, BRCA1 , BRCA2, RAD52, RAD54, RAD50, MRE 1 1 , NBS 1 , WRN, BLM, Ku70, Ku80, ATM, ATR, CHEK1 , CHEK2, FANCA, FANCB, FANCC, FANCD1 , FANCD2, FANCE, FANCF, FANCG, RAD1 , RAD9, FEN-1 , Mus81 , Emel, DSS1 and BARD.
  • the components of the HR dependent DNA DSB repair pathway listed include ATM (NM_000051 ), RAD51 (NM_002875), RAD51 L1 (NM_002877), RAD51 C (NM_002876), RAD51 L3
  • NM_005732 MRE1 1 A (NM_005590) and NBN (NM_002485), as well as regulatory factors such as EMSY.
  • WO 2008/147418, US2007/0292883 and US2008/0262062 (BiPAR Sciences Inc.) relates to methods of treating a PARP mediated disease comprising measuring the level of PARP in a sample from a patient and if the level of PARP is up- regulated treating the patient with a PARP modulator, e.g. PARP inhibitor.
  • a PARP modulator e.g. PARP inhibitor.
  • the present invention relates to the identification and use of biomarker expression patterns (or profiles or signatures) which are correlated with cancer cells that are responsive to PARP inhibitor treatment, and which can therefore serve as a diagnostic personalised healthcare test to select patients that will likely respond favourably to PARP inhibitor therapy and deselect those that are unlikely to respond to PARP inhibitor therapy.
  • the patterns may thus be used in diagnostic or prognostic methods or assays in the clinic to determine the appropriate treatment following identification of cancer in a patient.
  • the present invention provides methods of treating cancer in a subject/patient and methods of selecting cancer patients for such treatment.
  • the method of selection involves determining the expression level of PARP-1 in a cancer cell containing sample from the patient and if the PARP-1 expression level is not low, identifying or selecting the patient for treatment with a PARP inhibitor.
  • the method of treating cancer includes determining the expression level of PARP-1 in a cancer cell containing sample from the subject and if the PARP-1 expression level is not low, administering to the subject an effective amount of a PARP inhibitor.
  • the present invention provides methods of treating cancer in a subject/patient and methods of selecting cancer patients for such treatment.
  • the method of selection involves determining the expression level of MUTYH in a cancer cell containing sample from the patient and if the MUTYH expression level is not low, identifying or selecting the patient for treatment with a PARP inhibitor.
  • the method of treating cancer includes determining the expression level of MUTYH in a cancer cell containing sample from the subject and if the MUTYH expression level is not low, administering to the subject an effective amount of a PARP inhibitor.
  • the expression level of one or more genes involved in homologous recombination repair as listed in Table 2 is also measured; and selecting the patient for treatment with a PARP inhibitor if the expression profile of the biomarkers identifies the patient as being a likely responder to treatment with the PARP inhibitor.
  • a patient whose cancer cells do not express low levels of PARP-1 or MUTYH but do express low levels of any of the homologous recombination repair genes selected from the group consisting of: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1 A is selected for treatment and/or treated with the PARP inhibitor compound.
  • the invention provides a method for selecting a cancer patient for treatment with a PARP inhibitor comprising measuring the expression level of at least one base excision repair biomarker as listed in Table 1 , at least one homologous recombination biomarker as listed in Table 2 and at least one proliferation biomarker as listed in Table 3, in a cancer cell containing sample obtained from the patient and selecting the patient for treatment with a PARP inhibitor if the expression profile of the at least three biomarkers identifies the patient as being a likely responder to treatment with the PARP inhibitor.
  • the biomarker(s) from Table 1 are selected from PARP-1 , MUTYH, POLD1 and POLE3.
  • recombination biomarker from Table 2 is selected from: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1 A.
  • the homologous recombination biomarker from Table 2 is selected from: MCM2, XRCC3, BRCA1 , MDC1 , ATM, ATR, NBN, RAD51 and MRE1 1 A.
  • the proliferation biomarker from Table 3 is selected from AURKA, SMARCD3, ZIC1 , SSX2IP and BOC.
  • a method of treating cancer comprising measuring the expression level of at least one base excision repair biomarker from Table 1 , at least one homologous recombination biomarker from Table 2 and at least one proliferation biomarker from Table 3, in a cancer cell containing sample obtained from the patient and if the expression profile of the biomarkers identifies the patient as being a likely responder to treatment with the PARP inhibitor, administering to said patient an effective amount of a PARP inhibitor.
  • the biomarker(s) from Table 1 is selected from PARP-1 and MUTYH.
  • the homologous recombination biomarker from Table 2 is selected from: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and
  • MRE1 1 A In another embodiment the homologous recombination biomarker from Table 2 is selected from: MCM2, XRCC3, BRCA1 , MDC1 , ATM, ATR, NBN, RAD51 and MRE1 1A.
  • the proliferation biomarker from Table 3 is selected from AURKA, SMARCD3, ZIC1 , SSX2IP, BOC, POLH, TP53BP2, SCMH1 , SMARCA5, MRAS, IP6K2, GTF2H4, MBD1 , RASA3, ZMYM4, PHF13, ARNT, KDM4A, PCBP4, TLR4, NUDT1 , PMS1 and ZMYM6.
  • a suitable PARP inhibitor compound that the methods of the invention can be applied to is olaparib.
  • Figure 1 shows PARP-1 gene and protein expression levels for each of the cell lines in the KU95 panel and the correlation with olaparib response.
  • A Scatter plots comparing PARP-1 mRNA expression (normalised to the average of 3 housekeeping genes - PPIA, PGK1 and TBP) on the x-axis and olaparib IC50 on the y-axis.
  • the solid line represents a simple straight line fit between all data points.
  • the hatched lines are cut-off levels for mean normalised gene expression (0; x-axis) or olaparib sensitivity (0; less than 1 ⁇ ; y-axis).
  • FIG. 2 shows BRCA1 gene expression for each of the cell lines in the KU95 panel and the correlation with olaparib response. Scatter plots comparing BRCA1 mRNA expression (normalised to the average of 3 housekeeping genes) on the x- axis and olaparib IC50 on the y-axis. The solid line represents a simple straight line fit between all data points.
  • Figure 3 shows the ROC curve demonstrating the increased predictive power of using PARP-1 and ATM over and above either biomarker alone
  • Figure 4 shows the identification of two main clusters within the 426 Affymetrix genes: the lower (smaller) cluster is a DNA repair cluster containing primarily genes associated with BER and HR, the other genes associated with cell proliferation function.
  • Figure 5 shows the three main functional groups of biomarkers for predicting olaparib sensitivity and how they were identified.
  • Figure 6 shows a ROC curve that illustrates the improved predictive power of the combination of PARP-1 (BER), BRCA1 (HR) and AURKA (proliferation)
  • Figure 7 shows a ROC curve that illustrates the improved predictive power of the combination of MUTYH (BER), BRCA1 (HR) and SMARCD3 (proliferation) biomarkers to predict olaparib response.
  • Figure 8 shows a ROC curve that illustrate the improved predictive power of the combination of MUTYH (BER), ATM (HR) and ZIC1 (proliferation) biomarkers to predict olaparib response.
  • Figure 9 shows a ROC curve that illustrates the improved predictive power of the combination of POLD1 , (BER), ATM (HR) and SSX2IP (proliferation) biomarkers to predict olaparib response.
  • Figure 10 shows a ROC curve that illustrates the improved predictive power of the combination of POLE3 (BER), BRCA1 (HR) and BOC1 (proliferation) biomarkers to predict olaparib response.
  • biomarker in the context of the present invention encompasses, without limitation, a gene (e.g. nucleic acid) including its encoded protein or polypeptide as disclosed in any of Tables 1 , 2 or 3, as well as polymorphisms thereof. Biomarkers can also include mutated proteins or mutated nucleic acids.
  • a gene e.g. nucleic acid
  • Biomarkers can also include mutated proteins or mutated nucleic acids.
  • a "gene” is a polynucleotide that encodes a discrete product, whether RNA or proteinaceous in nature. It is appreciated that more than one polynucleotide may be capable of encoding a discrete product.
  • the term includes alleles and polymorphisms of a gene that encodes the same product, or a functionally associated (including gain, loss, or modulation of function) analog thereof, based upon chromosomal location and ability to recombine during normal mitosis.
  • a biomarker (gene) expression “pattern” or “profile” or “signature” refers to the relative expression of one or more biomarkers (genes) between different cells, which expression is correlated with being able to distinguish between cancer cells that will respond favourably or not to treatment with a PARP inhibitor.
  • a “sequence” or “gene sequence” as used herein is a nucleic acid molecule or polynucleotide composed of a discrete order of nucleotide bases.
  • the term includes the ordering of bases that encodes a discrete product (i.e. "coding region"), whether RNA or proteinaceous in nature, as well as the ordered bases that precede or follow a "coding region". Non-limiting examples of the latter include 5' and 3' untranslated regions of a gene. It is appreciated that more than one polynucleotide may be capable of encoding a discrete product. It is also
  • alleles and polymorphisms of the disclosed sequences may exist and may be used in the practice of the invention to identify the expression level(s) of the disclosed sequences or the allele or polymorphism. Identification of an allele or polymorphism depends in part upon chromosomal location and ability to recombine during mitosis.
  • correlate refers to an association between the expression of one or more genes and the response to treatment with olaparib.
  • correlation refers to an association between the expression of one or more genes and the response to treatment with olaparib.
  • correlation are used more broadly than simply a Pearson or Spearman correlation to refer to an association or relationship which can take one of many forms, as demonstrated in the examples. Correlations may be positive such that high levels of expression are associated with large or positive responses, and low levels of expression are associated with small or negative responses, or negatively correlated, such that high levels of expression are associated with small or negative responses, and low levels of expression are associated with large or positive responses.
  • Expression data may be generated by one or more of a range of gene or protein expression measuring techniques, for example but not limited to, RT-PCR, Affymetrix whole genome microarray profiling for gene expression or IHC or Western Blotting for protein expression. Normalisation is typically applied to the raw data generated from these techniques to remove any artefactual inter-subject differences arising from sample processing or sample quality. Data from RT-PCR is typically normalised by subtracting the average expression of one or more normalisation genes from the observed expression levels of the gene of interest for each sample. Data from Affymetrix whole genome microarrays is typically normalised by the RMA algorithm or one of a number of alternative algorithms including but not limited to MAS5, PLIER, GC-RMA.
  • increases in gene expression can be indicated by ratios of or about 1 .1 , of or about 1 .2, of or about 1 .3, of or about 1 .4, of or about 1 .5, of or about 1 .6, of or about 1 .7, of or about 1 .8, of or about 1 .9, of or about 2, of or about 2.5, of or about 3, of or about 3.5, of or about 4, of or about 4.5, of or about 5, of or about 5.5, of or about 6, of or about 6.5, of or about 7, of or about 7.5, of or about 8, of or about 8.5, of or about 9, of or about 9.5, of or about 10, of or about 15, of or about 20, of or about 30, of or about 40, of or about 50, of or about 60, of or about 70, of or about 80, of or about 90, of or about 100, of or about 150, of or about 200, of or about 300, of or about 400, of or about 500, of or about 600, of or about 700, of or about 800, of or about 900
  • a ratio of 2 is a 100% (or a two-fold) increase in expression.
  • Decreases in gene expression can be indicated by ratios of or about 0.9, of or about 0.8, of or about 0.7, of or about 0.6, of or about 0.5, of or about 0.4, of or about 0.3, of or about 0.2, of or about 0.1 , of or about 0.05, of or about 0.01 , of or about 0.005, of or about 0.001 , of or about 0.0005, of or about 0.0001 , of or about 0.00005, of or about 0.00001 , of or about 0.000005, or of or about 0.000001 .
  • a number of different statistical algorithms can be applied in order to generate a mathematical model combining together the expression levels of two or more genes or proteins with a cut-off to classify subjects as predicted olaparib responders. These include, but are not limited to logistic regression, multiple regression, Cox proportional hazard models, random forests, recursive
  • partitioning random survival forests, partial least squares, partial least squares discriminant analysis, Support Vector Machines, neural networks.
  • amplify is used in the broad sense to mean creating an amplification product, which for example, can be made enzymatically with DNA or RNA polymerases.
  • Amplification generally refers to the process of producing multiple copies of a desired sequence, particularly those of a sample.
  • Multiple copies mean at least 2 copies.
  • a “copy” does not necessarily mean perfect sequence complementarity or identity to the template sequence.
  • Methods for amplifying mRNA are generally known in the art, and include reverse transcription PCR (RT-PCR) and those described in U.S. patent application Ser. No. 10/062,857 (filed on Oct. 25, 2001 ), as well as U.S.
  • RNA may be directly labelled as the corresponding cDNA by methods known in the art.
  • a "microarray” is a linear or two-dimensional array of preferably discrete regions, each having a defined area, formed on the surface of a solid support such as, but not limited to, glass, plastic, or synthetic membrane.
  • the density of the discrete regions on a microarray is determined by the total numbers of immobilized polynucleotides to be detected on the surface of a single solid phase support, for example at least about 50/cm 2 , at least about 100/cm 2 , at least about 500/cm 2 , but preferably below about 1 ,000/cm 2 .
  • the arrays contain less than about 500, about 1000, about 1500, about 2000, about 2500, or about 3000 immobilized polynucleotides in total.
  • a DNA microarray is an array of oligonucleotides or polynucleotides placed on a chip or other surfaces used to hybridize to amplified or cloned polynucleotides from a sample. Since the position of each particular group of primers in the array is known, the identities of a sample polynucleotides can be determined based on their binding to a particular position in the microarray.
  • label refers to a composition capable of producing a detectable signal indicative of the presence of the labelled molecule. Suitable labels include radioisotopes, nucleotide chromophores, enzymes, substrates, fluorescent molecules, chemiluminescent moieties, magnetic particles, bioluminescent moieties, and the like. As such, a label is any composition detectable by
  • support refers to conventional supports such as beads, particles, dipsticks, fibres, filters, membranes and silane or silicate supports such as glass slides.
  • “Expression” and “gene expression” include transcription and/or translation of nucleic acid material.
  • Conditions that "allow” an event to occur or conditions that are “suitable” for an event to occur are conditions that do not prevent such events from occurring. Thus, these conditions permit, enhance, facilitate, and/or are conducive to the event.
  • Such conditions known in the art and described herein, depend upon, for example, the nature of the nucleotide sequence, temperature, and buffer conditions. These conditions also depend on what event is desired, such as hybridization, cleavage, strand extension or transcription.
  • Detection includes any means of detecting, including direct and indirect detection of gene expression and changes therein. For example, “detectably less” products may be observed directly or indirectly, and the term indicates any reduction (including the absence of detectable signal). Similarly, “detectably more” product means any increase, whether observed directly or indirectly.
  • treatment pertains generally to treatment and therapy, whether of a human or an animal (e.g. in veterinary applications), in which some desired therapeutic effect is achieved, for example, the inhibition of the progress of the condition, and includes a reduction in the rate of progress, a halt in the rate of progress, amelioration of the condition, and cure of the condition.
  • Treatment as a prophylactic measure i.e. prophylaxis is also included.
  • efficacious it is meant that the treatment leads to stabilization in tumour size, a decrease in tumour size, or a decrease in metastatic potential of cancer in a subject.
  • BER genes refers to genes associated with Base Excision Repair, a form of DNA repair involved in dealing with DNA single-strand breaks that may occur endogenously or may be induced through various cancer therapies such as ionizing radiation or treatment with DNA damaging chemotherapies. There are a number of genes associated with BER including PARP-1 . Those genes associated with BER for the purpose of this application are listed in Table 1 . Table 1 .
  • complementation group 1 (includes
  • PRIM1 primase DNA, polypeptide 1 (49kDa) 5557 -1 0.0073004 polymerase (DNA directed), epsilon 2
  • GNL3 like 3 (nucleolar) 26354 1 0.0315160 tankyrase, TRF1 -interacting ankyrin-
  • ESPL1 (S. cerevisiae) 9700 0.0649566
  • PARG poly (ADP-ribose) glycohydrolase 8505
  • Recombination repair pathway a form of DNA repair involved in dealing with DNA double strand breaks that may occur endogenously or may be induced through various cancer therapies such as ionizing radiation or treatment with DNA damaging chemotherapies.
  • HR a number of genes associated with HR including BRCA1 , BRCA2, ATM, ATR, CHEK2, MDC1 and MRE1 1A. Those genes associated with HR for the purpose of this application are listed in Table 2.
  • TROAP trophinin associated protein 1002 0.0005769
  • GINS2 GINS complex subunit 2 (Psf2 homolog) 5165 0.002101 1
  • CALM3 calmodulin 3 (phosphorylase kinase, 808 0.0027420 delta)
  • proliferation genes refers to those genes involved in the control of cell cycle and proliferation and for the purpose of this application are listed in Table 3. Table 3.
  • EIF2C3 eukaryotic translation initiation factor 2C, 3 19266 0.0002213
  • AIFM2 apoptosis-inducing factor, mitochondrion- 84883 0.0007537 associated, 2
  • TBC1 D2 TBC1 domain family member 2 55357 -1 0.0007978
  • SAMD1 sterile alpha motif domain containing 1 90378 1 0.0010875
  • EIF2C1 eukaryotic translation initiation factor 2C, 1 26523 1 0.0013255
  • PIAS2 protein inhibitor of activated STAT 2 9063 1 0.0014305
  • MIB2 mindbomb homolog 2 (Drosophila) 14267 0.0018255
  • TIA1 TIA1 cytotoxic granule-associated RNA 7072 0.0022886 binding protein 1
  • ORMDL2 ORM1 -like 2 (S. cerevisiae) 29095 -1 0.0024889
  • PCDHAC2 protocadherin alpha subfamily C 2 56134 1 0.0027171
  • NUDT3 nudix (nucleoside diphosphate linked 1 1 165 0.0039702 moiety X)-type motif 3 1
  • ATAD2 ATPase family AAA domain containing 2 29028 -1 0.0042200
  • IL1 R1 interleukin 1 receptor type I 3554 1 0.0048077
  • NDUFA5 NADH dehydrogenase (ubiquinone) 1 4698 0.0060914
  • PHF21A PHD finger protein 21A 51317 1 0.0068604
  • TP53BP2 tumor protein p53 binding protein 2 7159 1 0.0101765
  • DIRAS3 DIRAS family GTP-binding RAS-like 3 9077 1 0.0193385
  • PRKCA protein kinase C alpha 5578 -1 0.0196635
  • SERPINE1 serpin peptidase inhibitor SERPINE1 serpin peptidase inhibitor, clade E (nexin, 5054 -1 0.021 1086 plasminogen activator inhibitor type 1 ),
  • HNRNPA2B heterogeneous nuclear ribonucleoprotein 3181 0.0215084 1 A2/B1
  • GLIPR1 GLI pathogenesis-related 1 1 1010 -1 0.0289794
  • NUDT1 nudix (nucleoside diphosphate linked 4521 -1 0.0353147 moiety X)-type motif 1
  • CASP1 caspase 1 apoptosis-related cysteine 834 0.0578672 peptidase (interleukin 1 , beta, convertase)
  • PSMB8 proteasome prosome, macropain
  • 5696 -1 0.0714354 subunit, beta type, 8 (large multifunctional
  • oncogene homolog 2 neuro/glioblastoma derived oncogene homolog (avian)
  • "Directionality" values of -1 represent a biomarker for which a high level of expression was found to be associated with resistance or a low level of expression to be associated with sensitivity (e.g.
  • Values of +1 represent a biomarker for which a high level of expression was found to be associated with sensitivity or a low level of expression to be associated with resistance in Example 4.
  • the biomarkers without a direction are those that did have a strong association in one or more of the analyses, but did not always have a constant direction of association across the different analyses that were performed.
  • the p-value in these tables (also referred to as p.min) is the smallest of the 5 permutation p-values from the DEGNN, DEGTN, DESNG, DEGTG and DES analyses as described in Example 4.
  • NCBI National Center for Biotechnology Information
  • NCBI National Center for Biotechnology Information
  • An 'Entrez Genlnfo Identifier' (“Entrez Gene ID”) sequence identification number is a series of digits assigned consecutively to each sequence record processed by NCBI and is unique to a particular gene and associated DNA sequence
  • Entrez Gene ID refers to the Entrez Database accession number of a sequence of each gene, the sequences of which are hereby incorporated by reference in their entireties as they are available from
  • KU95 panel refers to the panel of 95 cancer cell lines as listed in Table 4 representing breast, ovarian, colorectal, lung, head & neck and pancreatic cancers, tested for their response to treatment with single agent olaparib.
  • IC50 refers to the concentration of olaparib (in ⁇ ) that results in 50% of the number of cell colonies that grow compared to the untreated control.
  • An individual having a cancer condition may comprise one or more cancer cells.
  • Cancer cells in general are characterised by abnormal proliferation relative to normal cells and typically form clusters or tumours in an individual having a cancer condition.
  • the cancer cells may possess a phenotype, which characterises the cancer condition. It is this phenotype that the present invention seeks to identify.
  • a method for selecting a cancer patient for treatment with a PARP inhibitor comprising determining the expression level of PARP-1 and/or MUTYH in a cancer cell containing sample from the patient and if the PARP-1 and/or MUTYH expression level is not low, identifying or selecting the patient for treatment with a PARP inhibitor.
  • a suitable PARP inhibitor is olaparib.
  • the expression levels of both PARP-1 and MUTYH are determined.
  • the expression level of one or more genes involved in homologous recombination repair as listed in Table 2 is also measured.
  • the patient is then identified or selected for treatment with a PARP inhibitor if the expression profile of the biomarkers identifies the patient as being a likely responder to treatment with the PARP inhibitor.
  • a patient whose cancer cells do not express low levels of PARP-1 or MUTYH but do express low levels of any of the homologous recombination repair genes selected from the group consisting of: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1 A is selected for treatment and/or treated with the PARP inhibitor compound.
  • the invention provides a method for selecting a cancer patient for PARP inhibitor based therapy comprising: measuring the amount of PARP-1 and at least one other biomarker selected from: ATM, BRCA1 , BRCA2, MRE1 1 A, ATR, CHEK2 and MDC1 , in a tumour cell containing sample from said cancer patient, comparing these amounts to reference values; and, selecting the patient for treatment with PARP inhibitor based therapy if, compared to the reference values, the level of PARP-1 is not low and the level of the other biomarker is reduced in the tumour cell containing sample from said cancer patient.
  • the invention provides a method for selecting a cancer patient for PARP inhibitor based therapy comprising: measuring the amount of MUTYH and at least one other biomarker selected from: ATM, BRCA1 , BRCA2, MRE1 1 A, ATR, CHEK2 and MDC1 , in a tumour cell containing sample from said cancer patient, comparing these amounts to reference values; and, selecting the patient for treatment with PARP inhibitor based therapy if, compared to the reference values, the level of MUTYH is not low and the level of the other biomarker is reduced in the tumour cell containing sample from said cancer patient.
  • the methods of the invention can be applied to testing colorectal or gastric cancers.
  • the measurement of PARP-1 and ATM and/or MRE1 1 A can be used to select or identify colorectal or gastric cancer patients for treatment with a PARP inhibitor as required.
  • a PARP inhibitor compound in the manufacture of a medicament for treating a patient suffering from colorectal cancer whose cancer cells are deficient in ATM and/or MRE1 1 A.
  • a method for selecting a colorectal cancer patient for PARP inhibitor based therapy comprising: measuring the amount of ATM and/or MRE1 1 A in a tumour cell containing sample from said cancer patient, comparing these amounts to reference values; and, selecting the patient for treatment with PARP inhibitor based therapy if, compared to the reference values, the level of ATM and/or MRE1 1A is low.
  • a PARP inhibitor compound in the manufacture of a medicament for treating a patient suffering from gastric cancer whose cancer cells are deficient in ATM.
  • a method for selecting a gastric cancer patient for PARP inhibitor based therapy comprising: measuring the amount of ATM in a tumour cell containing sample from said cancer patient, comparing these amounts to reference values; and, selecting the patient for treatment with PARP inhibitor based therapy if, compared to the reference values, the level of ATM is low.
  • a method for identifying whether an individual with cancer will likely be responsive to a treatment with a PARP inhibitor drug comprising:
  • a first gene expression profile which profile includes one or more genes from Table 1 such as PARP-1 , MUTYH, POLD1 and POLE3, at least one gene from Table 2 and at least one gene from Table 3;
  • the inventors have found that a multiplex diagnostic involving at least one gene from each of Tables 1 , 2 and 3, yields even greater statistically significant prediction of likely response to PARP inhibitor than either PARP-1 or an HR deficiency alone.
  • MUTYH was found to be extremely predictive (even when used alone) and examples were also identified where POLD1 or POLE3 could replace PARP-1 or MUTYH from the BER group of genes providing predictive value.
  • BER genes that were particularly useful include POLD1 and POLE3.
  • HR group of genes Table 2
  • Table 12 shows that each of AURKA, SMARCD3, ZIC1 , SSX2IP, BOC, POLH, TP53BP2, SCMH1 , SMARCA5, MRAS, IP6K2, GTF2H4, MBD1 , RASA3, ZMYM4, PHF13, ARNT, KDM4A, PCBP4, TLR4, NUDT1 , PMS1 and ZMYM6 increased the predictive value when combined with a gene from Table 1 and Table 2.
  • the invention provides a method for selecting a cancer patient for treatment with a PARP inhibitor comprising measuring the expression level of at least one BER biomarker from Table 1 , at least one homologous recombination biomarker from Table 2 and at least one proliferation biomarker from Table 3, in a cancer cell containing sample obtained from the patient and selecting the patient for treatment with a PARP inhibitor if the expression profile of the at least three biomarkers identifies the patient as being a likely responder to treatment with the PARP inhibitor.
  • the biomarker(s) from Table 1 is selected from PARP-1 and MUTYH, POLD1 or POLE3.
  • the homologous recombination biomarker from Table 2 is selected from: MCM2, XRCC3, BRCA1 , MDC1 , ATM, ATR, NBN, RAD51 and MRE1 1A.
  • the proliferation biomarker from Table 3 is selected from: AURKA, SMARCD3, ZIC1 , SSX2IP, BOC, POLH, TP53BP2, SCMH1 , SMARCA5, MRAS, IP6K2, GTF2H4, MBD1 , RASA3, ZMYM4, PHF13, ARNT, KDM4A, PCBP4, TLR4, NUDT1 , PMS1 and ZMYM6.
  • AURKA, SMARCD3, ZIC1 , SSX2IP and BOC is selected from: MCM2, XRCC3, BRCA1 , MDC1 , ATM, ATR, NBN, RAD51 and MRE1 1A.
  • the proliferation biomarker from Table 3 is selected from: AURKA, SMARCD3, Z
  • one or more, such as 2, 3, 4, 5, 6, 7, 8, 9, 10 or more of the other biomarkers identified in Table 1 are also assessed for their expression level.
  • At least 2, at least 3, at least 4, at least 5 or more BER biomarkers from Table 1 are assessed. In certain other embodiments, when more than one BER biomarker is assessed, one of these is PARP-1 or MUTYH.
  • At least 2, such as 3, 4, 5, 6, 7, 8, 9, 10, or more of the other biomarkers identified in Table 2 are also assessed for their expression level.
  • at least one HR biomarker is selected from the first 20 biomarkers listed in Table 2.
  • at least 2, at least 3, at least 4, at least 5 or more HR biomarkers from Table 2 are assessed.
  • the HR biomarker is selected from the group consisting of: MCM2, XRCC3, BRCA1 , MDC1 , ATM, ATR, NBN, RAD51 and MRE1 1A.
  • At least 2, such as 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 60, 70, 80, 90, 100 or more of the other biomarkers identified in Table 3 are also assessed for their expression level.
  • the at least one proliferation biomarker is selected from the first 20 biomarkers listed in Table 3.
  • at least 2, at least 3, at least 4, at least 5 or more proliferation biomarkers from Table 3 are assessed.
  • the proliferation biomarker from Table 3 is selected from: AURKA, SMARCD3, ZIC1 , SSX2IP, BOC, POLH, TP53BP2, SCMH1 , SMARCA5, MRAS, IP6K2, GTF2H4, MBD1 , RASA3, ZMYM4, PHF13, ARNT, KDM4A, PCBP4, TLR4, NUDT1 , PMS1 and ZMYM6, in particular from AURKA, SMARCD3, ZIC1 , SSX2IP and BOC.
  • the combination of 1 biomarker from Table 1 , one from Table 2 and one from Table 3 is any of the combinations shown in Figures 6- 10. According to certain embodiments, the methods of the invention involve
  • the set of biomarkers may involve just the recited 3 biomarkers or it may also involve one or more additional biomarkers, which additional biomarker may be from Table 1 , 2 or 3.
  • the differential biomarker expression values thus provide a profile of expression for the particular cancer cells and a prediction of likely response to treatment with a PARP inhibitor.
  • the examples described herein assessed the expression levels of each of the biomarkers listed in Tables 1 , 2 and 3 in the 95 cancer cell lines and determined a p-value for the expression of the marker in olaparib sensitive cell lines, compared to resistant cell lines.
  • the highest ranked biomarkers are predicted to be those that will deliver the best predictive value either alone or when combined with the biomarkers from the other Tables. However, it will be appreciated that the most predictive biomarkers for a particular cancer type will likely differ from the most predictive biomarkers for a different cancer type.
  • the one or more biomarker(s), in addition to PARP-1 and/or MUTYH, from Table 1 that are measured are selected from: POLD1 and POLE3.
  • the one or more biomarkers that are measured are selected from the group consisting of MCM2, XRCC3, BRCA1 , MDC1 , ATM, ATR, NBN, RAD51 and MRE1 1 A.
  • the one or more biomarkers that are measured are selected from the first 20 listed in Table 3.
  • the one or more biomarkers that are measured are selected from the group consisting of: AURKA, SMARCD3, ZIC1 , SSX2IP, BOC, POLH, TP53BP2, SCMH1 , SMARCA5, MRAS, IP6K2, GTF2H4, MBD1 , RASA3, ZMYM4, PHF13, ARNT, KDM4A, PCBP4, TLR4, NUDT1 , PMS1 and ZMYM6, in particular from AURKA, SMARCD3, ZIC1 , SSX2IP and BOC.
  • diagnostic patient selection methods do not involve the actual step of isolating the cancer cell-containing sample. Rather they are carried out on samples that have previously been isolated and are thus ex vivo diagnostic tests.
  • An individual suitable for treatment or identification as described herein may include a eukaryote, an animal, a vertebrate animal, a mammal, a rodent (e.g. a guinea pig, a hamster, a rat, a mouse), a murine (e.g. a mouse), a canine (e.g. a dog), a feline (e.g. a cat), an equine (e.g. a horse), a primate, such as a simian (e.g. a monkey or ape), a monkey (e.g. marmoset, baboon), an ape (e.g. gorilla, chimpanzee, gibbon), or a human.
  • the various aspects of the invention are particularly suited for application to humans.
  • Biomarker expression patterns of the invention may be identified by analysis of gene expression in samples containing cancer cells, e.g. tumour biopsies or blood samples that contain circulating cancer cells.
  • the overall gene expression profile of a sample can be obtained through quantifying the expression levels of mRNA or protein corresponding to one or more of the genes (biomarkers) identified herein, that the inventors have found correlate with response to PARP inhibitor.
  • the correlated biomarkers may be used singly with significant accuracy or in combination to increase the ability to accurately predict favourable treatment with a PARP inhibitor, in particular olaparib.
  • the present invention thus provides means for correlating a molecular expression phenotype with likely outcome following PARP inhibitor treatment.
  • Expression of the biomarkers can be determined at the protein or nucleic acid level using any method known in the art. For example, at the nucleic acid level Northern hybridization analysis using probes which specifically recognize one or more of these sequences can be used to determine gene expression.
  • expression can be measured using reverse-transcription-based PCR assays, e.g., using primers specific for the differentially expressed sequence of genes.
  • the diagnostic methods of the invention are carried out on fresh samples, frozen samples or formalin-fixed, paraffin-embedded tissue samples.
  • An assay of the invention may utilize a means related to the expression level of a biomarker disclosed herein as long as the assay reflects, quantitatively or qualitatively, expression of the biomarker.
  • a quantitative assay is performed. The ability to discriminate is conferred by the identification of expression of the individual biomarkers as relevant and not by the form of the assay used to determine the actual level of expression.
  • An assay may utilize any identifying feature of an identified individual biomarker as disclosed herein as long as the assay reflects, quantitatively or qualitatively, expression of the biomarker. Identifying features include, but are not limited to, unique nucleic acid sequences used to encode (DNA), or express (RNA), said gene or epitopes specific to, or activities of, a protein encoded by said gene.
  • Alternative means include detection of nucleic acid amplification as indicative of increased expression levels and nucleic acid inactivation, deletion, or methylation, as indicative of decreased expression levels.
  • the invention may be practiced by assaying one or more aspect of the DNA template(s) underlying the expression of the disclosed sequence(s), of the RNA used as an intermediate to express the sequence(s), or of the
  • cancer cell-containing sample from the patient for analysis.
  • This can for example, be cells from a solid biopsy sample or may be circulating cancer (tumour) cells (CTCs).
  • any method known in the art may be utilized.
  • expression based on detection of mRNA, which hybridizes to the genes identified and disclosed herein is used. This is readily performed by any RNA detection or amplification+detection method known or recognized as equivalent in the art such as, but not limited to, reverse transcription-PCR, the methods disclosed in U.S. patent publication number US2003/0022194 (claiming priority from U.S. patent application Ser. No.
  • RNA stabilizing or destabilizing sequences 60/298,847 and 60/257,801 , and US regular application 10/062,857), and methods to detect the presence, or absence, of RNA stabilizing or destabilizing sequences.
  • the detection of gene expression from the samples may be by use of a single microarray able to assay gene expression of the genes disclosed herein.
  • the expression levels are determined by microarray analysis.
  • one embodiment of the invention involves determining expression by hybridization of mRNA, or an amplified or cloned version thereof, of a sample cell to a polynucleotide that is unique to a particular gene sequence.
  • one or more sequences capable of hybridising to one or more of the genes identified herein is immobilised on a solid support or microarray.
  • the immobilized gene(s) may be in the form of polynucleotides that are unique or otherwise specific to the gene(s) such that the polynucleotide would be capable of hybridizing to a DNA or RNA corresponding to the gene(s).
  • These polynucleotides may be the full length of the gene(s) or be short sequences of the genes (up to one nucleotide shorter than the full length sequence known in the art by deletion from the 5' or 3' end of the sequence) that are optionally minimally interrupted (such as by mismatches or inserted non-complementary base pairs) such that hybridization with a DNA or RNA corresponding to the gene(s) is not affected.
  • the polynucleotides used are from the 3' end of the gene, such as within about 350, about 300, about 250, about 200, about 150, about 100, or about 50 nucleotides from the polyadenylation signal or
  • Preferred polynucleotides contain at least about 18, at least about 20, at least about 22, at least about 24, at least about 26, at least about 28, at least about 30, or at least about 32, at least about 34, at least about 36, at least about 38, at least about 40, at least about 42, at least about 44, or at least about 46 consecutive base pairs of a gene sequence that is not found in other gene sequences.
  • the term "about” as used in the previous sentence refers to an increase or decrease of 1 from the stated numerical value.
  • the term "about” as used in the preceding sentence refers to an increase or decrease of 10% from the stated numerical value.
  • polynucleotides may also be referred to as polynucleotide probes that are capable of hybridizing to sequences of the genes, or unique portions thereof, described herein.
  • the sequences are those of mRNA encoded by the genes, the corresponding cDNA to such mRNAs, and/or amplified versions of such sequences.
  • the polynucleotide probes are immobilized on a microarray, other devices, or in individual spots that localize the probes on a support. Polynucleotides containing mutations relative to the sequences of the disclosed genes may also be used so long as the presence of the mutations still allows hybridization to produce a detectable signal.
  • all or part of a disclosed biomarker sequence may be amplified and detected by methods such as the polymerase chain reaction (PCR) and variations thereof, such as, but not limited to,
  • PCR polymerase chain reaction
  • Q-PCR quantitative PCR
  • RT-PCR reverse transcription PCR
  • real-time PCR including as a means of measuring the initial amounts of mRNA copies for each sequence in a sample
  • Q-PCR quantitative PCR
  • RT-PCR reverse transcription PCR
  • real-time PCR including as a means of measuring the initial amounts of mRNA copies for each sequence in a sample
  • Q-PCR quantitative PCR
  • RT-PCR reverse transcription PCR
  • real-time PCR including as a means of measuring the initial amounts of mRNA copies for each sequence in a sample
  • Q-PCR quantitative PCR
  • RT-PCR reverse transcription PCR
  • real-time PCR including as a means of measuring the initial amounts of mRNA copies for each sequence in a sample
  • Q-PCR quantitative PCR
  • RT-PCR reverse transcription PCR
  • real-time PCR including as a means of measuring the initial amounts of mRNA copies for each sequence in a sample
  • Q-PCR quantitative PCR
  • RT-PCR reverse transcription PCR
  • the expression level is determined by reverse phase polymerase chain reaction (RT-PCR).
  • RT-PCR reverse phase polymerase chain reaction
  • RNA is fragmented.
  • the nucleic acid derived from the sample cancer cell(s) may be preferentially amplified by use of appropriate primers such that only the genes to be analyzed are amplified to reduce contaminating background signals from other genes expressed in the cancer cell.
  • the nucleic acid from the sample may be globally amplified before hybridization to the immobilized polynucleotides.
  • RNA or the cDNA counterpart thereof may be directly labelled and used, without amplification, by methods known in the art.
  • the isolation and analysis of a cancer-cell containing sample may be performed as follows: (1 ) RNA is extracted from a tissue biopsy sample obtained from a cancer patient;
  • RNA is purified, amplified, and labelled
  • Binding of a probe to target nucleic acid may be measured using any of a variety of techniques at the disposal of those skilled in the art.
  • probes may be radioactively, fluorescently or enzymatically labelled.
  • Other methods not employing labelling of probe include examination of restriction fragment length polymorphisms, amplification using PCR, RN'ase cleavage and allele specific oligonucleotide probing.
  • Suitable selective hybridisation conditions for oligonucleotides of 17 to 30 bases include hybridization overnight at 42°C in 6X SSC and then washing in 6X SSC at a series of increasing temperatures from 42°C to 65°C.
  • probes may be washed in 6xSSC at 42 °C for 30 minutes then 6xSSC at 50°C for 45 mins then 2xSSC for 45 mins at 65°C.
  • Other suitable conditions and protocols are described in Molecular Cloning: a Laboratory Manual: 3rd edition, Sambrook & Russell (2001 ) Cold Spring Harbor Laboratory Press NY and Current Protocols in
  • gene expression may be determined at the protein level, e.g. by measuring the levels of peptides encoded by the gene products described herein, or activities thereof.
  • Such methods are well known in the art and include, e.g., any immunohistochemistry (IHC) based, blood based (especially for secreted proteins), antibody (including autoantibodies against the protein) based, ex foliate cell (from the cancer) based, mass spectroscopy based, and image (including used of labelled ligand) based method known in the art and recognized as appropriate for the detection of the protein.
  • the detection is via an immunoassay that uses one or more antibodies specific for one or more epitopes of individual gene products in a cell sample of interest. Any biological material can be used for the
  • a suitable method can be selected to determine the activity of proteins encoded by the marker genes according to the activity of each protein analyzed.
  • the biomarker proteins can be detected in any suitable manner, but are typically detected by contacting a sample from the patient with an antibody that binds the biomarker protein and then detecting the presence or absence of a reaction product. Such as, by use of labelled antibodies against cell surface markers followed by fluorescence activated cell sorting (FACS). Such antibodies are preferably labelled to permit their easy detection after binding to the gene product.
  • Detection methodologies suitable for use in the practice of the invention include, but are not limited to, immunohistochemistry of cell containing samples or tissue, enzyme linked immunosorbent assays (ELISAs) including antibody sandwich assays of cell containing tissues or blood samples, mass spectroscopy, and immuno-PCR.
  • the antibody may be monoclonal, polyclonal, chimeric, or a fragment of the foregoing, as discussed in detail above, and the step of detecting the reaction product may be carried out with any suitable immunoassay.
  • the sample from the subject is typically a solid tissue sample, e.g. a biopsy, as described above, but may be a cancer cell containing biological fluid, e.g. blood or serum sample.
  • the sample may be in the form of a tissue specimen from a patient where the specimen is suitable for immunohistochemistry in a variety of formats such as paraffin-embedded tissue, frozen sections of tissue, and freshly isolated tissue.
  • the immunodetection methods are antibody-based but there are numerous additional techniques that allow for highly sensitive determinations of binding to an antibody in the context of a tissue. Those skilled in the art will be familiar with various immunohistochemistry strategies.
  • Immunoassays carried out in accordance with the present invention may be homogeneous assays or heterogeneous assays.
  • the immunological reaction usually involves the specific antibody (e.g., anti- biomarker protein antibody), a labelled analyte, and the sample of interest.
  • the signal arising from the label is modified, directly or indirectly, upon the binding of the antibody to the labelled analyte.
  • Both the immunological reaction and detection of the extent thereof are carried out in a homogeneous solution.
  • Immunochemical labels that may be employed include free radicals, radioisotopes, fluorescent dyes, enzymes, bacteriophages, or coenzymes.
  • the reagents are usually the sample, the antibody, and means for producing a detectable signal.
  • Samples as described above may be used.
  • the antibody is generally immobilized on a support, such as a bead, plate or slide, and contacted with the specimen suspected of containing the antigen in a liquid phase.
  • the support is then separated from the liquid phase and either the support phase or the liquid phase is examined for a detectable signal employing means for producing such signal.
  • the signal is related to the presence of the analyte in the sample.
  • Means for producing a detectable signal include the use of radioactive labels, fluorescent labels, or enzyme labels.
  • an antibody which binds to that site can be conjugated to a detectable group and added to the liquid phase reaction solution before the separation step.
  • the presence of the detectable group on the solid support indicates the presence of the antigen in the test sample.
  • suitable immunoassays are radioimmunoassays, immunofluorescence methods, chemiluminescence methods, electrochemiluminescence or enzyme-linked immunoassays.
  • Antibodies may be conjugated to a solid support suitable for a diagnostic assay (e.g., beads, plates, slides or wells formed from materials such as latex or polystyrene) in accordance with known techniques, such as passive binding.
  • a diagnostic assay e.g., beads, plates, slides or wells formed from materials such as latex or polystyrene
  • Antibodies as described herein may likewise be conjugated to detectable groups such as radiolabels (e.g., 35 S, 125 I, 131 I), enzyme labels (e.g., horseradish peroxidase, alkaline phosphatase), and fluorescent labels (e.g., fluorescein) in accordance with known techniques.
  • radiolabels e.g., 35 S, 125 I, 131 I
  • enzyme labels e.g., horseradish peroxidase, alkaline phosphatase
  • fluorescent labels e.g., fluorescein
  • nucleic acid probes e.g., oligonucleotides, aptamers, siRNAs against any of the biomarkers in Tables 1 , 2 or 3.
  • the present invention may be practised with any subset of the genes, as disclosed herein.
  • 2 or more, 3 or more, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more, 9 or more, 10 or more, 15 or more, 20 or more, 30 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80 or more, 90 or more, 100 or more or all the genes provided in Table 1 , 2 or 3 below may be used in combination to increase the accuracy of the method.
  • the invention thus specifically contemplates the use of a multiplex assay system employing a number of biomarkers from each of Tables 1 , 2 and 3 for use as a subset in the identification of whether a cancer sample is one that will respond favourably to treatment with a PARP inhibitor.
  • a number of different statistical algorithms can be applied in order to generate a mathematical model combining together the expression levels of two or more genes or proteins with a cut-off to classify subjects as predicted olaparib responders. These include, but are not limited to logistic regression, multiple regression, Cox proportional hazard models, random forests, recursive
  • partitioning random survival forests, partial least squares, partial least squares discriminant analysis, Support Vector Machines, neural networks.
  • Increases and decreases in expression of the disclosed sequences can be determined based upon percent or fold changes over expression in normal cells, reference cells or normalised against one or more housekeeping genes. Increases may be of 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 120, 140, 160, 180, or 200% relative to expression levels in normal cells. Alternatively, fold increases may be of 1 , 1 .5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, or 10 fold over expression levels in normal cells.
  • Decreases may be of 10, 20, 30, 40, 50, 55, 60, 65, 70, 75, 80, 82, 84, 86, 88, 90, 92, 94, 96, 98, 99 or 100% relative to expression levels in normal cells. For example, a 2-fold increase or decrease is a useful measure for determining whether or not the expression level is low or high.
  • the actual level of expression of any biomarker used according to the invention to predict response to a PARP inhibitor will need to be determined empirically using clinical samples and an appropriate algorithm as described further herein.
  • kits comprising agents for the detection of expression of the disclosed genes for determining susceptibility to treatment with a PARP inhibitor.
  • a kit may comprise separate containers, each with one or more of the various reagents (typically in concentrated form) utilized in the methods, e.g., The kit may contain in separate containers one or more nucleic acids or antibodies (either already bound to a solid matrix or packaged separately with reagents for binding them to the matrix), control formulations (positive and/or negative), and/or a detectable label, as well as other reagents such as buffers, nucleotide
  • kits packaged together in the form of a kit.
  • Instructions e.g., written, or on electronic medium, e.g. CD-ROM, etc.
  • the assay may for example be in the form of a Northern hybridization or a sandwich ELISA as known in the art.
  • Suitable cancer cell(s) for use in the described methods may be obtained from an individual in a tissue sample for example a biopsy from a cancerous tissue or a blood sample that contains circulating tumour cells.
  • the cancer can be any cancer.
  • the cancer is selected from the group consisting of breast cancer, colorectal cancer, head and neck cancer, lung cancer, gastric cancer, prostate, haematological cancers, pancreatic cancer and ovarian cancer.
  • the expression level of the biomarker(s) can be compared to that detected in control cell(s), which may be obtained from non-cancerous tissue from the same or a different individual.
  • Suitable controls include non-cancer cells from the same tissue or lineage. Comparison can be performed on test and reference samples measured concurrently or at temporally distinct times. An example of the latter is the use of compiled expression information, e.g., a sequence database, which assembles information about expression levels of the biomarker(s). If the reference sample, e.g., a control sample is from cells that are sensitive to a therapeutic compound then a similarity in the amount of the biomarker proteins in the test sample and the reference sample indicates that treatment with that therapeutic compound will be efficacious.
  • a change in the amount of the biomarker in the test sample and the reference sample indicates treatment with that compound will result in a less favourable clinical outcome or prognosis.
  • the reference sample e.g., a control sample is from cells that are resistant to a therapeutic compound
  • a similarity in the amount of the biomarker proteins in the test sample and the reference sample indicates that the treatment with that compound will result in a less favourable clinical outcome or prognosis.
  • a change in the amount of the biomarker in the test sample and the reference sample indicates that treatment with that therapeutic compound will be efficacious.
  • the pattern of biomarker expression in the test sample is measured and then may be normalised against one or more control genes.
  • control genes against which the biomarker expression levels can be normalised include, but are not limited to: ACTB (ACTB 60), B2M (B2M 567), GAPDH (GAPDH 2597), GUSB (GUSB 2990), HMBS (HMBS 3145), HPRT1 (HPRT1 3251 ), IPO8 (IPO8 10526), PGK1 (PGK1 5230), POLR2A (POLR2A 5430), PPIA (PPIA 5478), RPLP0 (RPLP0 6175), TBP (TBP 6908), TFRC (TFRC 7037), UBC (UBC 7316), YWHAZ (YWHAZ 7534);
  • the Entrez gene IDs are in brackets. Another commonly used housekeeping gene is 18s rRNA (Genbank accession number is X03205).
  • a mathematical algorithm which has been pre-determined by the analysis of preclinical or historical clinical data cane then be applied to the expression measures to give a prediction of the sensitivity to olaparib.
  • the methods provided by the present invention may also be automated in whole or in part. All aspects of the present invention may also be practiced such that they consist essentially of a subset of the disclosed genes to the exclusion of material irrelevant to the identification of cells treatable with a PARP inhibitor.
  • the diagnostic methods permit the identification of which patient or patient populations are likely to be responsive to treatment with a PARP inhibitor, such as olaparib. Accordingly, the present invention also opens up the possibility of treating the patient or patient populations identified as likely to be responsive to a PARP inhibitor.
  • a method of treating a patient suffering from cancer comprising determining whether or not the patient will respond favourably to a PARP inhibitor according the method as claimed in any of claims, and administering an effective amount of a PARP inhibitor to said patient if they are identified as likely to be responsive to treatment with a PARP inhibitor.
  • a method of treating cancer comprising determining the expression level of PARP-1 in a cancer cell containing sample from the subject and if the PARP-1 expression level is not low, administering to the subject an effective amount of a PARP inhibitor.
  • the PARP inhibitor is olaparib.
  • a method of treating cancer comprising determining the expression level of PARP-1 and/or MUTYH and one or more genes involved in homologous recombination repair as listed in Table 2 in a cancer cell containing sample from a patient, and administering an effective amount of a PARP inhibitor compound to a patient whose cancer cells do not express low levels of PARP-1 or MUTYH but do express differences in expression in any of the homologous recombination repair genes according to Table 2, and in particular the directionality shown therein.
  • the PARP inhibitor is olaparib.
  • the homologous recombination repair gene is selected from: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1 A.
  • a method of treating cancer comprising measuring the expression level of at least one base excision repair biomarker from Table 1 , at least one homologous recombination biomarker from Table 2 and at least one proliferation biomarker from Table 3, in a cancer cell containing sample obtained from the patient and if the expression profile of the biomarkers identifies the patient as being a likely responder to treatment with the PARP inhibitor, administering to said patient an effective amount of a PARP inhibitor.
  • the PARP inhibitor is olaparib.
  • the biomarker(s) from Table 1 is selected from PARP-1 and MUTYH.
  • the homologous recombination biomarker from Table 2 is selected from: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1A.
  • the proliferation biomarker from Table 3 is selected from AURKA, SMARCD3, ZIC1 , SSX2IP, BOC, POLH, TP53BP2, SCMH1 , SMARCA5, MRAS, IP6K2, GTF2H4, MBD1 , RASA3, ZMYM4, PHF13, ARNT, KDM4A, PCBP4, TLR4, NUDT1 , PMS1 and ZMYM6.
  • a method for selecting a cancer patient for treatment with a PARP inhibitor comprising: measuring the expression level of at least three biomarker RNA transcripts or their products in a cancer cell containing sample obtained from said patient, wherein at least one of the biomarkers is selected from Table 1 , at least one of the biomarkers is selected from Table 2; and, at least one of the biomarkers is selected from Table 3, comparing the level of each measured biomarker in the sample to a reference level; and selecting a patient for treatment with a PARP inhibitor based on the biomarker levels present in the sample, with the proviso that PARP-1 represents one biomarker from Table 1 whose expression level is measured.
  • a PARP inhibitor for use in the treatment of a cancer patient whose cancer cells have been identified as not expressing low levels of PARP-1 .
  • the PARP inhibitor is olaparib.
  • a PARP inhibitor for use in the treatment of a cancer patient whose cancer cells have been identified as not expressing low levels of MUTYH.
  • the PARP inhibitor is olaparib.
  • a PARP inhibitor for use in the treatment of a cancer patient whose cancer cells have been identified as not expressing low levels of MUTYH do express differences in expression in any of the homologous recombination repair genes according to Table 2, and in particular differences in the directionality shown in Table 2.
  • the PARP inhibitor is olaparib.
  • the homologous recombination repair gene is selected from: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1A.
  • a PARP inhibitor for use in the treatment of a cancer patient whose cancer cells have been identified as being likely to be responsive to treatment with the PARP inhibitor according to the expression profile generated by measuring the expression levels of PARP-1 and/or MUTYH and at least one homologous recombination repair gene from Table 2.
  • BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1 A is selected for treatment and/or treated with the PARP inhibitor compound.
  • a PARP inhibitor for use in the treatment of a cancer patient whose cancer cells have been identified as being likely to respond to treatment with the PARP inhibitor according to the gene expression profile generated by measuring the expression level of at least one base excision repair biomarker from Table 1 , at least one homologous recombination biomarker from Table 2 and at least one proliferation biomarker from Table 3, in a cancer cell containing sample obtained from the patient .
  • the PARP inhibitor is olaparib.
  • the biomarker(s) from Table 1 is selected from PARP-1 and MUTYH.
  • the homologous recombination biomarker from Table 2 is selected from: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1 A.
  • the proliferation biomarker from Table 3 is selected from AURKA, SMARCD3, ZIC1 , SSX2IP, BOC, POLH, TP53BP2, SCMH1 , SMARCA5, MRAS, IP6K2, GTF2H4, MBD1 , RASA3, ZMYM4, PHF13, ARNT, KDM4A, PCBP4, TLR4, NUDT1 , PMS1 and ZMYM6.
  • a PARP inhibitor in the manufacture of a medicament for treating a cancer patient whose cancer cells have been identified as not expressing low levels of PARP-1 .
  • the PARP inhibitor is olaparib.
  • a PARP inhibitor in the manufacture of a medicament for treating a cancer patient whose cancer cells have been identified as not expressing low levels of MUTYH.
  • the PARP inhibitor is olaparib.
  • a PARP inhibitor in the manufacture of a medicament for treating a cancer patient whose cancer cells have been identified as being likely to be responsive to treatment with the PARP inhibitor according to the expression profile generated by measuring the expression levels of PARP-1 and/or MUTYH and at least one homologous recombination repair gene from Table 2.
  • the cancer cells are identified as being likely to be responsive to treatment with the PARP inhibitor if the cancer cells do not express low levels of PARP-1 and/or MUTYH but do express low levels of any of the homologous recombination repair genes from Table 2.
  • the PARP inhibitor is olaparib.
  • the cancer cells are identified as being likely to be responsive to treatment with the PARP inhibitor if the cancer cells do not express low levels of PARP-1 and/or MUTYH but do express low levels of any of the homologous recombination repair genes from Table 2.
  • the PARP inhibitor is olaparib.
  • homologous recombination repair gene is selected from: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1 A.
  • a PARP inhibitor in the manufacture of a medicament for treating a cancer patient whose cancer cells have been identified as not expressing low levels of PARP-1 and/or MUTYH but do express differences in expression in any of the homologous recombination repair genes according to Table 2, and in particular according to the directionality in Table 2.
  • the PARP inhibitor is olaparib.
  • the homologous recombination repair gene is selected from: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1 A.
  • a PARP inhibitor in the manufacture of a medicament for treating a cancer patient whose cancer cells have been identified as not expressing low levels of PARP-1 and/or MUTYH but do express differences in expression in any of the homologous recombination repair genes according to Table 2, and in particular according to the directionality in Table 2.
  • a PARP inhibitor in the manufacture of a medicament for treating a cancer patient whose cancer cells have been tested for expression level of at least one base excision repair biomarker from Table 1 , at least one homologous recombination biomarker from Table 2 and at least one proliferation biomarker from Table 3, and the expression profile of the biomarkers has identified the patient as being a likely responder to treatment with the PARP inhibitor.
  • the PARP inhibitor is olaparib.
  • the biomarker(s) from Table 1 is selected from PARP-1 and MUTYH.
  • the homologous recombination biomarker from Table 2 is selected from: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1A.
  • the proliferation biomarker from Table 3 is selected from AURKA, SMARCD3, ZIC1 , SSX2IP, BOC, POLH, TP53BP2, SCMH1 , SMARCA5, MRAS, IP6K2, GTF2H4, MBD1 , RASA3, ZMYM4, PHF13, ARNT, KDM4A, PCBP4, TLR4, NUDT1 , PMS1 and ZMYM6.
  • a treatment regimen comprising administration of a PARP inhibitor to a patient may be designed for an individual identified according to the present invention.
  • a suitable PARP inhibitor may be selected and the dosage and schedule of administration established for the individual using appropriate medical criteria.
  • the methods described herein may be particularly useful in identifying cohorts of cancer patients, for example for clinical trials of PARP inhibitor compounds.
  • 'PARP' refers to PARP-1 (EC 2.4.2.30, Genbank No: M32721 .1 Gl: 190266, D'Amours et al, (1999) Biochem. J. 342: 249-268; Ame et al., BioEssays (2004) 26 882-893) and/or PARP2 (Ame et al., J. Biol. Chem.
  • PARP inhibition may be determined using conventional methods, including for example dot blots (Affar EB et al., Anal Biochem. 1998; 259(2):280-3), and BER assays that measure the direct activity of PARP to form poly ADP-ribose chains for example by using radioactive assays with tritiated substrate NAD or specific antibodies to the polymer chains formed by PARP activity (K.J. Dillon et al, Journal of Biomolecular Screening, 8(3): 347-352 (2003). Examples of suitable methods for determining PARP activity are described below.
  • Examples of compounds which are known PARP inhibitors and which may be used in accordance with the invention include:
  • Nicotinamides such as 5-methyl nicotinamide and O-(2-hydroxy-3- piperidino-propyl)-3-carboxylic acid amidoxime, and analogues and derivatives thereof.
  • Benzamides including 3-substituted benzamides such as 3- aminobenzamide, 3-hydroxybenzamide, 3-nitrosobenzamide, 3- methoxybenzamide and 3-chloroprocainamide, and 4-aminobenzamide, 1 , 5-di[(3- carbamoylphenyl)aminocarbonyloxy] pentane, and analogues and derivatives thereof.
  • Isoquinolinones and Dihydroisoquinolinones including 2H-isoquinolin-1 -ones, 3H-quinazolin-4-ones, 5-substituted dihydroisoquinolinones such as 5-hydroxy dihydroisoquinolinone, 5-methyl dihydroisoquinolinone, and 5-hydroxy
  • Benzimidazoles and indoles including benzoxazole-4-carboxamides, benzimidazole-4-carboxamides, such as 2-substituted benzoxazole 4- carboxamides and 2-substituted benzimidazole 4-carboxamides such as 2-aryl benzimidazole 4-carboxamides and 2-cycloalkylbenzimidazole-4-carboxamides including 2-(4-hydroxphenyl) benzimidazole 4-carboxamide,
  • Phthalazin-1 (2H)-ones and quinazolinones such as 4-hydroxyquinazoline, phthalazinone, 5-methoxy-4-methyl-1 (2) phthalazinones, 4-substituted
  • phthalazinones 4-(1 -piperazinyl)-1 (2H)-phthalazinone, tetracyclic benzopyrano[4, 3, 2-de] phthalazinones and tetracyclic indeno [1 , 2, 3-de] phthalazinones and 2- substituted quinazolines, such as 8-hydroxy-2-methylquinazolin-4-(3H) one, tricyclic phthalazinones and 2-aminophthalhydrazide, and analogues and derivatives thereof.
  • Phenanthridines and phenanthhdinones such as 5[H]phenanthhdin-6-one, substituted 5[H] phenanthridin-6-ones, especially 2-, 3- substituted 5[H]
  • 6(5H)phenanthhdinones thieno[2, 3-c]isoquinolones such as 9-annino thieno[2, 3- c]isoquinolone and 9-hydroxythieno[2, 3-c]isoquinolone, 9-methoxythieno[2, 3- c]isoquinolone, and N-(6-oxo-5, 6-dihydrophenanthridin-2-yl]-2-(N,N- dimethylannino ⁇ acetannide, substituted 4,9-dihydrocyclopenta[lmn]phenanthridine- 5-ones, and analogues and derivatives thereof.
  • Benzopyrones such as 1 , 2-benzopyrone, 6-nitrosobenzopyrone, 6-nitroso 1 , 2- benzopyrone, and 5-iodo-6-aminobenzopyrone, and analogues and derivatives thereof.
  • Unsaturated hydroximic acid derivatives such as O-(3-piperidino-2-hydroxy- 1 -propyl)nicotinic amidoxime, and analogues and derivatives thereof.
  • Pyridazines including fused pyridazines and analogues and derivatives thereof.
  • the PARP inhibitor is selected from the group consisting of: benzamide, quinolone, isoquinolone, benzopyrone, methyl 3,5-diiodo-4-(4'-methoxyphenoxy)benzoate, and methyl-3,5-diiodo-4-(4'-methoxy- 3',5'-diiodo-phenoxy)benzoate, cyclic benzamide, benzimidazole and indole.
  • a PARP inhibitor includes phthalazinones such as 1 (2H)- phthalazinone and derivatives thereof, as described in WO02/36576, which is incorporated herein by reference.
  • a PARP inhibitor may be a compound of the formula (I):
  • RC is represented by -L-RL, where L is of formula:
  • RL is optionally substituted C5-20 aryl
  • RN is selected from hydrogen, optionally substituted C1 -7 alkyl, C3-20
  • heterocyclyl and C5-20 aryl, hydroxy, ether, nitro, amino, amido, thiol, thioether, sulfoxide and sulfone.
  • a preferred compound may have the formula (I) wherein:
  • RC is -CH2-RL
  • RL is optionally substituted phenyl
  • RN is hydrogen
  • Suitable PARP inhibitors are described in WO 2004/080976, which is incorporated herein by reference, and may have the formula (III):
  • X can be NRX or CRXRY
  • RX is selected from the group consisting of H, optionally substituted C1 -20 alkyl, C5-20 aryl, C3-20 heterocyclyl, amido, thioamido, ester, acyl, and sulfonyl groups;
  • RY is selected from H, hydroxy, amino;
  • RX and RY may together form a spiro-C3-7 cycloalkyl or heterocyclyl group;
  • RC1 and RC2 are both hydrogen, or when X is CRXRY, RC1 , RC2, RX and RY, together with the carbon atoms to which they are attached, may form an optionally substituted fused aromatic ring; and
  • R1 is selected from H and halo.
  • PARP poly(ADP-ribose)polymerase
  • X and Y are selected from CH and CH, CF and CH, CH and CF and N and CH respectively;
  • R c is selected from H, Ci -4 alkyl
  • R 1 is selected from Ci -7 alkyl, 03-20 heterocyclyl and C 5- 2o aryl, which groups are optionally substituted; or
  • R c and R 1 together with the carbon and oxygen atoms to which they are attached form a spiro-C 5-7 oxygen-containing heterocyclic group, which is optionally substituted or fused to a C 5-7 aromatic ring.
  • a suitable compound, from this patent publication, that can be used according to the present invention is 4-(4-Fluoro-3-(4-methoxypiperidine-1 - carbonyl)benzyl)phthalazin-1 (2H)-one.
  • Other examples of suitable PARP inhibitors are described in WO2008/122810, which is incorporated herein by reference, and have the formula (I):
  • X is selected from H and F;
  • R 1 and R 2 are independently selected from H and methyl
  • R N1 is selected from H and optionally substituted Ci -7 alkyl
  • R N2 is selected from H, optionally substituted Ci -7 alkyl, C3-7 heterocylyl and C 5- 6 aryl;
  • R N1 and R N2 and the nitrogen atom to which they are bound form an optionally substituted nitrogen containing C 5-7 heterocyclic group.
  • R represents one or more optional substituents on the fused cyclohexene ring;
  • R x is selected from the group consisting of H, optionally substituted alkyl, optionally substituted C 5- 2o aryl, optionally substituted 03-20 heterocyclyl, optionally substituted amido, optionally substituted thioamido, optionally substituted ester, optionally substituted acyl, and optionally substituted sulfonyl groups;
  • R x is selected from the group consisting of H, optionally substituted alkyl, optionally substituted C 5- 2o aryl, optionally substituted 03-20 heterocyclyl, optionally substituted amido, optionally substituted thioamido, optionally substituted sulfonamino, optionally substituted ether, optionally substituted ester, optionally substituted acyl, optionally substituted acylamido and optionally substituted sulfonyl groups and R Y is selected from H, hydroxy, optionally substituted amino, or R x and R Y may together form an optionally substituted spiro-C3-7 cycloalkyl or heterocyclyl group;
  • R C1 and R C2 are both hydrogen, or when X is CR X R Y , R C1 , R C2 , R x and R Y , together with the carbon atoms to which they are attached, may form an optionally substituted fused aromatic ring;
  • R 1 is selected from H and halo.
  • the present invention can be applied to any compound disclosed and/or exemplified in these patent publications.
  • the PARP inhibitor may be a compound selected from the group consisting of: 3-[2-fluoro-5-(4-oxo-3,4-dihydro-phthalazin-1 - ylmethyl)-phenyl]-5-methyl-imidazolidine-2,4-dione; 3-[3-(5,8-difluoro-4-oxo-3,4- dihydro-phthalazin-1 -ylmethyl)-phenyl]-5-methyl-imidazoline-2,4-dione; 5-chloro- 2- ⁇ 1 -[3-([1 ,4]diazepane-1 -carbonyl)-4-fluoro-phenyl]-ethoxy ⁇ -benzamide; 2- ⁇ 3-[2- fluoro-5-(4-oxo-3,4-dihydro-phthalazin-1 -yl methyl )-phenyl]-5-methyl-2,4-dioxo- imidazolidin-1 -yl ⁇
  • the PARP inhibitor may have a greater potency than the potency of 3-aminobenzamide (IC50 ⁇ 20uM), preferably 5-fold or greater, 10-fold or greater, 50-fold or greater, 100 fold or greater or 1000-fold or greater than the potency of 3-aminobenzamide.
  • Suitable PARP inhibitors are either commercially available or may be synthesized by known methods from starting materials that are known (see, for example, Suto et al. Anticancer Drug Des. 6:107-17, 1991 ).
  • an active PARP inhibitor compound While it is possible for an active PARP inhibitor compound to be administered alone, it is preferable to present it as a pharmaceutical composition (e.g., formulation) comprising at least one active compound, as defined above, together with one or more pharmaceutically acceptable carriers, adjuvants, excipients, diluents, fillers, buffers, stabilisers, preservatives, lubricants, or other materials well known to those skilled in the art and optionally other therapeutic or
  • compositions comprising a PARP inhibitor and/or a kinase- mediated cellular pathway inhibitor as defined above, for example, an inhibitor admixed or formulated together with one or more pharmaceutically acceptable carriers, excipients, buffers, adjuvants, stabilisers, or other materials, as described herein, may be used in the methods described herein.
  • pharmaceutically acceptable refers to compounds, materials, compositions, and/or dosage forms which are, within the scope of sound medical judgement, suitable for use in contact with the tissues of a subject (e.g., human) without excessive toxicity, irritation, allergic response, or other problem or complication, commensurate with a reasonable benefit/risk ratio.
  • a subject e.g., human
  • Each carrier, excipient, etc. must also be “acceptable” in the sense of being compatible with the other ingredients of the formulation.
  • Suitable carriers, excipients, etc. can be found in standard pharmaceutical texts, for example, Remington's Pharmaceutical Sciences, 18th edition, Mack Publishing Company, Easton, Pa., 1990.
  • the formulations may conveniently be presented in unit dosage form and may be prepared by any methods well-known in the art of pharmacy. Such methods include the step of bringing the active compound into association with a carrier, which may constitute one or more accessory ingredients. In general, the formulations are prepared by uniformly and intimately bringing into association the active compound with liquid carriers or finely divided solid carriers or both, and then if necessary shaping the product.
  • Formulations may be in the form of liquids, solutions, suspensions, emulsions, elixirs, syrups, tablets, lozenges, granules, powders, capsules, cachets, pills, ampoules, suppositories, pessaries, ointments, gels, pastes, creams, sprays, mists, foams, lotions, oils, boluses, electuaries, or aerosols.
  • the inhibitor(s) or pharmaceutical composition comprising the inhibitor(s) may be administered to a subject by any convenient route of administration, whether systemically/ peripherally or at the site of desired action, including but not limited to, oral (e.g. by ingestion); topical (including e.g. transdermal, intranasal, ocular, buccal, and sublingual); pulmonary (e.g. by inhalation or insufflation therapy using, e.g. an aerosol, e.g.
  • vaginal parenteral, for example, by injection, including subcutaneous, intradermal, intramuscular, intravenous, intraarterial, intracardiac, intrathecal, intraspinal, intracapsular, subcapsular, intraorbital, intraperitoneal, intratracheal, subcuticular, intraarticular, subarachnoid, and intrasternal; by implant of a depot, for example, subcutaneously or intramuscularly.
  • Formulations suitable for oral administration may be presented as discrete units such as capsules, cachets or tablets, each containing a predetermined amount of the active compound; as a powder or granules; as a solution or suspension in an aqueous or non-aqueous liquid; or as an oil-in-water liquid emulsion or a water-in-oil liquid emulsion; as a bolus; as an electuary; or as a paste.
  • a tablet may be made by conventional means, e.g., compression or moulding, optionally with one or more accessory ingredients.
  • Compressed tablets may be prepared by compressing in a suitable machine the active compound in a free- flowing form such as a powder or granules, optionally mixed with one or more binders (e.g., povidone, gelatin, acacia, sorbitol, tragacanth, hydroxypropyl methyl cellulose); fillers or diluents (e.g., lactose, microcrystalline cellulose, calcium hydrogen phosphate); lubricants (e.g., magnesium stearate, talc, silica);
  • binders e.g., povidone, gelatin, acacia, sorbitol, tragacanth, hydroxypropyl methyl cellulose
  • fillers or diluents e.g., lactose, microcrystalline cellulose, calcium hydrogen phosphate
  • lubricants
  • Moulded tablets may be made by moulding in a suitable machine a mixture of the powdered compound moistened with an inert liquid diluent.
  • the tablets may optionally be coated or scored and may be formulated so as to provide slow or controlled release of the active compound therein using, for example, hydroxypropyl methyl cellulose in varying proportions to provide the desired release profile. Tablets may optionally be provided with an enteric coating, to provide release in parts of the gut other than the stomach.
  • Formulations suitable for parenteral administration include aqueous and non-aqueous isotonic, pyrogen-free, sterile injection solutions which may contain anti-oxidants, buffers, preservatives, stabilisers, bacteriostats, and solutes which render the formulation isotonic with the blood of the intended recipient; and aqueous and non-aqueous sterile suspensions which may include suspending agents and thickening agents, and liposomes or other microparticulate systems which are designed to target the compound to blood components or one or more organs.
  • formulations include Sodium Chloride Injection, Ringer's Solution, or Lactated Ringer's Injection.
  • concentration of the active compound in the solution is from about 1 ng/ml to about 10 ⁇ g ml, for example, from about 10 ng/ml to about 1 ⁇ g/ml.
  • the formulations may be presented in unit-dose or multi-dose sealed containers, for example, ampoules and vials, and may be stored in a freeze-dried (lyophilised) condition requiring only the addition of the sterile liquid carrier, for example water for injections, immediately prior to use.
  • Extemporaneous injection solutions and suspensions may be prepared from sterile powders, granules, and tablets.
  • Formulations may be in the form of liposomes or other microparticulate systems which are designed to target the active compound to blood components or one or more organs.
  • appropriate dosages of the active compounds, and compositions comprising the active compounds can vary from patient to patient. Determining the optimal dosage will generally involve the balancing of the level of therapeutic benefit against any risk or deleterious side effects of the treatments of the present invention.
  • the selected dosage level will depend on a variety of factors including, but not limited to, the activity of the particular compound, the route of administration, the time of administration, the rate of excretion of the compound, the duration of the treatment, other drugs, compounds, and/or materials used in combination, and the age, sex, weight, condition, general health, and prior medical history of the patient.
  • the amount of compound and route of administration will ultimately be at the discretion of the physician, although generally the dosage will be to achieve local concentrations at the site of action which achieve the desired effect without causing substantial harmful or deleterious side-effects.
  • Administration in vivo can be effected in one dose, continuously or intermittently (e.g., in divided doses at appropriate intervals) throughout the course of treatment. Methods of determining the most effective means and dosage of administration are well known to those of skill in the art and will vary with the formulation used for therapy, the purpose of the therapy, the target cell being treated, and the subject being treated. Single or multiple administrations can be carried out with the dose level and pattern being selected by the treating physician.
  • a suitable dose of the active compound is in the range of about 100 ⁇ g to about 250 mg per kilogram body weight of the subject per day.
  • the active compound is a salt, an ester, prodrug, or the like
  • the amount administered is calculated on the basis of the parent compound and so the actual weight to be used is increased proportionately.
  • a cross tumor-type panel of 95 cell lines was tested for sensitivity to olaparib.
  • Baseline (untreated) gene expression profiles were generated using Affymetrix genome-wide U133A 2.0 arrays for each cell line.
  • Current state-of-the- art has suggested that sensitivity to PARP inhibitors can be correlated with high levels of PARP expression (WO 2008/147418, US2007/0292883 and
  • Example 1 Analysis of 95 cancer cell lines (KU95 panel) for their response to olaparib
  • a panel of 95 cancer cell lines representing six tumour types were assessed for their response to single agent olaparib using long-term 2-D colony-formation assays (CFA; clonogenic) with continual exposure to the drug.
  • CFA colony-formation assays
  • Each cell line was plated at an appropriate pre-determined concentration (-150-200 colonies/well in vehicle alone wells) into three 6-well plates and allowed to attach overnight.
  • Olaparib was added to triplicate wells at 0 (vehicle alone), 0.123, 0.370, 1 .1 1 1 , 3.333, 10 ⁇
  • Cellular IC 5 o values were calculated using a dose response curve plotted using XLFit, set with the curve fit 4 Parameter Logistic Model (IDBS XLFit model 205) for each cell line.
  • the baseline mRNA expression levels of HR factors (ATM, ATR, BRCA1 , BRCA2, CHEK2, MDC1 and MRE1 1A), PARP-1 (a BER factor) and ABCB1 (a drug transporter gene) were determined for each cell line in the KU95 cell line panel (see Table 4). Exponentially growing cell lines were grown in 15 cm dishes then washed in ice-cold Ca/Mg-free PBS (Invitrogen), scraped into centrifuge tubes and cells pelleted at 300 x g at a temperature of 4°C for 2 minutes. Supernatants were discarded and cell pellets snap frozen in LN 2 and stored at -80°C until use.
  • HR factors ATM, ATR, BRCA1 , BRCA2, CHEK2, MDC1 and MRE1 1A
  • PARP-1 a BER factor
  • ABCB1 a drug transporter gene
  • Quantitative real-time PCR was performed using well established commercial TaqMan gene expression primer assays and master mix (Applied Biosystems) utilising FAM- MGB fluorescent dye-labelled probes and detection on a StepOnePlus real-time PCR system (Applied Biosystems). Normalised gene expression of ATM, ATR, BRCA1 , BRCA2, CHEK2, MDC1 , MRE1 1 A, PARP-1 and ABCB1 relative to the average of 3 endogenous control genes (PPIA, PGK1 , TBP) was calculated (ACT) for each cell line. Relative gene expression across all 95 cell lines was calculated using 2 _AACT method as described previously (Livak and Schmittgen Methods 25:402-408, 2001 ).
  • the baseline protein expression levels of ATM, ATR, CHEK2, MDC1 , MRE1 1A and PARP-1 were determined for each cell line in the KU95 cell line panel using western blotting with commercially available antibodies and densitometry quantification.
  • Total protein concentration for each extract was determined using the well-known reduction of Cu 2+ to Cu 1+ bicinchoninic acid (BCA) method in the form of commercial BCA Protein Assay Reagent kit from Pierce.
  • Primary antibodies were diluted to an appropriate concentration in MTBS-T buffer (5% skimmed milk powder, 0.05% Tween- 20 in Tris-buffered saline (TBS)) and incubated with the membranes for 2.5 hours at room temperature. Proteins were detected using standard electrochemiluminescent (ECL) reagent methods. Images and protein band intensity were quantified on a LAS- 3000 luminescent image analyser and associated AIDA software (Fujifilm).
  • the term "sensitive" in the context of this Example refers to those cancer cell lines in the KU95 panel that have an IC50 value of less than 1 ⁇ . 1 uM has been found by the applicant to be a pharmacologically relevant concentration for which tumour exposure has been demonstrated for tolerable doses of olaparib in a phase 1 biopsy study clinical trial in man.
  • resistant in the context of this Example refers to those cancer cell lines in the KU95 panel that have an IC50 value of more than 4 ⁇ , which is the concentration just above that achieved in any sample within the phase 1 biopsy trial referred to above.
  • Table 4 lists the KU95 panel of cancer cell lines analysed along with their olaparib IC50 data as determined by 2D-colony formation assays.
  • HR gene mutation black boxes
  • the black boxes in the IC50 column indicate cell lines that demonstrated significant sensitivity to olaparib with IC50 values less than 1 .0 ⁇ (clinically achievable doses).
  • the grey boxes represent cell lines with olaparib sensitivity between 1 .0 and 1 .2 ⁇ .
  • Olaparib IC50 was determined by 2D-colony formation assays.
  • HR gene mutation data were obtained from literature or online public databases. Quantification of mRNA for HR genes (ATM, ATR, BRCA1 , BRCA2, CHEK2, MRE1 1A, MDC1 ), ABCB1 (P-gp drug transporter) and PARP-1 were determined by Taqman RT- PCR and relative expression levels (to mean of KU95 cell panel) calculated using 2- ⁇ me thod. HR gene expression was classified as low if relative mRNA levels were less than 50%. PARP-1 BER gene expression was classified as low if relative mRNA levels less than 50% or classified as high if relative mRNA levels were greater than 200%.
  • ABCB1 gene expression was classified as low if relative mRNA expression levels were up to 100%, moderate if relative expression between 100% and 200% or high if greater than 200%.
  • a number of cell lines that demonstrated high PARP-1 expression levels e.g. BT474, HCC-38 were not sensitive to olaparib.
  • Figure 1 shows plots of both PARP-1 gene and protein expression levels against cell line IC50 data.
  • the data in Figure 1 clearly show that higher levels of PARP cannot distinguish between those cell lines that are responsive to olaparib and those that are not.
  • these data do demonstrate that there are hardly any cell lines with low levels of PARP-1 expression that are sensitive to olaparib (see lower left quadrant), indicating that low levels of PARP-1 may be a useful biomarker to exclude those cancer cells unlikely to respond to PARP inhibition.
  • BRCA deficiencies are notably associated with breast and ovarian cancers but not all cancers, raising the possibility that different HR deficiencies may be more common in some tumour types than others. Consistent with this idea are the observations that up to 50% of head and neck cancers are associated with chromosome 1 1 q deletions that remove the ATM gene (Parikh et al. Genes Chromosomes & Cancer 46:761-775, 2007) and 30% of non-small cell lung cancers that are associated with MDC1 deficiencies (Bartkova et al. Oncogene 26:7414-7422, 2007).
  • Table 5 shows PARP and HR biomarker correlation with breast cancer cell line response to olaparib. Quantification of mRNA for HR genes (ATM, ATR, BRCA1 , BRCA2, CHEK2, MRE1 1A, MDC1 ) and PARP-1 were determined by Taqman RT- PCR and relative expression levels (to mean of breast cell panel) calculated using 2- ⁇ me thod.
  • Relative HR gene expression levels are shown as less that 50% (- 2; black), between 50% and 67% (-0.5), between 67% and 150% (0), between 150% and 200% (0.5) and greater than 200% (2). HR gene expression was classified as low if relative mRNA levels were less than 50% (-2). Relative PARP- 1 gene expression is shown as either low (less than 50%; grey) or high (greater than 200%).
  • Table 6 shows PARP and HR biomarker correlation with colorectal cancer cell line response to olaparib.
  • PARP inhibitor (olaparib) IC50 was determined by 2D- colony formation assays.
  • MSI Microsatelite instability
  • MRE1 1 A gene mutation data were obtained from literature or online public databases.
  • HR gene expression was classified as low (black boxes) if relative mRNA levels were less than 50%.
  • ABCB1 P-gp drug transporter gene expression was classified as low if relative mRNA expression levels were up to 100%, moderate if relative expression between 100% and 200% or high if greater than 200% (grey).
  • Table 7 shows PARP and HR biomarker correlation with gastric cancer cell line response to olaparib.
  • PARP inhibitor (olaparib) IC50 was deternnined by 2D- colony formation assays. The black boxes indicate cell lines that demonstrated sensitivity to olaparib with IC50 values less than 1 .0 ⁇ . The grey boxes represent cell lines with olaparib sensitivity between 1 .0 and 1 .2 ⁇ .
  • ATM gene mutation data were obtained from literature or online public databases. Cell lines with DNA mutations are shown in grey. ATM and PARP-1 protein expression was
  • Protein expression analysis was performed using the methods outlined above in Example 1 using antibodies against ATM, ATR, MDC1 , MRE1 1 A and PARP-1 .
  • a striking correlation was observed between the most sensitive gastric cancer cell lines and ATM expression levels (Table 7). Expression levels of ATM were termed low when less than 50% expression was observed relative to the mean ATM expression of the gastric cell line panel.
  • Immunohistochemistry using the following method.
  • IHC staining for ATM was performed using 4 ⁇ formalin fixed paraffin wax embedded (FFPE) sections of human tissue (mounted on slides) and microscopic interpretation. Slides were heated at 60°C for 30 min then rehydrated by sequential immersion in Xylene (Standard laboratory grade; 2 changes, 10 min each), alcohol (Industrial methylated, iso-propyl alcohol; 2 changes, 5 min each), 70% v/v alcohol in pure water (5 min) and in running tap water for 5 min.
  • Target antigen retrieval was performed using 1 X target retrieval solution pH 9 (DAKO S2367) in a boiling domestic pressure cooker for 5 minutes.
  • ATM staining was run using a Labvision automated IHC autostainer using the following incubation programme: Rinse slides in wash buffer (DAKO S3306), Peroxidase blocking solution (DAKO S2001 ) 5 min, wash slides in wash buffer twice, Protein blocking solution (DAKO X0909) 5min, Blow off, primary ATM antibody (Epitomics 1549-1 ) in diluent (DAKO S0809) 60min, wash slides in wash buffer twice, HRP labelled rabbit/mouse polymer (DAKO K5007) 30min, wash slides in wash buffer twice, Diaminobenzidene solution (DAKO K3468) 10min and wash slides in water. For negative control sections the ATM antibody was replaced with negative control rabbit IgG (DAKO X0903).
  • lymphocyte staining was acceptable then the tumour cells were identified and the presence or absence of nuclear staining and its intensity scored as:
  • Table 8 shows ATM protein expression level analysis by immunohistochemistry (IHC) on tumour and adjacent normal tissue samples from Chinese gastric cancer patients.
  • RNAi expression vectors were created for each of the HR knockdown clones using the pSilencer 3.1 -H1 neo vector and RNAi knockdown system (Ambion/Applied biosystems).
  • the RNAi target sequences for each HR gene clone was inserted into the pSilencer 3.1 -H1 neo vector between the BamHI and Hind 111 restriction enzyme sites according to the manufacturers' recommended conditions.
  • Nonspecific (NS) negative control constructs acting as controls were also generated from standard non-coding sequences (Ambion/Applied Biosystems).
  • the CAL51 breast cell line was transfected with each HR gene RNAi expression vector or nonspecific control vector using the Lipofectamine-2000 lipid transfection reagent (Invitrogen) according to the manufacturers' recommendation instructions.
  • Transfected cells were plated out into multiple dishes and incubated in RPMI1640 + 10% foetal bovine serum (FBS) media containing 300 g/ml Geneticin
  • Proteomic identification of differentially expressed proteins for each HRD knockdown cell line compared to HR-proficient control cells were undertaken using two-dimensional difference gel electrophoresis (2D-DIGE) method (Gharbi et al 2002).
  • Proteomic profiles for each HRD knockdown cell lines were compared with their wild type (CAL51 WT) or non-specific control (CAL51 NS control) cells.
  • For each cell line either nuclear protein extraction or phospho-protein enrichment was performed to reduce protein complexity and aid data analysis. Standard nuclear protein enrichment method was used involving the gentle lysis of the cells by repeated freeze/thawing in a Hypotonic buffer. A high salt buffer was then added and the samples underwent centrifugation to pellet the nuclear fraction. The supernatant containing the cytoplasmic fraction was removed and the nuclear pellet resuspended in the proteomics lysis buffer (Gharbi et al., Mol. Cell.
  • the two-dimensional difference gel electrophoresis (2D-DIGE) method used was peformed essentially as previously described (Gharbi et al., Mol. Cell. Proteomics. 1 : 91-98, 2002). 200pmol of CyDye fluor were used to label 50pg of protein, samples were IEF focussed on 24cm pH4-7 IEF strips using an IPGphor II with an IPGphor manifold (GE healthcare, Little Chalfont, Bucks) at 20°C, ⁇ /strip.
  • Focussing conditions were 300V for3hrs, then increased in a linear gradient to 1 000V over the following 6 hours, then increased to 8000V again in a l inear gradient over 3 hours and finally continued at 8000V for a further 4 hours and 40 minutes. Total volt hours were approximately 55000 hours.
  • IEF focussed strips were run in the 2 nd dimension on 26cm X 21 cm format 10-20% gradient gels. The gels were run overnight on an Ettan Dalt II system (GE healthcare, Little Chalfont, Bucks). Running conditions were 5W/gel for the first 15-60 minutes, then 1 - 1 .5W/gel overnight at 25°C until the dye front ran off the bottom of the gel.
  • Protein IDs for each protein spot of interest was determined as follows. Preparative 2D gels loaded with 500- 1 000 g protein/gel were run and subsequently fixed and stained with an appropriate fluorescent stain (Sypro Ruby or Deep Purple Total Protein Stain [GE healthcare, Little Chalfont, Bucks]). These preparative gels were then scanned and spots matched to those previously identified as those containing proteins of interest. These were then selected for processing and identification by mass spectrometry using peptide mass fingerprinting and protein sequencing.
  • Results from these analyses were cross-compared with those from a gene expression analysis of the cell lines along with pertinent data from other sources.
  • journal publications were identified disclosing genelists representing mRNA expression changes following dynamic activation or inhibition of core BER (PARP-1 ) or HR (BRCA1 , BRCA2, ATM, ATR, MRE1 1 A, CHEK2 or MDC1 ) genes, listed here by PubMed ID:
  • Table 11 shows the expanded list of 498 HR genes identified through proteomic and genomic analysis of isogenic cancer cell lines with HR deficiencies.
  • DEGs Differentially expressed genes between Core HR knockdown and isogenic wild-type cell lines as discovered through 2D-DIGE proteomics and Affymet gene expression array analysis.
  • GABA protein homolog 1 diazepam binding inhibitor
  • DCI isomerase (3,2 trans-enoyl-Coenzyme 1632
  • polypeptide 3 X-linked 1 dihydrolipoamide S-
  • DSTN destrin actin depolymerizing factor 11034 1 dynein, cytoplasmic 1, intermediate
  • subunit 2 beta 38kDa 1 eukaryotic translation initiation factor
  • TSFM (includes Ts translation elongation factor
  • twinfilin actin-binding protein
  • U2AF2 (includes U2 small nuclear RNA auxiliary
  • ADM adrenomedullin 133 1 anterior gradient homolog 3 (Xenopus
  • GPR177 G protein-coupled receptor 177 79971 1
  • GPR137C G protein-coupled receptor 137C 283554 1 phosphodiesterase 3A, cGMP-
  • subunit beta type, 10 1
  • RBP1 retinol binding protein 1 cellular 5947 1
  • Rho-related BTB domain containing 1 9886 1 roundabout, axon guidance receptor

Abstract

The present invention relates generally to methods for treating cancer and to methods of predicting the responsiveness of a cancer cell to therapeutic treatment. In particular, the invention provides the identities of genes (biomarkers) that may be used to identify populations or individuals of cancer sufferers that are likely to respond favourably to treatment with a Poly (ADP - Ribose) polymerase (PARP) inhibitor. In a preferred embodiment, the expression levels of at least one base excision repair biomarker from Table 1 (including at least PARP-1), at least one homologous recombination biomarker from Table 2 and at least one proliferation biomarker from Table 3 are measured.

Description

DIAGNOSTIC TEST FOR PREDICTING RESPONSIVENESS TO TREATMENT
WITH A POLY(ADP-RIBOSE) POLYMERASE (PARP) INHIBITOR- FIELD OF THE INVENTION
The invention relates generally to methods for treating cancer and to methods of predicting the responsiveness of a cancer cell to therapeutic treatment. In particular, the invention provides the identities of biomarkers (genes) that may be used to identify populations or individuals of cancer sufferers that are likely to respond favourably to treatment with PARP inhibitors, such as olaparib (4-[3-(4- cyclopropanecarbonyl-piperazine-1 -carbonyl)-4-fluoro-benzyl]-2H-phthalazin-1 - one). This invention also relates to the use of particular biomarkers to assess or determine the suitability of certain cells, in particular cancer cells, to treatment with a Poly(ADP-Ribose) polymerase (PARP) inhibitor. The biomarker expression profiles, whether embodied in nucleic acid expression, protein expression, or other expression formats can be used as part of a personalised healthcare approach to cancer treatments.
BACKGROUND OF THE INVENTION
Mammalian cells which are deficient in homologous recombination (HR) dependent DNA repair, in particular cells which are BRCA1 or BRCA2 deficient, have been shown to be extremely sensitive to the inhibition of Poly(ADP-Ribose) polymerase (PARP), which is a component of the Base Excision Repair (BER) pathway that repairs single strand DNA damage. (Farmer H et al. Nature 2005; 434:917-21 , McCabe et al Cancer Biology & Therapy 2005 4:9, 934-936, Bryant et al, Nature 2005; 434: 913-917).
Recent data suggest that defects in other components of the HR pathway e.g. ATR, ATM, NBN, RAD51 , RAD54, DSS1 , CHEK2, FANCD2, FANCA, FANCC, also leads to sensitivity to PARP inhibition (McCabe et al, Cancer Res. (2006), and WO05/053662).
WO2005/012524 (The University of Sheffield) teach that cells deficient in homologous recombination (HR) are hypersensitive to PARP inhibitors as compared to wild type cells, and thus that PARP inhibitors are useful in the treatment of cancer cells defective in the expression of a gene involved in HR. Specific HR genes identified therein include XRCC1 , ADPRT (PARP-1 ), ADPRTL2 (PARP-2), CTPS, RPA, RPA1 , RPA2, RPA3, XPD, ERCC1 , XPF, MMSI9, RAD51 , RAD51 B, RAD51 C, RAD51 D, DMC1 , XRCC2, XRCC3, BRCA1 , BRCA2, RAD52, RAD54, RAD50, MRE 1 1 , NBS 1 , WRN, BLM, Ku70, Ku80, ATM, ATR, CHEK1 , CHEK2, FANCA, FANCB, FANCC, FANCD1 , FANCD2, FANCE, FANCF, FANCG, RAD1 , RAD9, FEN-1 , Mus81 , Emel, DSS1 and BARD.
Similarly, WO 2005053662 (Institute of Cancer Research and KuDOS
Pharmaceuticals Ltd.) relates to the recognition that inhibition of the base excision repair pathway is selectively lethal in cells which are deficient in HR dependent DNA DSB repair and thus that PARP inhibitors are useful in treating cancers which are deficient in HR dependent DNA DSB repair. The components of the HR dependent DNA DSB repair pathway listed include ATM (NM_000051 ), RAD51 (NM_002875), RAD51 L1 (NM_002877), RAD51 C (NM_002876), RAD51 L3
(NM_002878), DMC1 (NM_007068), XRCC2 (NM_005431 ), XRCC3
(NM_005432), RAD52 (NM_002879), RAD54L (NM_003579), RAD54B
(NM_012415), BRCA1 (NM_007295), BRCA2 (NM_000059), RAD50
(NM_005732), MRE1 1 A (NM_005590) and NBN (NM_002485), as well as regulatory factors such as EMSY.
WO 2008/147418, US2007/0292883 and US2008/0262062 (BiPAR Sciences Inc.) relates to methods of treating a PARP mediated disease comprising measuring the level of PARP in a sample from a patient and if the level of PARP is up- regulated treating the patient with a PARP modulator, e.g. PARP inhibitor.
In order to identify predictive biomarkers of olaparib response, and to provide further insights into mechanisms of PARP inhibitor sensitivity, a study has been undertaken using a panel of cancer cell lines to correlate response with molecular markers that have the potential to be used for patient selection to identify those tumors most likely to respond to olaparib or any other PARP inhibitor. SUMMARY OF THE INVENTION
The present invention relates to the identification and use of biomarker expression patterns (or profiles or signatures) which are correlated with cancer cells that are responsive to PARP inhibitor treatment, and which can therefore serve as a diagnostic personalised healthcare test to select patients that will likely respond favourably to PARP inhibitor therapy and deselect those that are unlikely to respond to PARP inhibitor therapy. The patterns may thus be used in diagnostic or prognostic methods or assays in the clinic to determine the appropriate treatment following identification of cancer in a patient.
The present invention provides methods of treating cancer in a subject/patient and methods of selecting cancer patients for such treatment. In one embodiment, the method of selection involves determining the expression level of PARP-1 in a cancer cell containing sample from the patient and if the PARP-1 expression level is not low, identifying or selecting the patient for treatment with a PARP inhibitor. In another embodiment, the method of treating cancer includes determining the expression level of PARP-1 in a cancer cell containing sample from the subject and if the PARP-1 expression level is not low, administering to the subject an effective amount of a PARP inhibitor.
The present invention provides methods of treating cancer in a subject/patient and methods of selecting cancer patients for such treatment. In one embodiment, the method of selection involves determining the expression level of MUTYH in a cancer cell containing sample from the patient and if the MUTYH expression level is not low, identifying or selecting the patient for treatment with a PARP inhibitor. In another embodiment, the method of treating cancer includes determining the expression level of MUTYH in a cancer cell containing sample from the subject and if the MUTYH expression level is not low, administering to the subject an effective amount of a PARP inhibitor.
In another aspect, in addition to determining the expression level of PARP-1 and/or MUTYH in the subject or patient's sample, the expression level of one or more genes involved in homologous recombination repair as listed in Table 2 is also measured; and selecting the patient for treatment with a PARP inhibitor if the expression profile of the biomarkers identifies the patient as being a likely responder to treatment with the PARP inhibitor. In one embodiment a patient whose cancer cells do not express low levels of PARP-1 or MUTYH but do express low levels of any of the homologous recombination repair genes selected from the group consisting of: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1 A is selected for treatment and/or treated with the PARP inhibitor compound.
In another aspect, the invention provides a method for selecting a cancer patient for treatment with a PARP inhibitor comprising measuring the expression level of at least one base excision repair biomarker as listed in Table 1 , at least one homologous recombination biomarker as listed in Table 2 and at least one proliferation biomarker as listed in Table 3, in a cancer cell containing sample obtained from the patient and selecting the patient for treatment with a PARP inhibitor if the expression profile of the at least three biomarkers identifies the patient as being a likely responder to treatment with the PARP inhibitor. In a particular embodiment the biomarker(s) from Table 1 are selected from PARP-1 , MUTYH, POLD1 and POLE3. In another embodiment the homologous
recombination biomarker from Table 2 is selected from: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1 A. In another embodiment the homologous recombination biomarker from Table 2 is selected from: MCM2, XRCC3, BRCA1 , MDC1 , ATM, ATR, NBN, RAD51 and MRE1 1 A. In another embodiment the proliferation biomarker from Table 3 is selected from AURKA, SMARCD3, ZIC1 , SSX2IP and BOC.
In another aspect there is provided a method of treating cancer comprising measuring the expression level of at least one base excision repair biomarker from Table 1 , at least one homologous recombination biomarker from Table 2 and at least one proliferation biomarker from Table 3, in a cancer cell containing sample obtained from the patient and if the expression profile of the biomarkers identifies the patient as being a likely responder to treatment with the PARP inhibitor, administering to said patient an effective amount of a PARP inhibitor. In a particular embodiment the biomarker(s) from Table 1 is selected from PARP-1 and MUTYH. In another embodiment the homologous recombination biomarker from Table 2 is selected from: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and
MRE1 1 A. In another embodiment the homologous recombination biomarker from Table 2 is selected from: MCM2, XRCC3, BRCA1 , MDC1 , ATM, ATR, NBN, RAD51 and MRE1 1A. In another embodiment the proliferation biomarker from Table 3 is selected from AURKA, SMARCD3, ZIC1 , SSX2IP, BOC, POLH, TP53BP2, SCMH1 , SMARCA5, MRAS, IP6K2, GTF2H4, MBD1 , RASA3, ZMYM4, PHF13, ARNT, KDM4A, PCBP4, TLR4, NUDT1 , PMS1 and ZMYM6.
A suitable PARP inhibitor compound that the methods of the invention can be applied to is olaparib.
BRIEF DESCRIPTION OF THE FIGURES.
Figure 1 shows PARP-1 gene and protein expression levels for each of the cell lines in the KU95 panel and the correlation with olaparib response. (A) Scatter plots comparing PARP-1 mRNA expression (normalised to the average of 3 housekeeping genes - PPIA, PGK1 and TBP) on the x-axis and olaparib IC50 on the y-axis. The solid line represents a simple straight line fit between all data points. The hatched lines are cut-off levels for mean normalised gene expression (0; x-axis) or olaparib sensitivity (0; less than 1 μΜ; y-axis). (B) Scatter plots comparing PARP-1 protein expression (normalised to housekeeping protein β- actin) on the x-axis and olaparib IC50 on the y-axis. The solid line represents a simple straight line fit between all data points. The hatched lines are cut-off levels for mean normalised protein expression (0; x-axis) or olaparib sensitivity (0; less than 1 μΜ; y-axis).
Figure 2 shows BRCA1 gene expression for each of the cell lines in the KU95 panel and the correlation with olaparib response. Scatter plots comparing BRCA1 mRNA expression (normalised to the average of 3 housekeeping genes) on the x- axis and olaparib IC50 on the y-axis. The solid line represents a simple straight line fit between all data points. Figure 3 shows the ROC curve demonstrating the increased predictive power of using PARP-1 and ATM over and above either biomarker alone
Figure 4 shows the identification of two main clusters within the 426 Affymetrix genes: the lower (smaller) cluster is a DNA repair cluster containing primarily genes associated with BER and HR, the other genes associated with cell proliferation function.
Figure 5 shows the three main functional groups of biomarkers for predicting olaparib sensitivity and how they were identified.
Figure 6 shows a ROC curve that illustrates the improved predictive power of the combination of PARP-1 (BER), BRCA1 (HR) and AURKA (proliferation)
biomarkers to predict olaparib response.
Figure 7 shows a ROC curve that illustrates the improved predictive power of the combination of MUTYH (BER), BRCA1 (HR) and SMARCD3 (proliferation) biomarkers to predict olaparib response.
Figure 8 shows a ROC curve that illustrate the improved predictive power of the combination of MUTYH (BER), ATM (HR) and ZIC1 (proliferation) biomarkers to predict olaparib response.
Figure 9 shows a ROC curve that illustrates the improved predictive power of the combination of POLD1 , (BER), ATM (HR) and SSX2IP (proliferation) biomarkers to predict olaparib response.
Figure 10 shows a ROC curve that illustrates the improved predictive power of the combination of POLE3 (BER), BRCA1 (HR) and BOC1 (proliferation) biomarkers to predict olaparib response.
DETAILED DESCRIPTION OF THE INVENTION.
The term "biomarker" in the context of the present invention encompasses, without limitation, a gene (e.g. nucleic acid) including its encoded protein or polypeptide as disclosed in any of Tables 1 , 2 or 3, as well as polymorphisms thereof. Biomarkers can also include mutated proteins or mutated nucleic acids.
A "gene" is a polynucleotide that encodes a discrete product, whether RNA or proteinaceous in nature. It is appreciated that more than one polynucleotide may be capable of encoding a discrete product. The term includes alleles and polymorphisms of a gene that encodes the same product, or a functionally associated (including gain, loss, or modulation of function) analog thereof, based upon chromosomal location and ability to recombine during normal mitosis.
A biomarker (gene) expression "pattern" or "profile" or "signature" refers to the relative expression of one or more biomarkers (genes) between different cells, which expression is correlated with being able to distinguish between cancer cells that will respond favourably or not to treatment with a PARP inhibitor.
A "sequence" or "gene sequence" as used herein is a nucleic acid molecule or polynucleotide composed of a discrete order of nucleotide bases. The term includes the ordering of bases that encodes a discrete product (i.e. "coding region"), whether RNA or proteinaceous in nature, as well as the ordered bases that precede or follow a "coding region". Non-limiting examples of the latter include 5' and 3' untranslated regions of a gene. It is appreciated that more than one polynucleotide may be capable of encoding a discrete product. It is also
appreciated that alleles and polymorphisms of the disclosed sequences may exist and may be used in the practice of the invention to identify the expression level(s) of the disclosed sequences or the allele or polymorphism. Identification of an allele or polymorphism depends in part upon chromosomal location and ability to recombine during mitosis.
The terms "correlate" or "correlation" or equivalents thereof, refer to an association between the expression of one or more genes and the response to treatment with olaparib. Note that in this setting the terms "correlate" or "correlation" are used more broadly than simply a Pearson or Spearman correlation to refer to an association or relationship which can take one of many forms, as demonstrated in the examples. Correlations may be positive such that high levels of expression are associated with large or positive responses, and low levels of expression are associated with small or negative responses, or negatively correlated, such that high levels of expression are associated with small or negative responses, and low levels of expression are associated with large or positive responses.
Expression data may be generated by one or more of a range of gene or protein expression measuring techniques, for example but not limited to, RT-PCR, Affymetrix whole genome microarray profiling for gene expression or IHC or Western Blotting for protein expression. Normalisation is typically applied to the raw data generated from these techniques to remove any artefactual inter-subject differences arising from sample processing or sample quality. Data from RT-PCR is typically normalised by subtracting the average expression of one or more normalisation genes from the observed expression levels of the gene of interest for each sample. Data from Affymetrix whole genome microarrays is typically normalised by the RMA algorithm or one of a number of alternative algorithms including but not limited to MAS5, PLIER, GC-RMA.
For example, increases in gene expression can be indicated by ratios of or about 1 .1 , of or about 1 .2, of or about 1 .3, of or about 1 .4, of or about 1 .5, of or about 1 .6, of or about 1 .7, of or about 1 .8, of or about 1 .9, of or about 2, of or about 2.5, of or about 3, of or about 3.5, of or about 4, of or about 4.5, of or about 5, of or about 5.5, of or about 6, of or about 6.5, of or about 7, of or about 7.5, of or about 8, of or about 8.5, of or about 9, of or about 9.5, of or about 10, of or about 15, of or about 20, of or about 30, of or about 40, of or about 50, of or about 60, of or about 70, of or about 80, of or about 90, of or about 100, of or about 150, of or about 200, of or about 300, of or about 400, of or about 500, of or about 600, of or about 700, of or about 800, of or about 900, or of or about 1000. A ratio of 2 is a 100% (or a two-fold) increase in expression. Decreases in gene expression can be indicated by ratios of or about 0.9, of or about 0.8, of or about 0.7, of or about 0.6, of or about 0.5, of or about 0.4, of or about 0.3, of or about 0.2, of or about 0.1 , of or about 0.05, of or about 0.01 , of or about 0.005, of or about 0.001 , of or about 0.0005, of or about 0.0001 , of or about 0.00005, of or about 0.00001 , of or about 0.000005, or of or about 0.000001 .
A number of different statistical algorithms can be applied in order to generate a mathematical model combining together the expression levels of two or more genes or proteins with a cut-off to classify subjects as predicted olaparib responders. These include, but are not limited to logistic regression, multiple regression, Cox proportional hazard models, random forests, recursive
partitioning, random survival forests, partial least squares, partial least squares discriminant analysis, Support Vector Machines, neural networks.
The term "amplify" is used in the broad sense to mean creating an amplification product, which for example, can be made enzymatically with DNA or RNA polymerases. "Amplification," as used herein, generally refers to the process of producing multiple copies of a desired sequence, particularly those of a sample. "Multiple copies" mean at least 2 copies. A "copy" does not necessarily mean perfect sequence complementarity or identity to the template sequence.
By "homologous" is meant that a nucleic acid molecule shares a substantial amount of sequence identity with another nucleic acid molecule. Substantial amount means at least 90%, such as at least 95%, at least 98% and more usually at least 99%, and sequence identity is determined using the BLAST algorithm, as described in Altschul et al. (1990), J. Mol. Biol. 215:403-410 (using the published default setting, i.e. parameters w=4, t=17). Methods for amplifying mRNA are generally known in the art, and include reverse transcription PCR (RT-PCR) and those described in U.S. patent application Ser. No. 10/062,857 (filed on Oct. 25, 2001 ), as well as U.S. Provisional Patent Applications 60/298,847 (filed Jun. 15, 2001 ) and 60/257,801 (filed Dec. 22, 2000), all of which are hereby incorporated by reference in their entireties as if fully set forth. Another method that may be used is quantitative PCR (or Q-PCR). Alternatively, RNA may be directly labelled as the corresponding cDNA by methods known in the art. A "microarray" is a linear or two-dimensional array of preferably discrete regions, each having a defined area, formed on the surface of a solid support such as, but not limited to, glass, plastic, or synthetic membrane. The density of the discrete regions on a microarray is determined by the total numbers of immobilized polynucleotides to be detected on the surface of a single solid phase support, for example at least about 50/cm2, at least about 100/cm2, at least about 500/cm2, but preferably below about 1 ,000/cm2. In certain embodiments, the arrays contain less than about 500, about 1000, about 1500, about 2000, about 2500, or about 3000 immobilized polynucleotides in total. As used herein, a DNA microarray is an array of oligonucleotides or polynucleotides placed on a chip or other surfaces used to hybridize to amplified or cloned polynucleotides from a sample. Since the position of each particular group of primers in the array is known, the identities of a sample polynucleotides can be determined based on their binding to a particular position in the microarray.
The term "label" refers to a composition capable of producing a detectable signal indicative of the presence of the labelled molecule. Suitable labels include radioisotopes, nucleotide chromophores, enzymes, substrates, fluorescent molecules, chemiluminescent moieties, magnetic particles, bioluminescent moieties, and the like. As such, a label is any composition detectable by
spectroscopic, photochemical, biochemical, immunochemical, electrical, optical or chemical means.
The term "support" refers to conventional supports such as beads, particles, dipsticks, fibres, filters, membranes and silane or silicate supports such as glass slides.
"Expression" and "gene expression" include transcription and/or translation of nucleic acid material.
Conditions that "allow" an event to occur or conditions that are "suitable" for an event to occur, such as hybridization, strand extension, and the like, or "suitable" conditions are conditions that do not prevent such events from occurring. Thus, these conditions permit, enhance, facilitate, and/or are conducive to the event. Such conditions, known in the art and described herein, depend upon, for example, the nature of the nucleotide sequence, temperature, and buffer conditions. These conditions also depend on what event is desired, such as hybridization, cleavage, strand extension or transcription.
"Detection" includes any means of detecting, including direct and indirect detection of gene expression and changes therein. For example, "detectably less" products may be observed directly or indirectly, and the term indicates any reduction (including the absence of detectable signal). Similarly, "detectably more" product means any increase, whether observed directly or indirectly.
The term "treatment", as used herein in the context of treating a condition, pertains generally to treatment and therapy, whether of a human or an animal (e.g. in veterinary applications), in which some desired therapeutic effect is achieved, for example, the inhibition of the progress of the condition, and includes a reduction in the rate of progress, a halt in the rate of progress, amelioration of the condition, and cure of the condition. Treatment as a prophylactic measure (i.e. prophylaxis) is also included.
By "efficacious" it is meant that the treatment leads to stabilization in tumour size, a decrease in tumour size, or a decrease in metastatic potential of cancer in a subject.
The term "BER genes" refers to genes associated with Base Excision Repair, a form of DNA repair involved in dealing with DNA single-strand breaks that may occur endogenously or may be induced through various cancer therapies such as ionizing radiation or treatment with DNA damaging chemotherapies. There are a number of genes associated with BER including PARP-1 . Those genes associated with BER for the purpose of this application are listed in Table 1 . Table 1 .
Biomarker Entrez
Direction
gene Entrez Gene Name Gene p-value ality
Symbol ID
PARP-1 poly (ADP-ribose) polymerase 1 142 1 0.0000079
MBD4 methyl-CpG binding domain protein 4 8930 -1 0.0006197
TMSB15A thymosin beta 15a 1 1013 1 0.0034041
OGG1 8-oxoguanine DNA glycosylase 4968 -1 0.0034407 polymerase (DNA directed), delta 1 ,
POLD1 catalytic subunit 125kDa 5424 _! 0.00441 15 polymerase (DNA directed), epsilon 3
POLE3 (p17 subunit) 54107 _! 0.0044624 minichromosome maintenance
MCM5 complex component 5 4174 -1 0.0055936 excision repair cross-complementing
rodent repair deficiency,
complementation group 1 (includes
ERCC1 overlapping antisense sequence) 2067 0.0063634
MUTYH mutY homolog (E. coli) 4595 1 0.0068137
PRIM1 primase, DNA, polypeptide 1 (49kDa) 5557 -1 0.0073004 polymerase (DNA directed), epsilon 2
POLE2 (p59 subunit) 5427 _! 0.0140415 non-SMC condensin I complex,
NCAPG subunit G 64151 0.0182952
PTTG1 pituitary tumor-transforming 1 9232 -1 0.0210048
FEN1 flap structure-specific endonuclease 1 2237 -1 0.0213244 nuclear factor of kappa light
polypeptide gene enhancer in B-cells
NFKBIL1 inhibitor-like 1 4795 0.0252430
PPT2 palmitoyl-protein thioesterase 2 9374 1 0.0297983 guanine nucleotide binding protein¬
GNL3 like 3 (nucleolar) 26354 1 0.0315160 tankyrase, TRF1 -interacting ankyrin-
TNKS related ADP-ribose polymerase 8658 1 0.0359318
KDM5B lysine (K)-specific demethylase 5B 10765 1 0.0391910
MPG N-methylpurine-DNA glycosylase 4350 -1 0.0459623
PCNA proliferating cell nuclear antigen 51 1 1 0.0476059 v-myb myeloblastosis viral oncogene
MYBL2 homolog (avian)-like 2 4605 _! 0.0536009
PRC1 protein regulator of cytokinesis 1 9055 0.0604505
POLB polymerase (DNA directed), beta 5423 1 0.0639530 extra spindle pole bodies homolog 1
ESPL1 (S. cerevisiae) 9700 0.0649566
UNG uracil-DNA glycosylase 7374 0.0767188
PARG poly (ADP-ribose) glycohydrolase 8505
poly (ADP-ribose) polymerase family,
PARP3 member 3 10039 The term "HR genes" refers to genes associated with the Homologous
Recombination repair pathway, a form of DNA repair involved in dealing with DNA double strand breaks that may occur endogenously or may be induced through various cancer therapies such as ionizing radiation or treatment with DNA damaging chemotherapies. There are a number of genes associated with HR including BRCA1 , BRCA2, ATM, ATR, CHEK2, MDC1 and MRE1 1A. Those genes associated with HR for the purpose of this application are listed in Table 2.
Table 2.
Entr
Biomarker
ez Direction
gene Entrez Gene Name p-value
Gen ality
Symbol
e ID
PAPSS1 3'-phosphoadenosine 5'-phosphosulfate 9061 0.0001719
1
synthase 1
PCYT1A phosphate cytidylyltransferase 1 , 5130 0.0002438 choline, alpha
NBN nibrin 4683 -1 0.0002917
NANS N-acetylneuraminic acid synthase 5418 0.0004443
7
TIMELESS timeless homolog (Drosophila) 8914 -1 0.0004697
TROAP trophinin associated protein (tastin) 1002 0.0005769
4
PHF15 PHD finger protein 15 2333 0.0006954
8
NP nucleoside phosphorylase 4860 -1 0.0009158
PDE4B phosphodiesterase 4B, cAMP-specific 5142 0.001 1225
1
(phosphodiesterase E4 dunce homolog,
Drosophila)
HIPK2 homeodomain interacting protein kinase 2899 0.001 1526
2 1
6
ARHGDIA Rho GDP dissociation inhibitor (GDI) 396 0.0012812 alpha
ISYNA1 inositol-3-phosphate synthase 1 5147 0.0013454
7 1
SUMF2 sulfatase modifying factor 2 2587 0.0016755
0 1
PBX1 pre-B-cell leukemia homeobox 1 5087 1 0.0017322
MAN2A1 mannosidase, alpha, class 2A, member 4124 0.0018873
1
GINS2 GINS complex subunit 2 (Psf2 homolog) 5165 0.002101 1
9
RAB7A RAB7A, member RAS oncogene family 7879 -1 0.0021792
CALM3 calmodulin 3 (phosphorylase kinase, 808 0.0027420 delta)
ACTL6A actin-like 6A 86 -1 0.0031460
COMMD3 COMM domain containing 3 2341 1 0.0031731
Figure imgf000015_0001
Figure imgf000016_0001
(double-strand-break rejoining)
The term "proliferation genes" refers to those genes involved in the control of cell cycle and proliferation and for the purpose of this application are listed in Table 3. Table 3.
Biomarker Entrez
Direction
gene Entrez Gene Name Gene p-value ality
Symbol ID
KDM4A lysine (K)-specific demethylase 4A 9682 1 0.0000049
GPBP1 L1 GC-rich promoter binding protein 1 -like 1 60313 1 0.0000265
SSX2IP synovial sarcoma, X breakpoint 2 1 1717 0.0000368 interacting protein 1
8
USP34 ubiquitin specific peptidase 34 9736 1 0.0000388
ZMYM6 zinc finger, MYM-type 6 9204 1 0.0000388
SMARCA5 SWI/SNF related, matrix associated, actin 8467 0.0000527 dependent regulator of chromatin, 1
subfamily a, member 5
ZNF287 zinc finger protein 287 57336 1 0.0000636
BSDC1 BSD domain containing 1 55108 1 0.0000807
MBD1 methyl-CpG binding domain protein 1 4152 1 0.0000907
ALDH1 L2 aldehyde dehydrogenase 1 family, 16042 0.0001052 member L2 1
8
AURKA aurora kinase A 6790 -1 0.0001 123
ERI3 exoribonuclease 3 79033 1 0.0001286
YWHAB tyrosine 3-monooxygenase/tryptophan 5- 7529 0.0001430 monooxygenase activation protein, beta
polypeptide
KLHDC10 kelch domain containing 10 23008 1 0.0001450
MAPK9 mitogen-activated protein kinase 9 5601 -1 0.0001582
TMEM97 transmembrane protein 97 27346 -1 0.0001935
ZZZ3 zinc finger, ZZ-type containing 3 26009 1 0.0001935
EIF2C3 eukaryotic translation initiation factor 2C, 3 19266 0.0002213
1
9
SMARCD3 SWI/SNF related, matrix associated, actin 6604 0.0002326 dependent regulator of chromatin, 1
subfamily d, member 3
TLR4 toll-like receptor 4 7099 -1 0.0002370
B4GALNT4 beta-1 ,4-N-acetyl-galactosaminyl 33870 0.0002431
1
transferase 4 7
DOCK3 dedicator of cytokinesis 3 1795 1 0.0002531
TRIT1 tRNA isopentenyltransferase 1 54802 1 0.0002632
ZMYM4 zinc finger, MYM-type 4 9202 1 0.0002668
BOC Boc homolog (mouse) 91653 1 0.0002919
POLH polymerase (DNA directed), eta 5429 1 0.0003007
ZNF682 zinc finger protein 682 91 120 1 0.0003007
AKIRIN1 akirin 1 79647 1 0.0003038
C1 orf50 chromosome 1 open reading frame 50 79078 1 0.0003087
TEX15 testis expressed 15 56154 1 0.0003356
PEAR1 platelet endothelial aggregation receptor 1 37503 0.0003471
3
BNIP3 BCL2/adenovirus E1 B 19kDa interacting 664 0.0003702 protein 3 1
IP6K2 inositol hexakisphosphate kinase 2 51447 1 0.0003737
ZNF14 zinc finger protein 14 7561 1 0.0003856
ZNF382 zinc finger protein 382 8491 1 1 0.0004070 CXXC1 CXXC finger 1 (PHD domain) 30827 1 0.0004263
INPP5B inositol polyphosphate-5-phosphatase, 3633 0.0004322
1
75kDa
TPD52 tumor protein D52 7163 -1 0.0004481
TST thiosulfate sulfurtransferase (rhodanese) 7263 -1 0.0004949
SUV39H1 suppressor of variegation 3-9 homolog 1 6839 0.0004964
(Drosophila)
SRA1 steroid receptor RNA activator 1 1001 1 -1 0.0005035
SEMA6A sema domain, transmembrane domain 57556 0.0005074
(TM), and cytoplasmic domain, 1
(semaphorin) 6A
NAP1 L3 nucleosome assembly protein 1 -like 3 4675 1 0.0005145
MRAS muscle RAS oncogene homolog 22808 1 0.0005388
TRIM14 tripartite motif-containing 14 9830 -1 0.0006131
SH3PXD2B SH3 and PX domains 2B 28559 0.0006292
1
0
ZIC1 Zic family member 1 (odd-paired homolog, 7545 0.0006409
Drosophila) 1
ENAH enabled homolog (Drosophila) 55740 1 0.0006700
COR02A coronin, actin binding protein, 2A 7464 -1 0.0007334
USP46 ubiquitin specific peptidase 46 64854 1 0.0007354
AIFM2 apoptosis-inducing factor, mitochondrion- 84883 0.0007537 associated, 2
TYSND1 trypsin domain containing 1 21974 0.0007540
3
GTF2H4 general transcription factor IIH, 2968 1 0.0007879 polypeptide 4, 52kDa
TBC1 D2 TBC1 domain family, member 2 55357 -1 0.0007978
CT45A3 cancer/testis antigen family 45, member 44151 0.0009231
1
A3 9
KRAS v-Ki-ras2 Kirsten rat sarcoma viral 3845 0.0009670
1
oncogene homolog
MKI67 antigen identified by monoclonal antibody 4288 0.0009783
Ki-67
G6PC3 glucose 6 phosphatase, catalytic, 3 92579 -1 0.0009880
SAMD1 sterile alpha motif domain containing 1 90378 1 0.0010875
SLC22A17 solute carrier family 22, member 17 51310 1 0.0012269
MBP myelin basic protein 4155 -1 0.001231 1
C1 orf52 chromosome 1 open reading frame 52 14842 0.0012561
3 1
CBS cystathionine-beta-synthase 875 1 0.0012761
RGNEF Rho-guanine nucleotide exchange factor 64283 -1 0.0013176
EIF2C1 eukaryotic translation initiation factor 2C, 1 26523 1 0.0013255
TET1 tet oncogene 1 80312 1 0.0013518
ASAP3 ArfGAP with SH3 domain, ankyrin repeat 55616 0.001361 1 and PH domain 3 1
ARNT aryl hydrocarbon receptor nuclear 405 0.0013961 translocator 1
PIAS2 protein inhibitor of activated STAT, 2 9063 1 0.0014305
NRD1 nardilysin (N-arginine dibasic convertase) 4898 1 0.0014471
RANBP9 RAN binding protein 9 10048 1 0.0014502 ZMYM3 zinc finger, MYM-type 3 9203 1 0.0014967
ZMYM2 zinc finger, MYM-type 2 7750 1 0.0015268
ABCA7 ATP-binding cassette, sub-family A 10347 0.001631 1
1
(ABC1 ), member 7
UFSP2 UFM1 -specific peptidase 2 55325 1 0.0016805
RND2 Rho family GTPase 2 8153 1 0.0017308
GAS1 growth arrest-specific 1 2619 1 0.0017959
SCMH1 sex comb on midleg homolog 1 22955 0.0017995
1
(Drosophila)
MIB2 mindbomb homolog 2 (Drosophila) 14267 0.0018255
8 1
ATP5G1 ATP synthase, H+ transporting, 516 0.0019210 mitochondrial F0 complex, subunit C1
(subunit 9)
AK2 adenylate kinase 2 204 1 0.0019865
PRR3 proline rich 3 80742 1 0.0021209
HDAC4 histone deacetylase 4 9759 1 0.0021480
SOS1 son of sevenless homolog 1 (Drosophila) 6654 1 0.0021836
TIA1 TIA1 cytotoxic granule-associated RNA 7072 0.0022886 binding protein 1
C1 orf149 chromosome 1 open reading frame 149 64769 1 0.0023102
FNBP1 L formin binding protein 1 -like 54874 1 0.0023162
RABGAP1 L RAB GTPase activating protein 1 -like 9910 1 0.0024693
ORMDL2 ORM1 -like 2 (S. cerevisiae) 29095 -1 0.0024889
PHF13 PHD finger protein 13 14847 0.0025026
1
9
SLC26A1 1 solute carrier family 26, member 1 1 28412 0.0027076
1
9
PCDHAC2 protocadherin alpha subfamily C, 2 56134 1 0.0027171
ZNF880 zinc finger protein 880 40071 0.0027329
3 1
NOTCH3 Notch homolog 3 (Drosophila) 4854 1 0.0028402
S100PBP S100P binding protein 64766 1 0.0029383
RPL17;C18 ribosomal protein L17 6139 0.0030109 orf32 1
RIMS3 regulating synaptic membrane exocytosis 9783 0.0031404
1
3
RLF rearranged L-myc fusion 6018 1 0.0031801
ANXA8L2 annexin A8-like 2 244 -1 0.0032033
EFHD2 EF-hand domain family, member D2 79180 -1 0.0033478
BEX4 brain expressed, X-linked 4 56271 1 0.0034080
AN01 anoctamin 1 , calcium activated chloride 55107 0.0034678 channel
TTC3 tetratricopeptide repeat domain 3 7267 1 0.0035632
PRKAR2B protein kinase, cAMP-dependent, 5577 0.0035693
1
regulatory, type II, beta
ZNF43 zinc finger protein 43 7594 1 0.0036203
C1 1 orf17 chromosome 1 1 open reading frame 17 56672 -1 0.0036640
ATXN3 ataxin 3 4287 1 0.0039021
PLAUR plasminogen activator, urokinase receptor 5329 -1 0.0039027
DDR2 discoidin domain receptor tyrosine kinase 4921 1 0.0039166 2
RAE1 RAE1 RNA export 1 homolog (S. pombe) 8480 -1 0.0039312
PBX2 pre-B-cell leukemia homeobox 2 5089 1 0.0039550
NUDT3 nudix (nucleoside diphosphate linked 1 1 165 0.0039702 moiety X)-type motif 3 1
C16orf5 chromosome 16 open reading frame 5 29965 1 0.0040091
ATAD2 ATPase family, AAA domain containing 2 29028 -1 0.0042200
SMC2 structural maintenance of chromosomes 2 10592 -1 0.0042868
ZNF74 zinc finger protein 74 7625 1 0.0043824
RFX5 regulatory factor X, 5 (influences HLA 5993 0.0043936 class II expression) 1
DZIP1 DAZ interacting protein 1 22873 1 0.0044360
C6orf64 chromosome 6 open reading frame 64 55776 1 0.0045024
IL1 R1 interleukin 1 receptor, type I 3554 1 0.0048077
CT45A2 cancer/testis antigen family 45, member 72891 0.0048404
A2 1 1
C19orf33 chromosome 19 open reading frame 33 64073 -1 0.0050299
GPC3 glypican 3 2719 1 0.0050968
ZNF607 zinc finger protein 607 84775 1 0.0051 109
FAM129B family with sequence similarity 129, 64855 0.0051927 member B
SERINC3 serine incorporator 3 10955 -1 0.0054281
PYCARD PYD and CARD domain containing 29108 0.0054489
PMS1 PMS1 postmeiotic segregation increased 5378 0.0055815
1
1 (S. cerevisiae)
CELSR1 cadherin, EGF LAG seven-pass G-type 9620 0.0059464 receptor 1 (flamingo homolog, Drosophila)
AIP aryl hydrocarbon receptor interacting 9049 0.0059993 protein 1
PCBP4 poly(rC) binding protein 4 57060 1 0.0060172
C4orf27 chromosome 4 open reading frame 27 54969 1 0.0060766
C5orf13 chromosome 5 open reading frame 13 9315 1 0.0060832
NDUFA5 NADH dehydrogenase (ubiquinone) 1 4698 0.0060914
1
alpha subcomplex, 5, 13kDa
C20orf43 chromosome 20 open reading frame 43 51507 -1 0.0060957
THBD thrombomodulin 7056 -1 0.0063237
SYNE2 spectrin repeat containing, nuclear 23224 0.0065957 envelope 2
GST01 glutathione S-transferase omega 1 9446 -1 0.0066979
GPR137C G protein-coupled receptor 137C 28355 0.0067014
4 1
PHF21A PHD finger protein 21A 51317 1 0.0068604
PODXL podocalyxin-like 5420 -1 0.0071927
SSH3 slingshot homolog 3 (Drosophila) 54961 0.0075951
ECT2 epithelial cell transforming sequence 2 1894 0.0076624 oncogene
RASA3 RAS p21 protein activator 3 22821 -1 0.0079433
JUP junction plakoglobin 3728 0.0080152
TP53BP2 tumor protein p53 binding protein, 2 7159 1 0.0101765
RELB v-rel reticuloendotheliosis viral oncogene 5971 0.0108766
1
homolog B CYFIP2 cytoplasmic FMR1 interacting protein 2 26999 0.01 1 1047
ETFB electron-transfer-flavoprotein, beta 2109 -1 0.0120792 polypeptide
CARD10 caspase recruitment domain family, 29775 -1 0.0139857 member 10
PPP1 R15A protein phosphatase 1 , regulatory 23645 -1 0.0151316
(inhibitor) subunit 15A
WDHD1 WD repeat and HMG-box DNA binding 1 1 169 -1 0.0161 1 12 protein 1
CCNB1 cyclin B1 891 0.0166370
SOX7 SRY (sex determining region Y)-box 7 83595 -1 0.0170736
CDC2 cell division cycle 2, G1 to S and G2 to M 983 0.0175563
CEP55 centrosomal protein 55kDa 55165 -1 0.0191 100
DIRAS3 DIRAS family, GTP-binding RAS-like 3 9077 1 0.0193385
PRKCA protein kinase C, alpha 5578 -1 0.0196635
SERPINE1 serpin peptidase inhibitor, clade E (nexin, 5054 -1 0.021 1086 plasminogen activator inhibitor type 1 ),
member 1
HNRNPA2B heterogeneous nuclear ribonucleoprotein 3181 0.0215084 1 A2/B1
PRKAB2 protein kinase, AMP-activated, beta 2 non- 5565 1 0.0228916 catalytic subunit
BCL2L1 BCL2-like 1 598 -1 0.0264679
MT2A metallothionein 2A 4502 -1 0.0266173
IFI16 interferon, gamma-inducible protein 16 3428 -1 0.0271243
GLIPR1 GLI pathogenesis-related 1 1 1010 -1 0.0289794
ZBTB7A zinc finger and BTB domain containing 7A 51341 -1 0.0305524
AXL AXL receptor tyrosine kinase 558 -1 0.0316230
NUDT1 nudix (nucleoside diphosphate linked 4521 -1 0.0353147 moiety X)-type motif 1
TPX2 TPX2, microtubule-associated, homolog 22974 -1 0.0358630
(Xenopus laevis)
VASH1 vasohibin 1 22846 1 0.0394555
NFKB2 nuclear factor of kappa light polypeptide 4791 1 0.0400759 gene enhancer in B-cells 2 (p49/p100)
ZWINT ZW10 interactor 1 1 130 -1 0.0402281
HAS2 hyaluronan synthase 2 3037 -1 0.0412488
BCL2A1 BCL2-related protein A1 597 -1 0.0495830
CASP1 caspase 1 , apoptosis-related cysteine 834 0.0578672 peptidase (interleukin 1 , beta, convertase)
CASP8 caspase 8, apoptosis-related cysteine 841 -1 0.0595356 peptidase
FGFR3 fibroblast growth factor receptor 3 2261 -1 0.0621 165
ITGB4 integrin, beta 4 3691 0.0694217
PSMB8 proteasome (prosome, macropain) 5696 -1 0.0714354 subunit, beta type, 8 (large multifunctional
peptidase 7)
CCND1 cyclin D1 595
CCNG1 cyclin G1 900
ERBB2 v-erb-b2 erythroblastic leukemia viral 2064
oncogene homolog 2, neuro/glioblastoma derived oncogene homolog (avian)
ESR1 estrogen receptor 1 2099
KRT18 keratin 18 3875
PGR progesterone receptor 5241
PTEN phosphatase and tensin homolog 5728
SFRS10 transformer 2 beta homolog 6434
VIM vimentin 7431
With respect to Tables 1 , 2 and 3, "Directionality" values of -1 represent a biomarker for which a high level of expression was found to be associated with resistance or a low level of expression to be associated with sensitivity (e.g.
BRCA1 ) in Example 4.
Values of +1 represent a biomarker for which a high level of expression was found to be associated with sensitivity or a low level of expression to be associated with resistance in Example 4. The biomarkers without a direction are those that did have a strong association in one or more of the analyses, but did not always have a constant direction of association across the different analyses that were performed. The p-value in these tables (also referred to as p.min) is the smallest of the 5 permutation p-values from the DEGNN, DEGTN, DESNG, DEGTG and DES analyses as described in Example 4.
Unless otherwise stated, database entries for sequences refer to the National Center for Biotechnology Information (NCBI) Nucleotide Entrez database. An 'Entrez Genlnfo Identifier' ("Entrez Gene ID") sequence identification number is a series of digits assigned consecutively to each sequence record processed by NCBI and is unique to a particular gene and associated DNA sequence
information, and is linked to protein variant sequences in the NCBI Protein Entrez database. As used in the context of the Tables herein as well as the present invention "Entrez Gene ID" refers to the Entrez Database accession number of a sequence of each gene, the sequences of which are hereby incorporated by reference in their entireties as they are available from
www.ncbi.nlm.nih.gov/sites/gquery, as accessed on the filing date of the present application. Gene names and symbols represent the recognisable descriptions of genes as annotated by the official human genome consortium available from:
www.hugo-international.org/ and www.genenames.org/, as accessed on the filing date of the present application. These unique identifiers may thus identify the sequences of the biomarkers used according to the present invention.
"KU95 panel" refers to the panel of 95 cancer cell lines as listed in Table 4 representing breast, ovarian, colorectal, lung, head & neck and pancreatic cancers, tested for their response to treatment with single agent olaparib.
"IC50" refers to the concentration of olaparib (in μΜ) that results in 50% of the number of cell colonies that grow compared to the untreated control.
Unless defined otherwise all technical and scientific terms used herein have the same meaning as commonly understood to one of ordinary skill in the art to which this invention belongs.
An individual having a cancer condition may comprise one or more cancer cells. Cancer cells in general are characterised by abnormal proliferation relative to normal cells and typically form clusters or tumours in an individual having a cancer condition. The cancer cells may possess a phenotype, which characterises the cancer condition. It is this phenotype that the present invention seeks to identify.
According to one aspect of the invention there is provided a method for selecting a cancer patient for treatment with a PARP inhibitor comprising determining the expression level of PARP-1 and/or MUTYH in a cancer cell containing sample from the patient and if the PARP-1 and/or MUTYH expression level is not low, identifying or selecting the patient for treatment with a PARP inhibitor. A suitable PARP inhibitor is olaparib.
In one embodiment, the expression levels of both PARP-1 and MUTYH are determined.
In another aspect, in addition to determining the expression level of PARP-1 and/or MUTYH in the cancer cell-containing sample, the expression level of one or more genes involved in homologous recombination repair as listed in Table 2 is also measured. The patient is then identified or selected for treatment with a PARP inhibitor if the expression profile of the biomarkers identifies the patient as being a likely responder to treatment with the PARP inhibitor. In one embodiment a patient whose cancer cells do not express low levels of PARP-1 or MUTYH but do express low levels of any of the homologous recombination repair genes selected from the group consisting of: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1 A is selected for treatment and/or treated with the PARP inhibitor compound.
In another aspect the invention provides a method for selecting a cancer patient for PARP inhibitor based therapy comprising: measuring the amount of PARP-1 and at least one other biomarker selected from: ATM, BRCA1 , BRCA2, MRE1 1 A, ATR, CHEK2 and MDC1 , in a tumour cell containing sample from said cancer patient, comparing these amounts to reference values; and, selecting the patient for treatment with PARP inhibitor based therapy if, compared to the reference values, the level of PARP-1 is not low and the level of the other biomarker is reduced in the tumour cell containing sample from said cancer patient.
In another aspect the invention provides a method for selecting a cancer patient for PARP inhibitor based therapy comprising: measuring the amount of MUTYH and at least one other biomarker selected from: ATM, BRCA1 , BRCA2, MRE1 1 A, ATR, CHEK2 and MDC1 , in a tumour cell containing sample from said cancer patient, comparing these amounts to reference values; and, selecting the patient for treatment with PARP inhibitor based therapy if, compared to the reference values, the level of MUTYH is not low and the level of the other biomarker is reduced in the tumour cell containing sample from said cancer patient.
As shown in the Example 2 herein, in colorectal cancer, the HR deficiencies observed were MRE1 1 A and ATM while in gastric cancers only ATM deficiencies were associated with olaparib sensitivity.
Thus according to another aspect, the methods of the invention can be applied to testing colorectal or gastric cancers. In a particular embodiment the measurement of PARP-1 and ATM and/or MRE1 1 A can be used to select or identify colorectal or gastric cancer patients for treatment with a PARP inhibitor as required.
According to another aspect of the invention there is provided the use of a PARP inhibitor compound in the manufacture of a medicament for treating a patient suffering from colorectal cancer whose cancer cells are deficient in ATM and/or MRE1 1 A. Further, there is provided a method for selecting a colorectal cancer patient for PARP inhibitor based therapy comprising: measuring the amount of ATM and/or MRE1 1 A in a tumour cell containing sample from said cancer patient, comparing these amounts to reference values; and, selecting the patient for treatment with PARP inhibitor based therapy if, compared to the reference values, the level of ATM and/or MRE1 1A is low.
According to another aspect of the invention there is provided the use of a PARP inhibitor compound in the manufacture of a medicament for treating a patient suffering from gastric cancer whose cancer cells are deficient in ATM. Further, there is provided a method for selecting a gastric cancer patient for PARP inhibitor based therapy comprising: measuring the amount of ATM in a tumour cell containing sample from said cancer patient, comparing these amounts to reference values; and, selecting the patient for treatment with PARP inhibitor based therapy if, compared to the reference values, the level of ATM is low.
According to another aspect of the invention there is provided a method for identifying whether an individual with cancer will likely be responsive to a treatment with a PARP inhibitor drug comprising:
a. Obtaining a tumour cell-containing sample from the individual;
b. Analyzing said sample to obtain a first gene expression profile, which profile includes one or more genes from Table 1 such as PARP-1 , MUTYH, POLD1 and POLE3, at least one gene from Table 2 and at least one gene from Table 3;
c. Comparing said first gene expression profile to a PARP inhibitor predictor set of gene expression profiles by applying a mathematical algorithm derived from previous PARP inhibitor treated samples to make a prediction as to whether the individual will likely be responsive to a treatment with a PARP inhibitor drug. The inventors have discovered three clusters of biomarkers with predictive value for PARP inhibitor efficacy. Those listed in Table 1 include genes generally known to be associated with the base excision repair pathway and a number of other genes shown to be part of a BER interaction network. Table 1 has therefore been nominally termed the BER group. However, as used herein when discussing the selection or use of a BER gene from Table 1 it is to be appreciated that it embraces any gene in Table 1 , not just those that are classically (in public domain) known as BER pathway genes.
Similarly, with the cluster of genes in Table 2, many of these are known
homologous recombination repair genes. However, some have not been
demonstrated publically to be part of the HR repair pathway. When discussing the selection or use of a HR gene from Table 2, it is to be appreciated that this embraces any gene in Table 2 and not just those that are classically known as HR pathway genes. Similarly, with the cluster of genes in Table 3, many of these genes are known to be involved in cell proliferation. However, many are not. When discussing the selection or use of a proliferation gene from Table 3, it is to be appreciated that this embraces any gene in Table 3 and not just those that are classically known to be involved in cell proliferation
The inventors have found that a multiplex diagnostic involving at least one gene from each of Tables 1 , 2 and 3, yields even greater statistically significant prediction of likely response to PARP inhibitor than either PARP-1 or an HR deficiency alone.
With respect to the BER group (Table 1 ), in addition to PARP-1 , MUTYH was found to be extremely predictive (even when used alone) and examples were also identified where POLD1 or POLE3 could replace PARP-1 or MUTYH from the BER group of genes providing predictive value.
Thus, the various aspects of the invention (diagnostic patient selection, therapeutic treatment) can be applied to MUTYH alone.
Other BER genes that were particularly useful include POLD1 and POLE3. With respect to the HR group of genes (Table 2), the inventors found that MCM2, XRCC3, BRCA1 , MDC1 , ATM, ATR, NBN, RAD51 and MRE1 1A were particularly predictive when combined with a gene from Table 1 and one from Table 3.
With respect to the proliferation group (Table 3), certain of these genes are predictive when over-expressed, others when under-expressed. The direction of expression for each individual gene is shown in Table 3. The inventors found that AURKA, SMARCD3, ZIC1 , SSX2IP, BOC, POLH, TP53BP2, SCMH1 , SMARCA5, MRAS, IP6K2, GTF2H4, MBD1 , RASA3, ZMYM4, PHF13, ARNT, KDM4A, PCBP4, TLR4, NUDT1 , PMS1 and ZMYM6 were particularly predictive when combined with a gene from Table 1 and one from Table 2 although many different genes from Table 3 also increased the predictive value when combined with a gene from Table 1 and Table 2 (see Table 12). In particular Table 12 shows that each of AURKA, SMARCD3, ZIC1 , SSX2IP, BOC, POLH, TP53BP2, SCMH1 , SMARCA5, MRAS, IP6K2, GTF2H4, MBD1 , RASA3, ZMYM4, PHF13, ARNT, KDM4A, PCBP4, TLR4, NUDT1 , PMS1 and ZMYM6 increased the predictive value when combined with a gene from Table 1 and Table 2.
In another aspect, the invention provides a method for selecting a cancer patient for treatment with a PARP inhibitor comprising measuring the expression level of at least one BER biomarker from Table 1 , at least one homologous recombination biomarker from Table 2 and at least one proliferation biomarker from Table 3, in a cancer cell containing sample obtained from the patient and selecting the patient for treatment with a PARP inhibitor if the expression profile of the at least three biomarkers identifies the patient as being a likely responder to treatment with the PARP inhibitor. In a particular embodiment the biomarker(s) from Table 1 is selected from PARP-1 and MUTYH, POLD1 or POLE3. In another embodiment the homologous recombination biomarker from Table 2 is selected from: MCM2, XRCC3, BRCA1 , MDC1 , ATM, ATR, NBN, RAD51 and MRE1 1A. In another embodiment the proliferation biomarker from Table 3 is selected from: AURKA, SMARCD3, ZIC1 , SSX2IP, BOC, POLH, TP53BP2, SCMH1 , SMARCA5, MRAS, IP6K2, GTF2H4, MBD1 , RASA3, ZMYM4, PHF13, ARNT, KDM4A, PCBP4, TLR4, NUDT1 , PMS1 and ZMYM6. In particular from AURKA, SMARCD3, ZIC1 , SSX2IP and BOC.
In certain embodiments, in addition to the PARP-1 and/or MUTYH biomarker one or more, such as 2, 3, 4, 5, 6, 7, 8, 9, 10 or more of the other biomarkers identified in Table 1 are also assessed for their expression level.
In certain embodiments at least 2, at least 3, at least 4, at least 5 or more BER biomarkers from Table 1 are assessed. In certain other embodiments, when more than one BER biomarker is assessed, one of these is PARP-1 or MUTYH.
In certain embodiments, at least 2, such as 3, 4, 5, 6, 7, 8, 9, 10, or more of the other biomarkers identified in Table 2 are also assessed for their expression level. In certain embodiments at least one HR biomarker is selected from the first 20 biomarkers listed in Table 2. In certain embodiments at least 2, at least 3, at least 4, at least 5 or more HR biomarkers from Table 2 are assessed. In other embodiments the HR biomarker is selected from the group consisting of: MCM2, XRCC3, BRCA1 , MDC1 , ATM, ATR, NBN, RAD51 and MRE1 1A.
In certain embodiments, at least 2, such as 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 60, 70, 80, 90, 100 or more of the other biomarkers identified in Table 3 are also assessed for their expression level. In certain embodiments the at least one proliferation biomarker is selected from the first 20 biomarkers listed in Table 3. In certain embodiments at least 2, at least 3, at least 4, at least 5 or more proliferation biomarkers from Table 3 are assessed. In certain other embodiments the proliferation biomarker from Table 3 is selected from: AURKA, SMARCD3, ZIC1 , SSX2IP, BOC, POLH, TP53BP2, SCMH1 , SMARCA5, MRAS, IP6K2, GTF2H4, MBD1 , RASA3, ZMYM4, PHF13, ARNT, KDM4A, PCBP4, TLR4, NUDT1 , PMS1 and ZMYM6, in particular from AURKA, SMARCD3, ZIC1 , SSX2IP and BOC.
In certain other embodiments the combination of 1 biomarker from Table 1 , one from Table 2 and one from Table 3 is any of the combinations shown in Figures 6- 10. According to certain embodiments, the methods of the invention involve
assessment of the expression levels of a set of biomarkers that include (i) PARP- 1 , BRCA1 and AURKA; or (ii) MUTYH, BRCA1 and SMARCD3; or (iii) MUTYH, ATM and ZIC1 ; or (iv) POLD1 , ATM and SSX2IP; or (v) POLE3, BRCA1 and BOC. The set of biomarkers may involve just the recited 3 biomarkers or it may also involve one or more additional biomarkers, which additional biomarker may be from Table 1 , 2 or 3.
The differential biomarker expression values thus provide a profile of expression for the particular cancer cells and a prediction of likely response to treatment with a PARP inhibitor.
The examples described herein assessed the expression levels of each of the biomarkers listed in Tables 1 , 2 and 3 in the 95 cancer cell lines and determined a p-value for the expression of the marker in olaparib sensitive cell lines, compared to resistant cell lines. The highest ranked biomarkers are predicted to be those that will deliver the best predictive value either alone or when combined with the biomarkers from the other Tables. However, it will be appreciated that the most predictive biomarkers for a particular cancer type will likely differ from the most predictive biomarkers for a different cancer type.
In certain embodiments the one or more biomarker(s), in addition to PARP-1 and/or MUTYH, from Table 1 that are measured are selected from: POLD1 and POLE3.
Similarly, with respect to those biomarkers in Table 2, the one or more biomarkers that are measured are selected from the group consisting of MCM2, XRCC3, BRCA1 , MDC1 , ATM, ATR, NBN, RAD51 and MRE1 1 A.
Similarly, with respect to those biomarkers in Table 3, the one or more biomarkers that are measured are selected from the first 20 listed in Table 3. In a further embodiment, with respect to those biomarkers in Table 3, the one or more biomarkers that are measured are selected from the group consisting of: AURKA, SMARCD3, ZIC1 , SSX2IP, BOC, POLH, TP53BP2, SCMH1 , SMARCA5, MRAS, IP6K2, GTF2H4, MBD1 , RASA3, ZMYM4, PHF13, ARNT, KDM4A, PCBP4, TLR4, NUDT1 , PMS1 and ZMYM6, in particular from AURKA, SMARCD3, ZIC1 , SSX2IP and BOC.
Other suitable combinations include: PARP-1 , BRCA1 and AURKA; MUTYH, BRCA1 and SMARCD3; MUTYH, ATM and ZIC1 ; POLD1 , ATM and SSX2IP; POLE3, BRCA1 and BOC. Additional combination examples that provide improved predictive value are listed in Table 13. In particular embodiments, the methods of the inventions comprise or consist of any of the combinations listed in Table 13.
These diagnostic patient selection methods do not involve the actual step of isolating the cancer cell-containing sample. Rather they are carried out on samples that have previously been isolated and are thus ex vivo diagnostic tests.
An individual suitable for treatment or identification as described herein may include a eukaryote, an animal, a vertebrate animal, a mammal, a rodent (e.g. a guinea pig, a hamster, a rat, a mouse), a murine (e.g. a mouse), a canine (e.g. a dog), a feline (e.g. a cat), an equine (e.g. a horse), a primate, such as a simian (e.g. a monkey or ape), a monkey (e.g. marmoset, baboon), an ape (e.g. gorilla, chimpanzee, gibbon), or a human. The various aspects of the invention are particularly suited for application to humans.
Biomarker expression patterns of the invention may be identified by analysis of gene expression in samples containing cancer cells, e.g. tumour biopsies or blood samples that contain circulating cancer cells. The overall gene expression profile of a sample can be obtained through quantifying the expression levels of mRNA or protein corresponding to one or more of the genes (biomarkers) identified herein, that the inventors have found correlate with response to PARP inhibitor.
The correlated biomarkers may be used singly with significant accuracy or in combination to increase the ability to accurately predict favourable treatment with a PARP inhibitor, in particular olaparib. The present invention thus provides means for correlating a molecular expression phenotype with likely outcome following PARP inhibitor treatment. Expression of the biomarkers can be determined at the protein or nucleic acid level using any method known in the art. For example, at the nucleic acid level Northern hybridization analysis using probes which specifically recognize one or more of these sequences can be used to determine gene expression.
Alternatively, expression can be measured using reverse-transcription-based PCR assays, e.g., using primers specific for the differentially expressed sequence of genes.
In particular embodiments the diagnostic methods of the invention are carried out on fresh samples, frozen samples or formalin-fixed, paraffin-embedded tissue samples.
An assay of the invention may utilize a means related to the expression level of a biomarker disclosed herein as long as the assay reflects, quantitatively or qualitatively, expression of the biomarker. In one embodiment a quantitative assay is performed. The ability to discriminate is conferred by the identification of expression of the individual biomarkers as relevant and not by the form of the assay used to determine the actual level of expression. An assay may utilize any identifying feature of an identified individual biomarker as disclosed herein as long as the assay reflects, quantitatively or qualitatively, expression of the biomarker. Identifying features include, but are not limited to, unique nucleic acid sequences used to encode (DNA), or express (RNA), said gene or epitopes specific to, or activities of, a protein encoded by said gene. Alternative means include detection of nucleic acid amplification as indicative of increased expression levels and nucleic acid inactivation, deletion, or methylation, as indicative of decreased expression levels. The invention may be practiced by assaying one or more aspect of the DNA template(s) underlying the expression of the disclosed sequence(s), of the RNA used as an intermediate to express the sequence(s), or of the
proteinaceous product expressed by the sequence(s), as well as proteolytic fragments of such products. As such, the detection of the presence of, amount of, stability of, or degradation (including rate) of, such DNA, RNA and proteinaceous molecules may be used in the practice of the invention. Accordingly, all that is required is an appropriate cancer cell-containing sample from the patient for analysis. This can for example, be cells from a solid biopsy sample or may be circulating cancer (tumour) cells (CTCs).
To determine the (increased or decreased) expression levels of genes in the practice of the present invention, any method known in the art may be utilized. In one preferred embodiment of the invention, expression based on detection of mRNA, which hybridizes to the genes identified and disclosed herein is used. This is readily performed by any RNA detection or amplification+detection method known or recognized as equivalent in the art such as, but not limited to, reverse transcription-PCR, the methods disclosed in U.S. patent publication number US2003/0022194 (claiming priority from U.S. patent application Ser. No.
10/062,857) and resulting in granted US patent US 6,794,141 ; as well as in WO 2002/052031 (claiming priority from U.S. Provisional Patent Applications
60/298,847 and 60/257,801 , and US regular application 10/062,857), and methods to detect the presence, or absence, of RNA stabilizing or destabilizing sequences.
The detection of gene expression from the samples may be by use of a single microarray able to assay gene expression of the genes disclosed herein. Thus in particular embodiments, the expression levels are determined by microarray analysis.
Because the invention relies upon the identification of genes that are over-or under-expressed, one embodiment of the invention involves determining expression by hybridization of mRNA, or an amplified or cloned version thereof, of a sample cell to a polynucleotide that is unique to a particular gene sequence. In one embodiment, one or more sequences capable of hybridising to one or more of the genes identified herein is immobilised on a solid support or microarray.
Alternatively, solution based expression assays known in the art may also be used. The immobilized gene(s) may be in the form of polynucleotides that are unique or otherwise specific to the gene(s) such that the polynucleotide would be capable of hybridizing to a DNA or RNA corresponding to the gene(s). These polynucleotides may be the full length of the gene(s) or be short sequences of the genes (up to one nucleotide shorter than the full length sequence known in the art by deletion from the 5' or 3' end of the sequence) that are optionally minimally interrupted (such as by mismatches or inserted non-complementary base pairs) such that hybridization with a DNA or RNA corresponding to the gene(s) is not affected. In certain embodiments, the polynucleotides used are from the 3' end of the gene, such as within about 350, about 300, about 250, about 200, about 150, about 100, or about 50 nucleotides from the polyadenylation signal or
polyadenylation site of a gene or expressed sequence.
Preferred polynucleotides contain at least about 18, at least about 20, at least about 22, at least about 24, at least about 26, at least about 28, at least about 30, or at least about 32, at least about 34, at least about 36, at least about 38, at least about 40, at least about 42, at least about 44, or at least about 46 consecutive base pairs of a gene sequence that is not found in other gene sequences. The term "about" as used in the previous sentence refers to an increase or decrease of 1 from the stated numerical value. Even more preferred are polynucleotides of at least or about 50, at least or about 100, at least about or 150, at least or about 200, at least or about 250, at least or about 300, at least or about 350, or at least or about 400 base pairs of a gene sequence that is not found in other gene sequences. The term "about" as used in the preceding sentence refers to an increase or decrease of 10% from the stated numerical value. Such
polynucleotides may also be referred to as polynucleotide probes that are capable of hybridizing to sequences of the genes, or unique portions thereof, described herein. In one embodiment, the sequences are those of mRNA encoded by the genes, the corresponding cDNA to such mRNAs, and/or amplified versions of such sequences. In certain embodiments of the invention, the polynucleotide probes are immobilized on a microarray, other devices, or in individual spots that localize the probes on a support. Polynucleotides containing mutations relative to the sequences of the disclosed genes may also be used so long as the presence of the mutations still allows hybridization to produce a detectable signal.
In another embodiment of the invention, all or part of a disclosed biomarker sequence may be amplified and detected by methods such as the polymerase chain reaction (PCR) and variations thereof, such as, but not limited to,
quantitative PCR (Q-PCR), reverse transcription PCR (RT-PCR), and real-time PCR (including as a means of measuring the initial amounts of mRNA copies for each sequence in a sample), optionally real-time RT-PCR or real-time Q-PCR. Such methods would utilize one or two primers that are complementary to portions of a disclosed sequence, where the primers are used to prime nucleic acid synthesis. The newly synthesized nucleic acids are optionally labelled and may be detected directly or by hybridization to a polynucleotide of the invention. The newly synthesized nucleic acids may be contacted with biomarker polynucleotides of the invention under conditions, which allow for their hybridization. Additional methods to detect the expression of expressed nucleic acids include RNAse protection assays, including liquid phase hybridizations, and in situ hybridization of cells. The Ct values generated by such methods may be used to generate the ratios of expression levels as described herein.
In particular embodiments, the expression level is determined by reverse phase polymerase chain reaction (RT-PCR).
In other embodiments the RNA is fragmented.
In embodiments where only one or a few genes are to be analyzed, the nucleic acid derived from the sample cancer cell(s) may be preferentially amplified by use of appropriate primers such that only the genes to be analyzed are amplified to reduce contaminating background signals from other genes expressed in the cancer cell. Alternatively and where multiple genes are to be analyzed or where very few cells (or one cell) are used, the nucleic acid from the sample may be globally amplified before hybridization to the immobilized polynucleotides. Of course RNA or the cDNA counterpart thereof may be directly labelled and used, without amplification, by methods known in the art.
In one embodiment of the invention, the isolation and analysis of a cancer-cell containing sample may be performed as follows: (1 ) RNA is extracted from a tissue biopsy sample obtained from a cancer patient;
(2) RNA is purified, amplified, and labelled;
(3) Labelled nucleic acid is contacted with a microarray containing
polynucleotides of the genes identified herein as correlated to discriminate between PARP inhibitor treatment status under hybridization conditions to allow hybridization to occur, and the expression levels of the biomarkers is measured; and
(4) A mathematical algorithm is applied to predict the likelihood of response to the PARP inhibitor.
Binding of a probe to target nucleic acid (e.g. DNA) may be measured using any of a variety of techniques at the disposal of those skilled in the art. For instance, probes may be radioactively, fluorescently or enzymatically labelled. Other methods not employing labelling of probe include examination of restriction fragment length polymorphisms, amplification using PCR, RN'ase cleavage and allele specific oligonucleotide probing.
Those skilled in the art are well able to employ suitable conditions of the desired stringency for selective hybridisation, taking into account factors such as oligonucleotide length and base composition, temperature and so on.
Suitable selective hybridisation conditions for oligonucleotides of 17 to 30 bases include hybridization overnight at 42°C in 6X SSC and then washing in 6X SSC at a series of increasing temperatures from 42°C to 65°C. For example, probes may be washed in 6xSSC at 42 °C for 30 minutes then 6xSSC at 50°C for 45 mins then 2xSSC for 45 mins at 65°C. Other suitable conditions and protocols are described in Molecular Cloning: a Laboratory Manual: 3rd edition, Sambrook & Russell (2001 ) Cold Spring Harbor Laboratory Press NY and Current Protocols in
Molecular Biology, Ausubel et al. eds. John Wiley & Sons (1992).
Alternatively, and in yet another embodiment of the invention, gene expression may be determined at the protein level, e.g. by measuring the levels of peptides encoded by the gene products described herein, or activities thereof. Such methods are well known in the art and include, e.g., any immunohistochemistry (IHC) based, blood based (especially for secreted proteins), antibody (including autoantibodies against the protein) based, ex foliate cell (from the cancer) based, mass spectroscopy based, and image (including used of labelled ligand) based method known in the art and recognized as appropriate for the detection of the protein.
In one embodiment the detection is via an immunoassay that uses one or more antibodies specific for one or more epitopes of individual gene products in a cell sample of interest. Any biological material can be used for the
detection/quantification of the protein or its activity. Alternatively, a suitable method can be selected to determine the activity of proteins encoded by the marker genes according to the activity of each protein analyzed.
The biomarker proteins can be detected in any suitable manner, but are typically detected by contacting a sample from the patient with an antibody that binds the biomarker protein and then detecting the presence or absence of a reaction product. Such as, by use of labelled antibodies against cell surface markers followed by fluorescence activated cell sorting (FACS). Such antibodies are preferably labelled to permit their easy detection after binding to the gene product. Detection methodologies suitable for use in the practice of the invention include, but are not limited to, immunohistochemistry of cell containing samples or tissue, enzyme linked immunosorbent assays (ELISAs) including antibody sandwich assays of cell containing tissues or blood samples, mass spectroscopy, and immuno-PCR.
The antibody may be monoclonal, polyclonal, chimeric, or a fragment of the foregoing, as discussed in detail above, and the step of detecting the reaction product may be carried out with any suitable immunoassay. The sample from the subject is typically a solid tissue sample, e.g. a biopsy, as described above, but may be a cancer cell containing biological fluid, e.g. blood or serum sample. The sample may be in the form of a tissue specimen from a patient where the specimen is suitable for immunohistochemistry in a variety of formats such as paraffin-embedded tissue, frozen sections of tissue, and freshly isolated tissue. The immunodetection methods are antibody-based but there are numerous additional techniques that allow for highly sensitive determinations of binding to an antibody in the context of a tissue. Those skilled in the art will be familiar with various immunohistochemistry strategies.
Immunoassays carried out in accordance with the present invention may be homogeneous assays or heterogeneous assays. In a homogeneous assay the immunological reaction usually involves the specific antibody (e.g., anti- biomarker protein antibody), a labelled analyte, and the sample of interest. The signal arising from the label is modified, directly or indirectly, upon the binding of the antibody to the labelled analyte. Both the immunological reaction and detection of the extent thereof are carried out in a homogeneous solution. Immunochemical labels that may be employed include free radicals, radioisotopes, fluorescent dyes, enzymes, bacteriophages, or coenzymes.
In a heterogeneous assay approach, the reagents are usually the sample, the antibody, and means for producing a detectable signal. Samples as described above may be used. The antibody is generally immobilized on a support, such as a bead, plate or slide, and contacted with the specimen suspected of containing the antigen in a liquid phase. The support is then separated from the liquid phase and either the support phase or the liquid phase is examined for a detectable signal employing means for producing such signal. The signal is related to the presence of the analyte in the sample. Means for producing a detectable signal include the use of radioactive labels, fluorescent labels, or enzyme labels.
For example, if the antigen to be detected contains a second binding site, an antibody which binds to that site can be conjugated to a detectable group and added to the liquid phase reaction solution before the separation step. The presence of the detectable group on the solid support indicates the presence of the antigen in the test sample. Examples of suitable immunoassays are radioimmunoassays, immunofluorescence methods, chemiluminescence methods, electrochemiluminescence or enzyme-linked immunoassays.
Those skilled in the art will be familiar with numerous specific immunoassay formats and variations thereof, which may be useful for carrying out the method disclosed herein. See generally E. Maggio, Enzyme-lmmunoassay, (1980) (CRC Press, Inc., Boca Raton, Fla.); see also U.S. Pat. No. 4,727,022 to Skold et al. titled "Methods for Modulating Ligand-Receptor Interactions and their Application," U.S. Pat. No. 4,659,678 to Forrest et al. titled "Immunoassay of Antigens," U.S. Pat. No. 4,376,1 10 to David et al., titled "Immunometric Assays Using Monoclonal Antibodies," U.S. Pat. No. 4,275,149 to Litman et al., titled "Macromolecular Environment Control in Specific Receptor Assays," U.S. Pat. No. 4,233,402 to Maggio et al., titled "Reagents and Method Employing Channeling," and U.S. Pat. No. 4,230,767 to Boguslaski et al., titled "Heterogenous Specific Binding Assay Employing a Coenzyme as Label."
Antibodies may be conjugated to a solid support suitable for a diagnostic assay (e.g., beads, plates, slides or wells formed from materials such as latex or polystyrene) in accordance with known techniques, such as passive binding.
Antibodies as described herein may likewise be conjugated to detectable groups such as radiolabels (e.g., 35 S, 125 I, 131 I), enzyme labels (e.g., horseradish peroxidase, alkaline phosphatase), and fluorescent labels (e.g., fluorescein) in accordance with known techniques.
The skilled artisan can routinely make antibodies, nucleic acid probes, e.g., oligonucleotides, aptamers, siRNAs against any of the biomarkers in Tables 1 , 2 or 3.
While even a single correlated gene sequence may to able to provide adequate accuracy in discriminating between cancer cell populations according to whether or not they will respond favourably to treatment with a PARP inhibitor, the present invention may be practised with any subset of the genes, as disclosed herein. In certain embodiments, 2 or more, 3 or more, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more, 9 or more, 10 or more, 15 or more, 20 or more, 30 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80 or more, 90 or more, 100 or more or all the genes provided in Table 1 , 2 or 3 below may be used in combination to increase the accuracy of the method. The invention thus specifically contemplates the use of a multiplex assay system employing a number of biomarkers from each of Tables 1 , 2 and 3 for use as a subset in the identification of whether a cancer sample is one that will respond favourably to treatment with a PARP inhibitor.
A number of different statistical algorithms can be applied in order to generate a mathematical model combining together the expression levels of two or more genes or proteins with a cut-off to classify subjects as predicted olaparib responders. These include, but are not limited to logistic regression, multiple regression, Cox proportional hazard models, random forests, recursive
partitioning, random survival forests, partial least squares, partial least squares discriminant analysis, Support Vector Machines, neural networks.
Increases and decreases in expression of the disclosed sequences can be determined based upon percent or fold changes over expression in normal cells, reference cells or normalised against one or more housekeeping genes. Increases may be of 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 120, 140, 160, 180, or 200% relative to expression levels in normal cells. Alternatively, fold increases may be of 1 , 1 .5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, or 10 fold over expression levels in normal cells. Decreases may be of 10, 20, 30, 40, 50, 55, 60, 65, 70, 75, 80, 82, 84, 86, 88, 90, 92, 94, 96, 98, 99 or 100% relative to expression levels in normal cells. For example, a 2-fold increase or decrease is a useful measure for determining whether or not the expression level is low or high. The actual level of expression of any biomarker used according to the invention to predict response to a PARP inhibitor will need to be determined empirically using clinical samples and an appropriate algorithm as described further herein.
The materials for use in the methods of the present invention are ideally suited for preparation of kits produced in accordance with well-known procedures. The invention thus provides kits comprising agents for the detection of expression of the disclosed genes for determining susceptibility to treatment with a PARP inhibitor. Such a kit may comprise separate containers, each with one or more of the various reagents (typically in concentrated form) utilized in the methods, e.g., The kit may contain in separate containers one or more nucleic acids or antibodies (either already bound to a solid matrix or packaged separately with reagents for binding them to the matrix), control formulations (positive and/or negative), and/or a detectable label, as well as other reagents such as buffers, nucleotide
triphosphates, reverse transcriptase, DNA polymerase, RNA polymerase packaged together in the form of a kit.. Instructions (e.g., written, or on electronic medium, e.g. CD-ROM, etc.) for carrying out the assay may be included in the kit. The assay may for example be in the form of a Northern hybridization or a sandwich ELISA as known in the art.
Suitable cancer cell(s) for use in the described methods may be obtained from an individual in a tissue sample for example a biopsy from a cancerous tissue or a blood sample that contains circulating tumour cells.
The cancer can be any cancer. However, in particular embodiments, the cancer is selected from the group consisting of breast cancer, colorectal cancer, head and neck cancer, lung cancer, gastric cancer, prostate, haematological cancers, pancreatic cancer and ovarian cancer.
In certain embodiments the expression level of the biomarker(s) can be compared to that detected in control cell(s), which may be obtained from non-cancerous tissue from the same or a different individual. Suitable controls include non-cancer cells from the same tissue or lineage. Comparison can be performed on test and reference samples measured concurrently or at temporally distinct times. An example of the latter is the use of compiled expression information, e.g., a sequence database, which assembles information about expression levels of the biomarker(s). If the reference sample, e.g., a control sample is from cells that are sensitive to a therapeutic compound then a similarity in the amount of the biomarker proteins in the test sample and the reference sample indicates that treatment with that therapeutic compound will be efficacious. However, a change in the amount of the biomarker in the test sample and the reference sample indicates treatment with that compound will result in a less favourable clinical outcome or prognosis. In contrast, if the reference sample, e.g., a control sample is from cells that are resistant to a therapeutic compound then a similarity in the amount of the biomarker proteins in the test sample and the reference sample indicates that the treatment with that compound will result in a less favourable clinical outcome or prognosis. However, a change in the amount of the biomarker in the test sample and the reference sample indicates that treatment with that therapeutic compound will be efficacious. In some embodiments, the pattern of biomarker expression in the test sample is measured and then may be normalised against one or more control genes. Examples of control genes against which the biomarker expression levels can be normalised include, but are not limited to: ACTB (ACTB 60), B2M (B2M 567), GAPDH (GAPDH 2597), GUSB (GUSB 2990), HMBS (HMBS 3145), HPRT1 (HPRT1 3251 ), IPO8 (IPO8 10526), PGK1 (PGK1 5230), POLR2A (POLR2A 5430), PPIA (PPIA 5478), RPLP0 (RPLP0 6175), TBP (TBP 6908), TFRC (TFRC 7037), UBC (UBC 7316), YWHAZ (YWHAZ 7534); The Entrez gene IDs are in brackets. Another commonly used housekeeping gene is 18s rRNA (Genbank accession number is X03205).
A mathematical algorithm which has been pre-determined by the analysis of preclinical or historical clinical data cane then be applied to the expression measures to give a prediction of the sensitivity to olaparib.
The methods provided by the present invention may also be automated in whole or in part. All aspects of the present invention may also be practiced such that they consist essentially of a subset of the disclosed genes to the exclusion of material irrelevant to the identification of cells treatable with a PARP inhibitor.
The diagnostic methods permit the identification of which patient or patient populations are likely to be responsive to treatment with a PARP inhibitor, such as olaparib. Accordingly, the present invention also opens up the possibility of treating the patient or patient populations identified as likely to be responsive to a PARP inhibitor.
Thus, according to another aspect of the invention there is provided a method of treating a patient suffering from cancer comprising determining whether or not the patient will respond favourably to a PARP inhibitor according the method as claimed in any of claims, and administering an effective amount of a PARP inhibitor to said patient if they are identified as likely to be responsive to treatment with a PARP inhibitor.
Thus, according to another aspect of the invention there is provided a method of treating cancer comprising determining the expression level of PARP-1 in a cancer cell containing sample from the subject and if the PARP-1 expression level is not low, administering to the subject an effective amount of a PARP inhibitor. In a particular embodiment the PARP inhibitor is olaparib.
In another aspect, there is provided a method of treating cancer comprising determining the expression level of PARP-1 and/or MUTYH and one or more genes involved in homologous recombination repair as listed in Table 2 in a cancer cell containing sample from a patient, and administering an effective amount of a PARP inhibitor compound to a patient whose cancer cells do not express low levels of PARP-1 or MUTYH but do express differences in expression in any of the homologous recombination repair genes according to Table 2, and in particular the directionality shown therein. In a particular embodiment the PARP inhibitor is olaparib. In further embodiment the homologous recombination repair gene is selected from: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1 A.
In another aspect there is provided a method of treating cancer comprising measuring the expression level of at least one base excision repair biomarker from Table 1 , at least one homologous recombination biomarker from Table 2 and at least one proliferation biomarker from Table 3, in a cancer cell containing sample obtained from the patient and if the expression profile of the biomarkers identifies the patient as being a likely responder to treatment with the PARP inhibitor, administering to said patient an effective amount of a PARP inhibitor. In a particular embodiment the PARP inhibitor is olaparib. In another embodiment the biomarker(s) from Table 1 is selected from PARP-1 and MUTYH. In another embodiment the homologous recombination biomarker from Table 2 is selected from: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1A. In another embodiment the proliferation biomarker from Table 3 is selected from AURKA, SMARCD3, ZIC1 , SSX2IP, BOC, POLH, TP53BP2, SCMH1 , SMARCA5, MRAS, IP6K2, GTF2H4, MBD1 , RASA3, ZMYM4, PHF13, ARNT, KDM4A, PCBP4, TLR4, NUDT1 , PMS1 and ZMYM6.
In a further aspect of the invention there is provided a method for selecting a cancer patient for treatment with a PARP inhibitor comprising: measuring the expression level of at least three biomarker RNA transcripts or their products in a cancer cell containing sample obtained from said patient, wherein at least one of the biomarkers is selected from Table 1 , at least one of the biomarkers is selected from Table 2; and, at least one of the biomarkers is selected from Table 3, comparing the level of each measured biomarker in the sample to a reference level; and selecting a patient for treatment with a PARP inhibitor based on the biomarker levels present in the sample, with the proviso that PARP-1 represents one biomarker from Table 1 whose expression level is measured.
In a further aspect of the invention there is provided a PARP inhibitor for use in the treatment of a cancer patient whose cancer cells have been identified as not expressing low levels of PARP-1 . In a particular embodiment the PARP inhibitor is olaparib.
In another aspect of the invention there is provided a PARP inhibitor for use in the treatment of a cancer patient whose cancer cells have been identified as not expressing low levels of MUTYH. In a particular embodiment the PARP inhibitor is olaparib.
In another aspect of the invention there is provided a PARP inhibitor for use in the treatment of a cancer patient whose cancer cells have been identified as not expressing low levels of MUTYH do express differences in expression in any of the homologous recombination repair genes according to Table 2, and in particular differences in the directionality shown in Table 2. In a particular embodiment the PARP inhibitor is olaparib. In further embodiment the homologous recombination repair gene is selected from: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1A.
In another aspect of the invention there is provided a PARP inhibitor for use in the treatment of a cancer patient whose cancer cells have been identified as being likely to be responsive to treatment with the PARP inhibitor according to the expression profile generated by measuring the expression levels of PARP-1 and/or MUTYH and at least one homologous recombination repair gene from Table 2. In one embodiment a patient whose cancer cells do not express low levels of PARP-1 or MUTYH but do express low levels of any of the homologous recombination repair genes selected from the group consisting of: BRCA1 ,
BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1 A is selected for treatment and/or treated with the PARP inhibitor compound.
In another aspect there is provided a PARP inhibitor for use in the treatment of a cancer patient whose cancer cells have been identified as being likely to respond to treatment with the PARP inhibitor according to the gene expression profile generated by measuring the expression level of at least one base excision repair biomarker from Table 1 , at least one homologous recombination biomarker from Table 2 and at least one proliferation biomarker from Table 3, in a cancer cell containing sample obtained from the patient . In a particular embodiment the PARP inhibitor is olaparib. In another embodiment the biomarker(s) from Table 1 is selected from PARP-1 and MUTYH. In another embodiment the homologous recombination biomarker from Table 2 is selected from: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1 A. In another embodiment the proliferation biomarker from Table 3 is selected from AURKA, SMARCD3, ZIC1 , SSX2IP, BOC, POLH, TP53BP2, SCMH1 , SMARCA5, MRAS, IP6K2, GTF2H4, MBD1 , RASA3, ZMYM4, PHF13, ARNT, KDM4A, PCBP4, TLR4, NUDT1 , PMS1 and ZMYM6. In another aspect there is provided the use of a PARP inhibitor in the manufacture of a medicament for treating a cancer patient whose cancer cells have been identified as not expressing low levels of PARP-1 . In a particular embodiment the PARP inhibitor is olaparib.
In another aspect there is provided the use of a PARP inhibitor in the manufacture of a medicament for treating a cancer patient whose cancer cells have been identified as not expressing low levels of MUTYH. In a particular embodiment the PARP inhibitor is olaparib.
In another aspect, there is provided the use of a PARP inhibitor in the manufacture of a medicament for treating a cancer patient whose cancer cells have been identified as being likely to be responsive to treatment with the PARP inhibitor according to the expression profile generated by measuring the expression levels of PARP-1 and/or MUTYH and at least one homologous recombination repair gene from Table 2. In a particular embodiment, the cancer cells are identified as being likely to be responsive to treatment with the PARP inhibitor if the cancer cells do not express low levels of PARP-1 and/or MUTYH but do express low levels of any of the homologous recombination repair genes from Table 2. In a particular embodiment the PARP inhibitor is olaparib. In further embodiment the
homologous recombination repair gene is selected from: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1 A.
In another aspect, there is provided the use of a PARP inhibitor in the manufacture of a medicament for treating a cancer patient whose cancer cells have been identified as not expressing low levels of PARP-1 and/or MUTYH but do express differences in expression in any of the homologous recombination repair genes according to Table 2, and in particular according to the directionality in Table 2. In a particular embodiment the PARP inhibitor is olaparib. In further embodiment the homologous recombination repair gene is selected from: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1 A. In another aspect, there is provided the use of a PARP inhibitor in the manufacture of a medicament for treating a cancer patient whose cancer cells have been identified as not expressing low levels of PARP-1 and/or MUTYH but do express differences in expression in any of the homologous recombination repair genes according to Table 2, and in particular according to the directionality in Table 2.
In another aspect there is provided the use of a PARP inhibitor in the manufacture of a medicament for treating a cancer patient whose cancer cells have been tested for expression level of at least one base excision repair biomarker from Table 1 , at least one homologous recombination biomarker from Table 2 and at least one proliferation biomarker from Table 3, and the expression profile of the biomarkers has identified the patient as being a likely responder to treatment with the PARP inhibitor.
In a particular embodiment the PARP inhibitor is olaparib. In another embodiment the biomarker(s) from Table 1 is selected from PARP-1 and MUTYH. In another embodiment the homologous recombination biomarker from Table 2 is selected from: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1A. In another embodiment the proliferation biomarker from Table 3 is selected from AURKA, SMARCD3, ZIC1 , SSX2IP, BOC, POLH, TP53BP2, SCMH1 , SMARCA5, MRAS, IP6K2, GTF2H4, MBD1 , RASA3, ZMYM4, PHF13, ARNT, KDM4A, PCBP4, TLR4, NUDT1 , PMS1 and ZMYM6.
A treatment regimen comprising administration of a PARP inhibitor to a patient may be designed for an individual identified according to the present invention. For example, a suitable PARP inhibitor may be selected and the dosage and schedule of administration established for the individual using appropriate medical criteria.
The methods described herein may be particularly useful in identifying cohorts of cancer patients, for example for clinical trials of PARP inhibitor compounds.
The term 'PARP' as used herein refers to PARP-1 (EC 2.4.2.30, Genbank No: M32721 .1 Gl: 190266, D'Amours et al, (1999) Biochem. J. 342: 249-268; Ame et al., BioEssays (2004) 26 882-893) and/or PARP2 (Ame et al., J. Biol. Chem.
(1999) 274 15504-1551 1 ; Genbank No: AJ236912.1 Gl: 6688129), unless context dictates otherwise.
PARP inhibition may be determined using conventional methods, including for example dot blots (Affar EB et al., Anal Biochem. 1998; 259(2):280-3), and BER assays that measure the direct activity of PARP to form poly ADP-ribose chains for example by using radioactive assays with tritiated substrate NAD or specific antibodies to the polymer chains formed by PARP activity (K.J. Dillon et al, Journal of Biomolecular Screening, 8(3): 347-352 (2003). Examples of suitable methods for determining PARP activity are described below.
Examples of compounds which are known PARP inhibitors and which may be used in accordance with the invention include:
1 . Nicotinamides, such as 5-methyl nicotinamide and O-(2-hydroxy-3- piperidino-propyl)-3-carboxylic acid amidoxime, and analogues and derivatives thereof.
2. Benzamides, including 3-substituted benzamides such as 3- aminobenzamide, 3-hydroxybenzamide, 3-nitrosobenzamide, 3- methoxybenzamide and 3-chloroprocainamide, and 4-aminobenzamide, 1 , 5-di[(3- carbamoylphenyl)aminocarbonyloxy] pentane, and analogues and derivatives thereof.
3. Isoquinolinones and Dihydroisoquinolinones, including 2H-isoquinolin-1 -ones, 3H-quinazolin-4-ones, 5-substituted dihydroisoquinolinones such as 5-hydroxy dihydroisoquinolinone, 5-methyl dihydroisoquinolinone, and 5-hydroxy
isoquinolinone, 5-amino isoquinolin-1 -one, 5-dihydroxyisoquinolinone, 3, 4 dihydroisoquinolin-1 (2H)-ones such as 3, 4 dihydro-5-methoxy-isoquinolin-1 (2H)- one and 3, 4 dihydro-5-methyl-1 (2H)isoquinolinone, isoquinolin-1 (2H)-ones, 4,5- dihydro-imidazo[4,5,1 -ij]quinolin-6-ones, 1 , 6,-naphthyridine-5(6H)-ones, 1 ,8- naphthalimides such as 4-amino-1 ,8-naphthalimide, isoquinolinone, 3, 4-dihydro- 5-[4-1 (1 -piperidinyl) butoxy]-1 (2H)-isoquinolinone, 2, 3- dihydrobenzo[de]isoquinolin-1 -one, 1 -1 1 b-dihydro-[2H]benzopyrano[4, 3, 2- de]isoquinolin-3-one, and tetracyclic lactams, including benzpyranoisoquinolinones such as benzopyrano[4,3,2-de] isoquinolinone, and analogues and derivatives thereof
4. Benzimidazoles and indoles, including benzoxazole-4-carboxamides, benzimidazole-4-carboxamides, such as 2-substituted benzoxazole 4- carboxamides and 2-substituted benzimidazole 4-carboxamides such as 2-aryl benzimidazole 4-carboxamides and 2-cycloalkylbenzimidazole-4-carboxamides including 2-(4-hydroxphenyl) benzimidazole 4-carboxamide,
quinoxalinecarboxamides, imidazopyridinecarboxamides, 2-phenylindoles, 2- substituted benzoxazoles, such as 2-phenyl benzoxazole and 2-(3- methoxyphenyl) benzoxazole, 2-substituted benzimidazoles, such as 2-phenyl benzimidazole and 2-(3-methoxyphenyl) benzimidazole, 1 , 3, 4, 5 tetrahydro- azepino[5, 4, 3-cd]indol-6-one, azepinoindoles and azepinoindolones such as 1 , 5 dihydro-azepino[4, 5, 6-cd]indolin-6-one and dihydrodiazapinoindolinone, 3- substituted dihydrodiazapinoindolinones,such as 3-(4-thfluoromethyl phenyl )- dihydrodiazapinoindolinone, tetrahydrodiazapinoindolinone and 5,6,- dihydroimidazo[4, 5, 1 -j, k][1 , 4]benzodiazopin-7(4H)-one, 2-phenyl-5,6-dihydro- imidazo[4,5,1 -jk][1 ,4]benzodiazepin-7(4H)-one and 2, 3, dihydro-isoindol-1 -one, and analogues and derivatives thereof
5. Phthalazin-1 (2H)-ones and quinazolinones, such as 4-hydroxyquinazoline, phthalazinone, 5-methoxy-4-methyl-1 (2) phthalazinones, 4-substituted
phthalazinones, 4-(1 -piperazinyl)-1 (2H)-phthalazinone, tetracyclic benzopyrano[4, 3, 2-de] phthalazinones and tetracyclic indeno [1 , 2, 3-de] phthalazinones and 2- substituted quinazolines, such as 8-hydroxy-2-methylquinazolin-4-(3H) one, tricyclic phthalazinones and 2-aminophthalhydrazide, and analogues and derivatives thereof.
6. Isoindolinones and analogues and derivatives thereof 7. Phenanthridines and phenanthhdinones, such as 5[H]phenanthhdin-6-one, substituted 5[H] phenanthridin-6-ones, especially 2-, 3- substituted 5[H]
phenanthhdin-6-ones and sulfonamide/carbannide derivatives of
6(5H)phenanthhdinones, thieno[2, 3-c]isoquinolones such as 9-annino thieno[2, 3- c]isoquinolone and 9-hydroxythieno[2, 3-c]isoquinolone, 9-methoxythieno[2, 3- c]isoquinolone, and N-(6-oxo-5, 6-dihydrophenanthridin-2-yl]-2-(N,N- dimethylannino}acetannide, substituted 4,9-dihydrocyclopenta[lmn]phenanthridine- 5-ones, and analogues and derivatives thereof.
8. Benzopyrones such as 1 , 2-benzopyrone, 6-nitrosobenzopyrone, 6-nitroso 1 , 2- benzopyrone, and 5-iodo-6-aminobenzopyrone, and analogues and derivatives thereof.
9. Unsaturated hydroximic acid derivatives such as O-(3-piperidino-2-hydroxy- 1 -propyl)nicotinic amidoxime, and analogues and derivatives thereof.
10. Pyridazines, including fused pyridazines and analogues and derivatives thereof.
1 1 . Other compounds such as caffeine, theophylline, and thymidine, and analogues and derivatives thereof.
According to particular embodiments, the PARP inhibitor is selected from the group consisting of: benzamide, quinolone, isoquinolone, benzopyrone, methyl 3,5-diiodo-4-(4'-methoxyphenoxy)benzoate, and methyl-3,5-diiodo-4-(4'-methoxy- 3',5'-diiodo-phenoxy)benzoate, cyclic benzamide, benzimidazole and indole.
Additional PARP inhibitors are described for example in WO2009/093032,
WO2009/004356, WO2006078503 WO200607871 1 , DE102004050196,
WO2006024545, WO2006003148, WO2006003147, WO2006003146,
PCT/JP03/14319, WO2005123687, WO2005097750, WO2005058843, WO2005054210 , WO2005054209, WO2005054201 , US 2005054631 ,
WO2005012305, WO2004108723 ,WO2004105700, US2004229895,
WO2004096793, WO2004096779, WO2004087713, WO2004048339,
WO2004024694, WO2004014873, US6,635,642, US5,587,384, WO2003080581 , WO2003070707, WO2003055865, WO2003057145, WO2003051879,
US6514983, WO2003007959, US6426415, WO2003007959, WO 2002036599, WO2002094790, WO2002068407, US6476048, WO2001090077,
WO2001085687, WO2001085686, WO2001079184, WO2001057038,
WO2001023390, WO2001021615, WO2001016136, WO2001012199,
WO9524379, Banasik et al. J. Biol. Chem., 267:3, 1569-75 (1992), Banasik et al. Molec. Cell. Biochem. 138:185-97 (1994)), Cosi (2002) Expert Opin. Ther. Patents 12 (7), and Southan & Szabo (2003) Curr Med Chem 10:321 -340, and references therein.
Other examples of compounds which are known PARP inhibitors includes the hydrochloride salt of /V-(-oxo-5,6-dihydro-phenanthridin-2-yl)-/V,/V- dimethylacetamide and other analogues or similar compounds, such as INO-1001 that show PARP inhibition.
One preferred class of PARP inhibitors includes phthalazinones such as 1 (2H)- phthalazinone and derivatives thereof, as described in WO02/36576, which is incorporated herein by reference. In particular, a PARP inhibitor may be a compound of the formula (I):
Figure imgf000050_0001
or an isomer, salt, solvate, chemically protected form, or prodrug thereof, wherein: A and B together represent an optionally substituted, fused aromatic ring; RC is represented by -L-RL, where L is of formula:
-(CH2)n1 -Qn2-(CH2)n3- wherein n1 , n2 and n3 are each selected from 0, 1 , 2 and 3, the sum of n1 , n2 and n3 is 1 , 2 or 3 and Q is selected from O, S, NH, C(=O) or -CR1 R2-, where R1 and R2 are independently selected from hydrogen, halogen or optionally substituted C1 -7 alkyl, or may together with the carbon atom to which they are attached form a C3-7 cyclic alkyl group, which may be saturated (a C3-7 cycloalkyl group) or unsaturated (a C3-7 cycloalkenyl group), or one of R1 and R2 may be attached to an atom in RL to form an unsaturated C3-7 cycloalkenyl group which comprises the carbon atoms to which R1 and R2 are attached in Q, -(CH2)n3- (if present) and part of RL;
and RL is optionally substituted C5-20 aryl; and
RN is selected from hydrogen, optionally substituted C1 -7 alkyl, C3-20
heterocyclyl, and C5-20 aryl, hydroxy, ether, nitro, amino, amido, thiol, thioether, sulfoxide and sulfone.
For example, a preferred compound may have the formula (I) wherein:
A and B together represent an optionally substituted, fused aromatic ring;
RC is -CH2-RL;
RL is optionally substituted phenyl; and
RN is hydrogen.
Other examples of suitable PARP inhibitors are described in WO 2004/080976, which is incorporated herein by reference, and may have the formula (III):
Figure imgf000051_0001
and isomers, salts, solvates, chemically protected forms, and prodrugs thereof wherein:
A and B together represent an optionally substituted, fused aromatic ring;
X can be NRX or CRXRY;
if X = NRX then n is 1 or 2 and if X = CRXRY then n is 1 ;
RX is selected from the group consisting of H, optionally substituted C1 -20 alkyl, C5-20 aryl, C3-20 heterocyclyl, amido, thioamido, ester, acyl, and sulfonyl groups; RY is selected from H, hydroxy, amino;
or RX and RY may together form a spiro-C3-7 cycloalkyl or heterocyclyl group; RC1 and RC2 are both hydrogen, or when X is CRXRY, RC1 , RC2, RX and RY, together with the carbon atoms to which they are attached, may form an optionally substituted fused aromatic ring; and
R1 is selected from H and halo.
Therefore, if X is CRXRY, then n is 1 , the compound is of formula (IV):
Figure imgf000052_0001
If X is NRX, and n is 1 , the compound is of formula (V):
Figure imgf000052_0002
If X is NRX, and n is 2, the compound is of formula (VI):
Figure imgf000053_0001
One of the poly(ADP-ribose)polymerase (PARP) inhibitor compounds disclosed in WO 2004/080976 (compound 168) is 4-[3-(4-cyclopropanecarbonyl-piperazine-1 - carbonyl)-4-fluoro-benzyl]-2H-phthalazin-1 -one, which has the following structure:
Figure imgf000053_0002
It is currently in clinical trials for treating cancers, such as breast and ovarian cancer and has been assigned the International Non-proprietary Name (INN): Olaparib.
In particular embodiments, 4-[3-(4-Cyclopropanecarbonyl-piperazine-1 -carbonyl)- 4-fluoro-benzyl]-2H-phthalazin-1 -one or an isomer, salt, solvate, chemically protected form, or prodrug thereof, is used according to the present invention. Other examples of suitable PARP inhibitors are described in WO2009/ 093032, which is incorporated herein by reference, and have the formula (I):
Figure imgf000054_0001
wherein:
A and B together represent an optionally substituted, fused aromatic ring;
X and Y are selected from CH and CH, CF and CH, CH and CF and N and CH respectively;
Rc is selected from H, Ci-4 alkyl; and
R1 is selected from Ci-7 alkyl, 03-20 heterocyclyl and C5-2o aryl, which groups are optionally substituted; or
Rc and R1 together with the carbon and oxygen atoms to which they are attached form a spiro-C5-7 oxygen-containing heterocyclic group, which is optionally substituted or fused to a C5-7 aromatic ring.
Thus, when Rc is H, the compound is of formula (la):
Figure imgf000054_0002
A suitable compound, from this patent publication, that can be used according to the present invention is 4-(4-Fluoro-3-(4-methoxypiperidine-1 - carbonyl)benzyl)phthalazin-1 (2H)-one. Other examples of suitable PARP inhibitors are described in WO2008/122810, which is incorporated herein by reference, and have the formula (I):
Figure imgf000055_0001
(including isomers, salts, solvates, chemically protected forms, and prodrugs thereof)
wherein:
A and B together represent an optionally substituted, fused aromatic ring;
X is selected from H and F;
R1 and R2 are independently selected from H and methyl;
RN1 is selected from H and optionally substituted Ci-7 alkyl;
RN2 is selected from H, optionally substituted Ci-7 alkyl, C3-7 heterocylyl and C5-6 aryl;
or RN1 and RN2 and the nitrogen atom to which they are bound form an optionally substituted nitrogen containing C5-7 heterocyclic group.
Other examples of suitable PARP inhibitors are described in WO2009/004356, which is incorporated herein by reference, and have the formula (I):
Figure imgf000055_0002
wherein:
R represents one or more optional substituents on the fused cyclohexene ring; X can be NRX or CRxRY; if X = NR then n is 1 or 2 and if X = CR R then n is 1 ;
if X = NRX, then Rx is selected from the group consisting of H, optionally substituted
Figure imgf000056_0001
alkyl, optionally substituted C5-2o aryl, optionally substituted 03-20 heterocyclyl, optionally substituted amido, optionally substituted thioamido, optionally substituted ester, optionally substituted acyl, and optionally substituted sulfonyl groups;
if X = CRXRY then Rx is selected from the group consisting of H, optionally substituted
Figure imgf000056_0002
alkyl, optionally substituted C5-2o aryl, optionally substituted 03-20 heterocyclyl, optionally substituted amido, optionally substituted thioamido, optionally substituted sulfonamino, optionally substituted ether, optionally substituted ester, optionally substituted acyl, optionally substituted acylamido and optionally substituted sulfonyl groups and RY is selected from H, hydroxy, optionally substituted amino, or Rx and RY may together form an optionally substituted spiro-C3-7 cycloalkyl or heterocyclyl group;
RC1 and RC2 are both hydrogen, or when X is CRXRY, RC1, RC2, Rx and RY, together with the carbon atoms to which they are attached, may form an optionally substituted fused aromatic ring; and
R1 is selected from H and halo.
Therefore, if X is CRXRY, then n is 1 , the compound is of formula (la):
Figure imgf000056_0003
If X is NR , and n is 1 , the compound is of formula (lb):
Figure imgf000057_0001
If X is NR , and n is 2, the compound is of formula (Ic):
Figure imgf000057_0002
The present invention can be applied to any compound disclosed and/or exemplified in these patent publications.
PARP inhibitors currently in clinical trials include olaparib (AstraZeneca/KuDOS), INO-1001 (Inotek), AG-0014699 (Pfizer), and BSI-201 (BiPar Sciences), ABT888 (Abbott; INN = veliparib) and MK4827 (Merck); and PARP inhibitors in preclinical trials include BSI-401 and BSI-101 (BiPar Sciences).
2-[(2R)-2-methylpyrrolidin-2-yl]-3H-benzimidazole-4-carboxamide (ABT888) is disclosed in US 2006229289.
2-{4-[(3S)-Piperidin-3-yl]phenyl}-2H-indazole-7-carboxamide (MK4827) is disclosed in WO 2008084261 ).
4-iodo-3-nitrobenzamide (BSI-201 ) is disclosed in WO 9426730.
8-fluoro-2-{4-[(methylamino)methyl]phenyl}-1 ,3,4,5-tetrahydro-6H-azepino[5,4,3- cd]indol-6-one (AG-0014699) is disclosed in WO 2000042040. CEP-9881 is disclosed in WO 2009121031 .
In some preferred embodiments, the PARP inhibitor may be a compound selected from the group consisting of: 3-[2-fluoro-5-(4-oxo-3,4-dihydro-phthalazin-1 - ylmethyl)-phenyl]-5-methyl-imidazolidine-2,4-dione; 3-[3-(5,8-difluoro-4-oxo-3,4- dihydro-phthalazin-1 -ylmethyl)-phenyl]-5-methyl-imidazoline-2,4-dione; 5-chloro- 2-{1 -[3-([1 ,4]diazepane-1 -carbonyl)-4-fluoro-phenyl]-ethoxy}-benzamide; 2-{3-[2- fluoro-5-(4-oxo-3,4-dihydro-phthalazin-1 -yl methyl )-phenyl]-5-methyl-2,4-dioxo- imidazolidin-1 -yl}-acetamide; 4-[3-(4-Cyclopropanecarbonyl-piperazine-1 - carbonyl)-4-fluoro-benzyl]-2H-phthalazin-1 -one; 3-[2-fluoro-5-(4-oxo-3,4,dihydro- phthalazin-1 -yl methyl )-phenyl]-5,5-dimethyl-1 -[2-(4-methyl-piperazin-1 -yl)-2-oxo- ethyl]-imidazoline-2,4-dione; 8-fluoro-2-(4-methylaminomethyl-phenyl)-1 ,3,4,5- tetrahydro-azepino[5,4,3-cd]indol-6-one; 4-(4-Fluoro-3-(4-methoxypiperidine-1 - carbonyl)benzyl)phthalazin-1 (2H)-one; 2-[(2R)-2-methylpyrrolidin-2-yl]-3H- benzimidazole-4-carboxamide; 2-{4-[(3S)-Piperidin-3-yl]phenyl}-2H-indazole-7- carboxamide; 4-iodo-3-nitrobenzamide; BSI-401 ;CEP9881 , INO-1001 , INO-50065 and BSI-101 .
In some preferred embodiments, the PARP inhibitor may have a greater potency than the potency of 3-aminobenzamide (IC50 ~ 20uM), preferably 5-fold or greater, 10-fold or greater, 50-fold or greater, 100 fold or greater or 1000-fold or greater than the potency of 3-aminobenzamide.
Suitable PARP inhibitors are either commercially available or may be synthesized by known methods from starting materials that are known (see, for example, Suto et al. Anticancer Drug Des. 6:107-17, 1991 ).
While it is possible for an active PARP inhibitor compound to be administered alone, it is preferable to present it as a pharmaceutical composition (e.g., formulation) comprising at least one active compound, as defined above, together with one or more pharmaceutically acceptable carriers, adjuvants, excipients, diluents, fillers, buffers, stabilisers, preservatives, lubricants, or other materials well known to those skilled in the art and optionally other therapeutic or
prophylactic agents.
Pharmaceutical compositions comprising a PARP inhibitor and/or a kinase- mediated cellular pathway inhibitor as defined above, for example, an inhibitor admixed or formulated together with one or more pharmaceutically acceptable carriers, excipients, buffers, adjuvants, stabilisers, or other materials, as described herein, may be used in the methods described herein.
The term "pharmaceutically acceptable" as used herein pertains to compounds, materials, compositions, and/or dosage forms which are, within the scope of sound medical judgement, suitable for use in contact with the tissues of a subject (e.g., human) without excessive toxicity, irritation, allergic response, or other problem or complication, commensurate with a reasonable benefit/risk ratio. Each carrier, excipient, etc. must also be "acceptable" in the sense of being compatible with the other ingredients of the formulation.
Suitable carriers, excipients, etc. can be found in standard pharmaceutical texts, for example, Remington's Pharmaceutical Sciences, 18th edition, Mack Publishing Company, Easton, Pa., 1990.
The formulations may conveniently be presented in unit dosage form and may be prepared by any methods well-known in the art of pharmacy. Such methods include the step of bringing the active compound into association with a carrier, which may constitute one or more accessory ingredients. In general, the formulations are prepared by uniformly and intimately bringing into association the active compound with liquid carriers or finely divided solid carriers or both, and then if necessary shaping the product.
Formulations may be in the form of liquids, solutions, suspensions, emulsions, elixirs, syrups, tablets, lozenges, granules, powders, capsules, cachets, pills, ampoules, suppositories, pessaries, ointments, gels, pastes, creams, sprays, mists, foams, lotions, oils, boluses, electuaries, or aerosols.
The inhibitor(s) or pharmaceutical composition comprising the inhibitor(s) may be administered to a subject by any convenient route of administration, whether systemically/ peripherally or at the site of desired action, including but not limited to, oral (e.g. by ingestion); topical (including e.g. transdermal, intranasal, ocular, buccal, and sublingual); pulmonary (e.g. by inhalation or insufflation therapy using, e.g. an aerosol, e.g. through mouth or nose); rectal; vaginal; parenteral, for example, by injection, including subcutaneous, intradermal, intramuscular, intravenous, intraarterial, intracardiac, intrathecal, intraspinal, intracapsular, subcapsular, intraorbital, intraperitoneal, intratracheal, subcuticular, intraarticular, subarachnoid, and intrasternal; by implant of a depot, for example, subcutaneously or intramuscularly.
Formulations suitable for oral administration (e.g., by ingestion) may be presented as discrete units such as capsules, cachets or tablets, each containing a predetermined amount of the active compound; as a powder or granules; as a solution or suspension in an aqueous or non-aqueous liquid; or as an oil-in-water liquid emulsion or a water-in-oil liquid emulsion; as a bolus; as an electuary; or as a paste.
A tablet may be made by conventional means, e.g., compression or moulding, optionally with one or more accessory ingredients. Compressed tablets may be prepared by compressing in a suitable machine the active compound in a free- flowing form such as a powder or granules, optionally mixed with one or more binders (e.g., povidone, gelatin, acacia, sorbitol, tragacanth, hydroxypropyl methyl cellulose); fillers or diluents (e.g., lactose, microcrystalline cellulose, calcium hydrogen phosphate); lubricants (e.g., magnesium stearate, talc, silica);
disintegrants (e.g., sodium starch glycolate, cross-linked povidone, cross-linked sodium carboxymethyl cellulose); surface-active or dispersing or wetting agents (e.g., sodium lauryl sulfate); and preservatives (e.g., methyl p-hydroxybenzoate, propyl p-hydroxybenzoate, sorbic acid). Moulded tablets may be made by moulding in a suitable machine a mixture of the powdered compound moistened with an inert liquid diluent. The tablets may optionally be coated or scored and may be formulated so as to provide slow or controlled release of the active compound therein using, for example, hydroxypropyl methyl cellulose in varying proportions to provide the desired release profile. Tablets may optionally be provided with an enteric coating, to provide release in parts of the gut other than the stomach.
Formulations suitable for parenteral administration (e.g. by injection, including cutaneous, subcutaneous, intramuscular, intravenous and intradermal), include aqueous and non-aqueous isotonic, pyrogen-free, sterile injection solutions which may contain anti-oxidants, buffers, preservatives, stabilisers, bacteriostats, and solutes which render the formulation isotonic with the blood of the intended recipient; and aqueous and non-aqueous sterile suspensions which may include suspending agents and thickening agents, and liposomes or other microparticulate systems which are designed to target the compound to blood components or one or more organs. Examples of suitable isotonic vehicles for use in such
formulations include Sodium Chloride Injection, Ringer's Solution, or Lactated Ringer's Injection. Typically, the concentration of the active compound in the solution is from about 1 ng/ml to about 10 μg ml, for example, from about 10 ng/ml to about 1 μg/ml. The formulations may be presented in unit-dose or multi-dose sealed containers, for example, ampoules and vials, and may be stored in a freeze-dried (lyophilised) condition requiring only the addition of the sterile liquid carrier, for example water for injections, immediately prior to use.
Extemporaneous injection solutions and suspensions may be prepared from sterile powders, granules, and tablets. Formulations may be in the form of liposomes or other microparticulate systems which are designed to target the active compound to blood components or one or more organs.
It will be appreciated that appropriate dosages of the active compounds, and compositions comprising the active compounds, can vary from patient to patient. Determining the optimal dosage will generally involve the balancing of the level of therapeutic benefit against any risk or deleterious side effects of the treatments of the present invention. The selected dosage level will depend on a variety of factors including, but not limited to, the activity of the particular compound, the route of administration, the time of administration, the rate of excretion of the compound, the duration of the treatment, other drugs, compounds, and/or materials used in combination, and the age, sex, weight, condition, general health, and prior medical history of the patient. The amount of compound and route of administration will ultimately be at the discretion of the physician, although generally the dosage will be to achieve local concentrations at the site of action which achieve the desired effect without causing substantial harmful or deleterious side-effects.
Administration in vivo can be effected in one dose, continuously or intermittently (e.g., in divided doses at appropriate intervals) throughout the course of treatment. Methods of determining the most effective means and dosage of administration are well known to those of skill in the art and will vary with the formulation used for therapy, the purpose of the therapy, the target cell being treated, and the subject being treated. Single or multiple administrations can be carried out with the dose level and pattern being selected by the treating physician.
In general, a suitable dose of the active compound is in the range of about 100 μg to about 250 mg per kilogram body weight of the subject per day. Where the active compound is a salt, an ester, prodrug, or the like, the amount administered is calculated on the basis of the parent compound and so the actual weight to be used is increased proportionately.
All documents mentioned in this specification and the sequences and other contents of database entries recited in this specification are hereby incorporated herein by reference. Having now generally described the invention, the same will be more readily understood through reference to the following examples, which are provided by way of illustration, and are not intended to be limiting of the present invention, unless specified.
EXAMPLES
A cross tumor-type panel of 95 cell lines (KU95 panel) was tested for sensitivity to olaparib. Baseline (untreated) gene expression profiles were generated using Affymetrix genome-wide U133A 2.0 arrays for each cell line. Current state-of-the- art has suggested that sensitivity to PARP inhibitors can be correlated with high levels of PARP expression (WO 2008/147418, US2007/0292883 and
US2008/0262062 - BiPAR Sciences Inc.) or deficiencies in genes involved in Homologous recombination repair (WO2005/012524 -The University of Sheffield and WO 2005053662 - Institute of Cancer Research and KuDOS Pharmaceuticals Ltd.). To determine how effective these biomarkers are at predicting response to olaparib, directed RT-PCR and protein expression analysis of PARP-1 and a number of HR genes (BRCA1 , BRCA2, ATM, ATR, CHEK2, MDC1 and MRE1 1 A) was carried out for each one of the 95 cancer cell lines. In addition, an
assessment of novel HR-associated genes that might represent predictive biomarkers for PARP-inhibitor sensitivity was also carried out using both proteomic and genomic methodologies to assess differential gene expression in isogenic cell lines in which a number of HR genes had been stably suppressed by shRNA. The results of this extended HR gene analysis was then cross-referenced with the basal Affymetrix data using statistical, bioinformatics and pathway analysis approaches to identify genes that are predictive for olaparib response.
Example 1 : Analysis of 95 cancer cell lines (KU95 panel) for their response to olaparib
A panel of 95 cancer cell lines representing six tumour types (Breast, Ovarian, Colorectal, Head and Neck, Non-small cell lung and Pancreatic) were assessed for their response to single agent olaparib using long-term 2-D colony-formation assays (CFA; clonogenic) with continual exposure to the drug. General tissue culture lab practices were employed throughout. Each cell line was plated at an appropriate pre-determined concentration (-150-200 colonies/well in vehicle alone wells) into three 6-well plates and allowed to attach overnight. Olaparib was added to triplicate wells at 0 (vehicle alone), 0.123, 0.370, 1 .1 1 1 , 3.333, 10 μΜ
concentrations (in 0.1 % DMSO vehicle) and cells incubated for 6 to 28 days, depending on the growth rate of the cell line. Surviving cell colonies were visualised by staining with standard Giemsa histological stain and colony numbers per well counted using ColCount automated colony counter and ColCount analysis software (Oxford instruments Ltd, Oxford, UK). Cellular IC5o values were
determined for each cell line using Microsoft Excel 2003 and ID-BS XLFit (v4.2.2) charting application. Percentage cell survival (number colonies with olaparib / number colonies in vehicle x 100%) was determined for each olaparib
concentration. Cellular IC5o values were calculated using a dose response curve plotted using XLFit, set with the curve fit 4 Parameter Logistic Model (IDBS XLFit model 205) for each cell line.
The baseline mRNA expression levels of HR factors (ATM, ATR, BRCA1 , BRCA2, CHEK2, MDC1 and MRE1 1A), PARP-1 (a BER factor) and ABCB1 (a drug transporter gene) were determined for each cell line in the KU95 cell line panel (see Table 4). Exponentially growing cell lines were grown in 15 cm dishes then washed in ice-cold Ca/Mg-free PBS (Invitrogen), scraped into centrifuge tubes and cells pelleted at 300 x g at a temperature of 4°C for 2 minutes. Supernatants were discarded and cell pellets snap frozen in LN2 and stored at -80°C until use. Total RNA was extracted from each cell pellet using silica and guanidinium thiocyanate based purification method described by Boom et al (Boom et al. J Clin Micobiol 28:495-503, 1990) in the form of the commercial RNeasy total RNA mini extraction kit from Qiagen. RNA was quantified using standard UV spectrophotometry methods. Total cDNA was prepared according to standard DNase, reverse trancriptase and oligo-dT / random primer methods using the commercial Quantitect Reverse Transcription Kit from Qiagen. Quantitative real-time PCR was performed using well established commercial TaqMan gene expression primer assays and master mix (Applied Biosystems) utilising FAM- MGB fluorescent dye-labelled probes and detection on a StepOnePlus real-time PCR system (Applied Biosystems). Normalised gene expression of ATM, ATR, BRCA1 , BRCA2, CHEK2, MDC1 , MRE1 1 A, PARP-1 and ABCB1 relative to the average of 3 endogenous control genes (PPIA, PGK1 , TBP) was calculated (ACT) for each cell line. Relative gene expression across all 95 cell lines was calculated using 2_AACT method as described previously (Livak and Schmittgen Methods 25:402-408, 2001 ).
The baseline protein expression levels of ATM, ATR, CHEK2, MDC1 , MRE1 1A and PARP-1 were determined for each cell line in the KU95 cell line panel using western blotting with commercially available antibodies and densitometry quantification. Total protein concentration for each extract was determined using the well-known reduction of Cu2+ to Cu1+ bicinchoninic acid (BCA) method in the form of commercial BCA Protein Assay Reagent kit from Pierce. Primary antibodies were diluted to an appropriate concentration in MTBS-T buffer (5% skimmed milk powder, 0.05% Tween- 20 in Tris-buffered saline (TBS)) and incubated with the membranes for 2.5 hours at room temperature. Proteins were detected using standard electrochemiluminescent (ECL) reagent methods. Images and protein band intensity were quantified on a LAS- 3000 luminescent image analyser and associated AIDA software (Fujifilm).
Normalised protein expression of ATM, ATR, CHEK2, MDC1 , MREHA or PARP-1 compared to β-actin endogenous control protein was calculated for each cell line.
The term "sensitive" in the context of this Example refers to those cancer cell lines in the KU95 panel that have an IC50 value of less than 1 μΜ. 1 uM has been found by the applicant to be a pharmacologically relevant concentration for which tumour exposure has been demonstrated for tolerable doses of olaparib in a phase 1 biopsy study clinical trial in man.
The term "resistant" in the context of this Example refers to those cancer cell lines in the KU95 panel that have an IC50 value of more than 4 μΜ, which is the concentration just above that achieved in any sample within the phase 1 biopsy trial referred to above.
Table 4 lists the KU95 panel of cancer cell lines analysed along with their olaparib IC50 data as determined by 2D-colony formation assays. HR gene mutation (black boxes) and the experimentally-determined gene expression levels of PARP-1 and the HR genes ATM, ATR, CHEK2, MDC1 , MRE1 1 A or PARP-1 (relative expression less than 50% in black). The black boxes in the IC50 column indicate cell lines that demonstrated significant sensitivity to olaparib with IC50 values less than 1 .0 μΜ (clinically achievable doses). The grey boxes represent cell lines with olaparib sensitivity between 1 .0 and 1 .2 μΜ.
Table 4
Figure imgf000066_0001
Figure imgf000067_0001
Figure imgf000068_0001
Figure imgf000069_0001
Figure imgf000070_0001
bank
Olaparib IC50 was determined by 2D-colony formation assays. HR gene mutation data were obtained from literature or online public databases. Quantification of mRNA for HR genes (ATM, ATR, BRCA1 , BRCA2, CHEK2, MRE1 1A, MDC1 ), ABCB1 (P-gp drug transporter) and PARP-1 were determined by Taqman RT- PCR and relative expression levels (to mean of KU95 cell panel) calculated using 2-ΔΔΟΤ method. HR gene expression was classified as low if relative mRNA levels were less than 50%. PARP-1 BER gene expression was classified as low if relative mRNA levels less than 50% or classified as high if relative mRNA levels were greater than 200%. ABCB1 gene expression was classified as low if relative mRNA expression levels were up to 100%, moderate if relative expression between 100% and 200% or high if greater than 200%. Of note a number of cell lines that demonstrated high PARP-1 expression levels (e.g. BT474, HCC-38) were not sensitive to olaparib.
Figure 1 shows plots of both PARP-1 gene and protein expression levels against cell line IC50 data. Surprisingly, in contrast to previous suggestions that higher levels of PARP-1 can be used to predict response to PARP inhibitors, the data in Figure 1 clearly show that higher levels of PARP cannot distinguish between those cell lines that are responsive to olaparib and those that are not. In contrast, these data do demonstrate that there are hardly any cell lines with low levels of PARP-1 expression that are sensitive to olaparib (see lower left quadrant), indicating that low levels of PARP-1 may be a useful biomarker to exclude those cancer cells unlikely to respond to PARP inhibition. Using PARP-1 expression levels as a biomarker provided significant predictive value (p= 0.005) in this study.
Analysis of core HR gene expression correlated well with response to olaparib and data for BRCA1 are shown in Figure 2. These and other HR biomarkers provided significant predictive value for olaparib sensitivity (e.g. BRCA1 p= 0.035).
Individual exceptions were observed where HR deficiency did not correlate with response and in these cases the cell line's resistance was thought to be due to either low PARP-1 levels or high P-gp levels (the product of the ABCB1 gene and olaparib being a substrate for this drug transporter).
Based on these data an assessment was made of whether the combination of PARP-1 and a HR deficiency (HRD) was of greater predictive value than either of these biomarkers alone. Figure 3 indicates that this is the case and together these data provide a clear improvement on the predictive value of previous information claiming high PARP-1 levels or HRD alone as markers of PARP inhibitor response.
Example 2: Analysis of HR deficiencies in different tumour types
BRCA deficiencies are notably associated with breast and ovarian cancers but not all cancers, raising the possibility that different HR deficiencies may be more common in some tumour types than others. Consistent with this idea are the observations that up to 50% of head and neck cancers are associated with chromosome 1 1 q deletions that remove the ATM gene (Parikh et al. Genes Chromosomes & Cancer 46:761-775, 2007) and 30% of non-small cell lung cancers that are associated with MDC1 deficiencies (Bartkova et al. Oncogene 26:7414-7422, 2007).
To address this, the correlation of PARP-1 and HRD with response to olaparib in breast cancer, colorectal cancer and gastric cancer cell lines was analysed and the data are provided in Tables 5, 6 and 7 respectively. Table 5 shows PARP and HR biomarker correlation with breast cancer cell line response to olaparib. Quantification of mRNA for HR genes (ATM, ATR, BRCA1 , BRCA2, CHEK2, MRE1 1A, MDC1 ) and PARP-1 were determined by Taqman RT- PCR and relative expression levels (to mean of breast cell panel) calculated using 2-ΔΔΟΤ method. Relative HR gene expression levels are shown as less that 50% (- 2; black), between 50% and 67% (-0.5), between 67% and 150% (0), between 150% and 200% (0.5) and greater than 200% (2). HR gene expression was classified as low if relative mRNA levels were less than 50% (-2). Relative PARP- 1 gene expression is shown as either low (less than 50%; grey) or high (greater than 200%).
PARP-1
Olaparib BRCA mRNA
Cell Line HR mRNA expression levels
IC50 mutation expression Name
(μΜ) status levels
Low (grey) =
Black = -2 (black) = less than 50% expression (low expression) less than <1.0 μΜ -.5 = between 50% and 61% expression 50% Grey = 0 = between 61% and 150%o expression expression 1.0-1.2 0.5 = between 50%o and 150%o expression High = μΜ 2 = greater than 200%o expression greater
expression
Figure imgf000073_0001
Table 6 shows PARP and HR biomarker correlation with colorectal cancer cell line response to olaparib. PARP inhibitor (olaparib) IC50 was determined by 2D- colony formation assays. Microsatelite instability (MSI) status and MRE1 1 A gene mutation data were obtained from literature or online public databases.
Quantification of mRNA for HR genes (ATM, ATR, BRCA1 , BRCA2, CHEK2, MRE1 1A, MDC1 ) and PARP-1 were determined by Taqman RT-PCR and relative expression levels (to mean of colorectal cell panel) calculated using 2~AACT method. HR gene expression was classified as low (black boxes) if relative mRNA levels were less than 50%. ABCB1 (P-gp drug transporter) gene expression was classified as low if relative mRNA expression levels were up to 100%, moderate if relative expression between 100% and 200% or high if greater than 200% (grey).
Figure imgf000073_0002
Figure imgf000074_0001
Table 7 shows PARP and HR biomarker correlation with gastric cancer cell line response to olaparib. (A) PARP inhibitor (olaparib) IC50 was deternnined by 2D- colony formation assays. The black boxes indicate cell lines that demonstrated sensitivity to olaparib with IC50 values less than 1 .0 μΜ. The grey boxes represent cell lines with olaparib sensitivity between 1 .0 and 1 .2 μΜ. ATM gene mutation data were obtained from literature or online public databases. Cell lines with DNA mutations are shown in grey. ATM and PARP-1 protein expression was
determined by western blotting and densitometry. Expression was classified as low (black boxes) if relative protein levels (to mean of gastric cell panel) were less than 50%.
Figure imgf000074_0002
NUGC3 1.472 PARP high
PHM83 1.532 PARP high
SGC-7901 1.887
M N-74 2.262
GTL16 2.548
MGC803 2.624
MKN-1 3.178
PAMC82 3.812
SNU216 5.243
M N-45 15.75 ATM low PAR low
For the gastric cancer lines, analysis was carried out according to the clonogenic assay methods described above.
Protein expression analysis was performed using the methods outlined above in Example 1 using antibodies against ATM, ATR, MDC1 , MRE1 1 A and PARP-1 . A striking correlation was observed between the most sensitive gastric cancer cell lines and ATM expression levels (Table 7). Expression levels of ATM were termed low when less than 50% expression was observed relative to the mean ATM expression of the gastric cell line panel.
The analysis of gastric cancer cell lines was complemented by ATM
Immunohistochemistry (IHC) using the following method.
IHC staining for ATM was performed using 4μηη formalin fixed paraffin wax embedded (FFPE) sections of human tissue (mounted on slides) and microscopic interpretation. Slides were heated at 60°C for 30 min then rehydrated by sequential immersion in Xylene (Standard laboratory grade; 2 changes, 10 min each), alcohol (Industrial methylated, iso-propyl alcohol; 2 changes, 5 min each), 70% v/v alcohol in pure water (5 min) and in running tap water for 5 min. Target antigen retrieval was performed using 1 X target retrieval solution pH 9 (DAKO S2367) in a boiling domestic pressure cooker for 5 minutes. ATM staining was run using a Labvision automated IHC autostainer using the following incubation programme: Rinse slides in wash buffer (DAKO S3306), Peroxidase blocking solution (DAKO S2001 ) 5 min, wash slides in wash buffer twice, Protein blocking solution (DAKO X0909) 5min, Blow off, primary ATM antibody (Epitomics 1549-1 ) in diluent (DAKO S0809) 60min, wash slides in wash buffer twice, HRP labelled rabbit/mouse polymer (DAKO K5007) 30min, wash slides in wash buffer twice, Diaminobenzidene solution (DAKO K3468) 10min and wash slides in water. For negative control sections the ATM antibody was replaced with negative control rabbit IgG (DAKO X0903). Slides were removed from the autostainer and stained with Mayer's haematoxylin (DAKO S3309). Slides were dehydrated slides by sequential immersion in 95% v/v alcohol in pure water (5 min), 100% alcohol (2 changes, 5 min each), Xylene (2 changes, 5 min each) and then mounted in resinous mountant. Stained sample IHC sections were interpreted and scored using the following criteria. For each sample set the negative control sections were first examined and if specific nuclear or cytoplasmic staining was present or general staining is of moderate or of strong intensity then interpretation of the ATM stained section was not be attempted. If negative control sections were confirmed to either be unstained or show general weak diffuse staining then ATM stained sections were examined. For ATM stained samples morphological integrity and intensity of diffuse staining was determined. If the morphology was acceptable and diffuse staining is either weak or absent, the presence of lymphocytes was determined. If present, these should show moderate to strong nuclear staining but if they were unstained or weakly stained then the section was not interpreted. If lymphocyte staining was acceptable then the tumour cells were identified and the presence or absence of nuclear staining and its intensity scored as:
Negative 0% tumour cells,
Positive/Negative +/- % tumour cells
Weak + % tumour cells
Moderate ++ % tumour cells
Strong +++ % tumour cells
The data from this analysis are presented in Table 8 and show that 22% of the 1 1 1 gastric cancer clinical samples assessed stained negative for ATM using a tissue microarray. Table 8 shows ATM protein expression level analysis by immunohistochemistry (IHC) on tumour and adjacent normal tissue samples from Chinese gastric cancer patients.
Figure imgf000077_0001
Together, these data provide evidence that breast cancer deficiencies in MDC1 , CHEK2, ATM, ATR, BRCA1 and to a lesser extent BRCA2 are observed in sensitive cell lines. In colorectal cancer, the HR deficiencies observed were MRE1 1 A and ATM while in gastric cancers only ATM deficiencies were associated with olaparib sensitivity. These data therefore suggest that different HR
deficiencies may be more commonly associated with particular tumour types.
Example 3: Expansion of the HR-associated gene list
Previously published work has highlighted the link between HRD and PARP inhibitor response. However, our understanding of what constitutes an HR- associated gene is primarily limited to those genes with an already well-defined function within this repair pathway. HRD could conceivably result from gene deficiencies not currently linked to HR function but that nevertheless would have potential utility as biomarkers for PARP inhibitor response. To increase our understanding of HR-associated genes both proteomic and genomic analyses was performed on a number of isogenic cell lines in which expression of one of six HR genes BRCA1 , BRCA2, ATM, MRE1 1 A, NBN (NBN) or CHEK2 have been stably knocked-down through an established RNAi approach. RNAi expression vectors were created for each of the HR knockdown clones using the pSilencer 3.1 -H1 neo vector and RNAi knockdown system (Ambion/Applied biosystems). The RNAi target sequences for each HR gene clone was inserted into the pSilencer 3.1 -H1 neo vector between the BamHI and Hind 111 restriction enzyme sites according to the manufacturers' recommended conditions. Nonspecific (NS) negative control constructs acting as controls were also generated from standard non-coding sequences (Ambion/Applied Biosystems). The CAL51 breast cell line was transfected with each HR gene RNAi expression vector or nonspecific control vector using the Lipofectamine-2000 lipid transfection reagent (Invitrogen) according to the manufacturers' recommendation instructions.
Transfected cells were plated out into multiple dishes and incubated in RPMI1640 + 10% foetal bovine serum (FBS) media containing 300 g/ml Geneticin
(Invitrogen) for 14 days. Surviving stable cell colonies were taken and tested to determine the level of residual target gene protein expression by western blot analysis (as previously described) in comparison with the parental HR-proficient non-transfected cell line (CAL51 WT). In several cases multiple knockdown cell line clones per individual HR gene were obtained. The HR RNAi cell lines, level of gene knockdown, residual gene expression and the RNAi targeting sequences used are shown in Table 9.
Table 9. Level of HR gene expression in RNAi knockdown cell lines and targeting sequences used.
Level of Level of
target residual target
protein protein
knockdown expression
HR gene (% (% expression Target gene sequence used in
Knockdown expression relative to RNAi vectors
(designation) relative to parental HR- parental HR- proficient
proficient CAL51 WT)
CAL51 WT)
ATM 91 % 9% 5'- TAG AG CTACAG AACG AAAG -3' (clone 1-5) SEQ ID NO: 1
CHEK2 85% 15% 5'- G AACCTG AG G ACCAAG AAC -3' (clone 2-4) SEQ ID NO: 2
CHEK2 92% 8% 5'- G AACCTG AG G ACCAAG AAC -3' (clone 2-6) SEQ ID NO: 2
MRE1 1A 64% 36% 5'- GATGCCATTGAGGAATTAG -3' (clone 3-2) SEQ ID NO: 3
MRE1 1A 82% 72% 5'- GATGCCATTGAGGAATTAG -3' (clone 3-5) SEQ ID NO: 3
NBN 63% 37% 5'- GGCGTGTCAGTTGATGAAA -3' (clone 2-3) SEQ ID NO: 4
NBN 50% 50% 5'- GGCGTGTCAGTTGATGAAA -3' (clone 2-5) SEQ ID NO: 4
BRCA1 67% 33% 5'- GCTACAGAAACCGTGCCAA -3' (clone 4) SEQ ID NO: 5
BRCA1 79% 21 % 5'- GCTACAGAAACCGTGCCAA -3' (clone 7) SEQ ID NO: 5
BRCA1 87% 13% 5'- GCTACAGAAACCGTGCCAA -3' (clone 8) SEQ ID NO: 5
BRCA1 89% 1 1 % 5'- GCTACAGAAACCGTGCCAA -3' (clone 12) SEQ ID NO: 5
Proteomic identification of differentially expressed proteins for each HRD knockdown cell line compared to HR-proficient control cells were undertaken using two-dimensional difference gel electrophoresis (2D-DIGE) method (Gharbi et al 2002). Proteomic profiles for each HRD knockdown cell lines were compared with their wild type (CAL51 WT) or non-specific control (CAL51 NS control) cells. For each cell line either nuclear protein extraction or phospho-protein enrichment was performed to reduce protein complexity and aid data analysis. Standard nuclear protein enrichment method was used involving the gentle lysis of the cells by repeated freeze/thawing in a Hypotonic buffer. A high salt buffer was then added and the samples underwent centrifugation to pellet the nuclear fraction. The supernatant containing the cytoplasmic fraction was removed and the nuclear pellet resuspended in the proteomics lysis buffer (Gharbi et al., Mol. Cell.
Proteomics. 1 : 91-98, 2002). This then underwent further centrifugation to pellet insoluble cell debris, the supernatant was taken as the nuclear enriched extract. Protein enrichment was performed using the Qiagen Phospho Protein Purification Kit (Qiagen, Crawley, West Sussex) as per their instructions (Puente et al. FEBS Lett.574; 138-44, 2004).
The two-dimensional difference gel electrophoresis (2D-DIGE) method used was peformed essentially as previously described (Gharbi et al., Mol. Cell. Proteomics. 1 : 91-98, 2002). 200pmol of CyDye fluor were used to label 50pg of protein, samples were IEF focussed on 24cm pH4-7 IEF strips using an IPGphor II with an IPGphor manifold (GE healthcare, Little Chalfont, Bucks) at 20°C, δΟμΑ/strip. Focussing conditions were 300V for3hrs, then increased in a linear gradient to 1 000V over the following 6 hours, then increased to 8000V again in a l inear gradient over 3 hours and finally continued at 8000V for a further 4 hours and 40 minutes. Total volt hours were approximately 55000 hours. IEF focussed strips were run in the 2nd dimension on 26cm X 21 cm format 10-20% gradient gels. The gels were run overnight on an Ettan Dalt II system (GE healthcare, Little Chalfont, Bucks). Running conditions were 5W/gel for the first 15-60 minutes, then 1 - 1 .5W/gel overnight at 25°C until the dye front ran off the bottom of the gel.
In all the studies the desired result were protein spots with a significant difference in abundance between the specific HRD knockdown cell lines compared to the HR-proficient controls (wild type or non-specific). A significant difference was classed as a fold change in abundance above or below set criteria (Table 10) and a P va l u e (t-test) less than or equal to a set cut-off. The supervised and unsupervised statistical analysis tools in the DeCyder™ EDA and BVA software system (GE healthcare, Little Chalfont, Bucks) were utilised to select protein spots of interest meeting the criteria specified for each HR RNAi cell line DIGE study. The selected spots were then selected to undergo protein identification by mass spectrometry to determine if there were significant differences in abundance between specific HR gene KDs and control cell lines. Protein IDs for each protein spot of interest was determined as follows. Preparative 2D gels loaded with 500- 1 000 g protein/gel were run and subsequently fixed and stained with an appropriate fluorescent stain (Sypro Ruby or Deep Purple Total Protein Stain [GE healthcare, Little Chalfont, Bucks]). These preparative gels were then scanned and spots matched to those previously identified as those containing proteins of interest. These were then selected for processing and identification by mass spectrometry using peptide mass fingerprinting and protein sequencing.
Table 10. Fold change and p value cut offs used for selection of protein spots of interest for each KD cell line study
Cell Comparison type P value cut off Fold change cut Additional
Line/KD off selection
conditions
The fold change for KD vs WT and Scrambled control must both be either positive (+) or
negative (-)
MCF7 BRCA1 KD vs WT P <0.005 Fold change >1.3
BRCA1 BRCA1 KD vs P <0.005 (+/-)
KD scrambled control Fold change >1.8
(+/-)
or > 1.3 (+/-) for
high abundance
spots
CAL51 BRCA2 KD vs WT P <0.05 Fold change >1.3
BRCA2 BRCA2 KD vs NonP <0.05 (+/-)
specific (NS) control Fold change >1.3
(+/-)
CAL51 ATM KD vs WT P <0.05 Fold change >1.5 These criteria ATM ATM KD vs NonP <0.05 (+/-) must be met (clone 5) specific (NS) control Fold change >1.5 between
(+/-) controls and all individual clones
CAL51 CHEK2 KD vs WT P <0.05 Fold change >1.3 These criteria CHEK2 CHEK2 KD vs NonP <0.05 (+/-) must be met (clone 4 & specific (NS) control Fold change >1.3 between
6) (+/-) controls and all individual clones
CAL51 MRE1 1A KD vs WT P <0.05 Fold change >1.3 These criteria
MRE1 1A MRE1 1A KD vs P <0.05 (+/-) must be met
(clone 2 & Non-specific (NS) Fold change >1.3 between
5) control (+/-) controls and all individual clones
CAL51 MRE1 1A KD vs WT P <0.05 Fold change >1.3 These criteria
NBN MRE1 1A KD vs P <0.05 (+/-) must be met
(clone 2-3 Non-specific (NS) Fold change >1.3 between
& 2-5) control (+/-) controls and all individual clones
CAL51 BRCA1 KD vs WT P <0.05 Fold change >1.3 These criteria
BRCA1 BRCA1 KD vs NonP <0.05 (+/-) must be met
(clones 4, specific (NS) control Fold change >1.3 between
7, 8 & 12) (+/-) controls and all individual clones
Results from these analyses were cross-compared with those from a gene expression analysis of the cell lines along with pertinent data from other sources.
Identification of differentially expressed genes at the mRNA level for each HRD knockdown cell line was undertaken using Affymetrix array analysis using the method described below.
We compared the basal (untreated) differentially regulated gene expression (DEG) profiles between the parental HR-proficient line and the HRD knock down lines using 1 -way ANOVA and contrast analysis. Genes were selected showing FC>2 (or <-2) and P<0.01 in individual KD models (consistent across repeats for same gene knockdown), or FC>1 .3 (or <-1 .3) and P<0.05 consistent across multiple KD models. From these studies we identified a total of 498 genes (190 ranked with top priority) that were differentially expressed in the engineered HRD cell lines compared to the parental wild type control. The list of HR-associated genes is provided in Table 1 1 .
Further to this, an additional list of candidate mRNA markers of HR and BER signalling were generated from published data. Using PubMed
(www.ncbi.nlm.nih.gov/pubmed/), Oncomine (www.oncomine.com/) and GEO (www.ncbi.nlm.nih.gov/geo/), journal publications were identified disclosing genelists representing mRNA expression changes following dynamic activation or inhibition of core BER (PARP-1 ) or HR (BRCA1 , BRCA2, ATM, ATR, MRE1 1 A, CHEK2 or MDC1 ) genes, listed here by PubMed ID:
- BER: 1959195; 1959195; 18412984; 18412984; 16740713; 12729565;
1430828; 1986628; 1 1016956; 1 1016956; 14762203; 12379459
- HR: 10835497; 1 1207349; 1 1506493; 1 1709053; 1 1823860; 1 1823860;
12024039; 12096075; 12096084; 12096085; 12096086; 12162889; 12610208; 12829800; 12958068; 14745549; 14871973; 14978791 ; 15094373; 15868446; 16258266; 16280042; 16461462; 16818684; 16921376; 16998498; 17001622; 17043641 ; 17428335; 17487278; 17699107; 18071589; 18497862; 18563556; 18593983
Where possible related data was retrieved and resulting signatures were compared and contrasted to highlight genes whose mRNA expression consistently changed following pathway perturbation.
Knowledge mining [including application of text mining approaches
(www.linguamatics.com/; www.quosa.com/; www.medline.cos.com/) and Ingenuity Pathways Analysis (Ingenuity® Systems, www.ingenuity.com)] was also performed, collating published knowledge of gene and protein interactions with HR and BER pathway signalling. Genes were prioritised base on the number of publications supporting a role in HR/BER signalling, particularly where evidence suggested downstream mRNA expression.
Table 11 shows the expanded list of 498 HR genes identified through proteomic and genomic analysis of isogenic cancer cell lines with HR deficiencies.
Differentially expressed genes (DEGs) between Core HR knockdown and isogenic wild-type cell lines as discovered through 2D-DIGE proteomics and Affymet gene expression array analysis.
Figure imgf000084_0001
Figure imgf000085_0001
CRTAP cartilage associated protein 10491 1
CS citrate synthase 1431 1 catenin (cadherin-associated protein),
CTNNA1 1495
alpha 1, 102kDa 1
CTSD cathepsin D 1509 1
CWC15 spliceosome-associated
CWC15 51503
protein homolog (S. cerevisiae) 1 diazepam binding inhibitor (GABA
DBI receptor modulator, acyl-Coenzyme A 1622
binding protein)
dodecenoyl-Coenzyme A delta
DCI isomerase (3,2 trans-enoyl-Coenzyme 1632
A isomerase)
DEAD (Asp-Glu-Ala-Asp) box
DDX5 1655
polypeptide 5 1
DEAD (Asp-Glu-Ala-Asp) box
DDX39 10212
polypeptide 39 1
DEAD (Asp-Glu-Ala-Asp) box
DDX3X 1654
polypeptide 3, X-linked 1 dihydrolipoamide S-
DLST succinyltransferase (E2 component of 1743
2-oxo-glutarate complex)
DnaJ (Hsp40) homolog, subfamily A,
DNAJA2 10294
member 2 1
DnaJ (Hsp40) homolog, subfamily B,
DNAJB11 51726
member 11 1
DnaJ (Hsp40) homolog, subfamily C,
DNAJC3 5611
member 3 1
DnaJ (Hsp40) homolog, subfamily C,
DNAJC9 23234
member 9 1
DnaJ (Hsp40) homolog, subfamily C,
DNAJC14 85406
member 14 1
DNM1L dynamin 1 -like 10059 1
DPYSL2 dihydropyrimidinase-like 2 1808 1
DSTN destrin (actin depolymerizing factor) 11034 1 dynein, cytoplasmic 1, intermediate
DYNC1I2 1781
chain 2 1 enoyl Coenzyme A hydratase 1,
ECH1 1891
peroxisomal 1 enoyl Coenzyme A hydratase, short
ECHS1 1892
chain, 1, mitochondrial 1 eukaryotic translation elongation
EEF1A1 1915
factor 1 alpha 1 1 eukaryotic translation elongation
EEF1D factor 1 delta (guanine nucleotide 1936
exchange protein)
EFHD1 EF-hand domain family, member Dl 80303 1 eukaryotic translation initiation factor
EIF2S2 8894
2, subunit 2 beta, 38kDa 1 eukaryotic translation initiation factor
EIF4A1 1973
4A, isoform 1 1 eukaryotic translation initiation factor
EIF4E 1977
4E 1 eukaryotic translation initiation factor
EIF4H 7458
4H 1
ENOl enolase 1, (alpha) 2023 1
Figure imgf000087_0001
Figure imgf000088_0001
Figure imgf000089_0001
Figure imgf000090_0001
Figure imgf000091_0001
membrane 8 homolog A (yeast)
translocase of outer mitochondrial
TOMM70A membrane 70 homolog A (S. 9868 1
cerevisiae)
TOR1AIP1 torsin A interacting protein 1 26092 1
TPD52 tumor protein D52 7163 1
TPD52L2 tumor protein D52-like 2 7165 1
TPI1 triosephosphate isomerase 1 7167 1
TPM1 tropomyosin 1 (alpha) 7168 1
TPM2 tropomyosin 2 (beta) 7169 1
TPM3 tropomyosin 3 7170 1
transformer 2 alpha homolog
TRA2A 29896
(Drosophila) 1
TRAPPC4 trafficking protein particle complex 4 51399 1
TSFM (includes Ts translation elongation factor,
10102
EG: 10102) mitochondrial 1
TSG101 tumor susceptibility gene 101 7251 1
TUBA 1 A tubulin, alpha la 7846 1
TUBA IB tubulin, alpha lb 10376 1
TUBA1C tubulin, alpha lc 84790 1
TUBB tubulin, beta 203068 1
TUBB2C tubulin, beta 2C 10383 1
TUBG1 tubulin, gamma 1 7283 1
twinfilin, actin-binding protein,
TWF2 11344
homolog 2 (Drosophila) 1
thioredoxin domain containing 5
TXNDC5 81567
(endoplasmic reticulum) 1
U2AF2 (includes U2 small nuclear RNA auxiliary
11338
EG: 11338) factor 2 1
UBXN6 UBX domain protein 6 80700 1
ubiquitin fusion degradation 1 like
UFD1L 7353
(yeast) 1
ubiquinol-cytochrome c reductase,
UQCRFS1 7386
Rieske iron-sulfur polypeptide 1 1
VCP valosin-containing protein 7415 1
VDAC1 voltage-dependent anion channel 1 7416 1
VDAC2 voltage-dependent anion channel 2 7417 1
vacuolar protein sorting 25 homolog
VPS25 84313
(S. cerevisiae) 1
WARS tryptophanyl-tRNA synthetase 7453 1
X-prolyl aminopeptidase
XPNPEP3 63929
(aminopeptidase P) 3, putative 1
X-ray repair complementing defective
XRCC5 repair in Chinese hamster cells 5 7520
(double-strand-break rejoining)
YARS tyrosyl-tRNA synthetase 8565 1
ATP-binding cassette, sub-family C
ABCC4 10257
(CFTR/MRP), member 4 1
ATP-binding cassette, sub-family D
ABCD3 5825
(ALD), member 3 1
ADAM metallopeptidase with
ADAMTS9 56999
thrombospondin type 1 motif, 9 1
ADM adrenomedullin 133 1 anterior gradient homolog 3 (Xenopus
AGR3 155465
laevis) 1
AHNAK AHNAK nucleoprotein 79026 1
Figure imgf000093_0001
member 9
DOK4 docking protein 4 55715 1
Down syndrome cell adhesion
DSCAML1 57453
molecule like 1 1
DSE dermatan sulfate epimerase 29940 1
DSEL dermatan sulfate epimerase-like 92126 1
EBF1 early B-cell factor 1 1879 1
EGFL6 EGF-like-domain, multiple 6 25975 1 enoyl-Coenzyme A, hydratase/3-
EHHADH hydroxyacyl Coenzyme A 1962
dehydrogenase
erythrocyte membrane protein band
EPB49 2039
4.9 (dematin) 1
EYA4 eyes absent homolog 4 (Drosophila) 2070 1 fatty acid binding protein 3, muscle
FABP3 and heart (mammary-derived growth 2170
inhibitor)
FADS2 fatty acid desaturase 2 9415 1 family with sequence similarity 107,
FAM107A 11170
member A 1 family with sequence similarity 149,
FAM149A 25854
member A 1 family with sequence similarity 155,
FAM155A 728215
member A 1 family with sequence similarity 59,
FAM59A 64762
member A 1 family with sequence similarity 83,
FAM83B 222584
member B 1
FCGBP Fc fragment of IgG binding protein 8857 1
FYVE, RhoGEF and PH domain
FGD6 55785
containing 6 1
FGF2 fibroblast growth factor 2 (basic) 2247 1
FGFR2 fibroblast growth factor receptor 2 2263 1
FKBP7 FK506 binding protein 7 51661 1
FKBP14 FK506 binding protein 14, 22 kDa 55033 1 fibronectin leucine rich
FLRT3 23767
transmembrane protein 3 1
FN1 fibronectin 1 2335 1
FSTL1 follistatin-like 1 11167 1
FTH1 ferritin, heavy polypeptide 1 2495 1
FXYD domain containing ion
FXYD2 486
transport regulator 2 1
GABA(A) receptor-associated protein
GABARAPL1 23710
like 1 1 glucan (1,4-alpha-), branching
GBE1 2632
enzyme 1 1
GTP binding protein overexpressed in
GEM 2669
skeletal muscle 1
GLRB glycine receptor, beta 2743 1
GLRX glutaredoxin (thioltransferase) 2745 1 guanine nucleotide binding protein (G
GNB4 59345
protein), beta polypeptide 4 1
GPC4 glypican 4 2239 1
GPR20 G protein-coupled receptor 20 2843 1
GPR177 G protein-coupled receptor 177 79971 1
GPR137C G protein-coupled receptor 137C 283554 1
Figure imgf000095_0001
phosphodiesterase 3A, cGMP-
PDE3A 5139
inhibited 1 pyruvate dehydrogenase kinase,
PDK4 5166
isozyme 4 1
PDZK1 PDZ domain containing 1 5174 1
PER2 period homolog 2 (Drosophila) 8864 1 pleckstrin homology-like domain,
PHLDA1 22822
family A, member 1 1 pleckstrin homology-like domain,
PHLDB2 90102
family B, member 2 1
PITX2 paired-like homeodomain 2 5308 1 phospholipase C, beta 1
PLCB1 23236
(phosphoinositide-specific) 1
PLCB4 phospholipase C, beta 4 5332 1 phospholipase Dl,
PLD1 5337
phosphatidylcholine-specific 1 pleckstrin homology domain
PLEKHA6 22874
containing, family A member 6 1
POU3F3 POU class 3 homeobox 3 5455 1 peroxisome proliferator-activated
PPARG 5468
receptor gamma 1 proteasome (prosome, macropain)
PSMB10 5699
subunit, beta type, 10 1
PTGES prostaglandin E synthase 9536 1 protein tyrosine phosphatase type
PTP4A3 11156
IVA, member 3 1 poliovirus receptor-related 2
PVRL2 5819
(herpesvirus entry mediator B) 1 quaking homolog, KH domain RNA
QKI 9444
binding (mouse) 1
RAB38, member RAS oncogene
RAB38 23682
family 1
RBP1 retinol binding protein 1 , cellular 5947 1
RDH10 retinol dehydrogenase 10 (all-trans) 157506 1 reversion-inducing-cysteine-rich
RECK 8434
protein with kazal motifs 1
RHOBTB1 Rho-related BTB domain containing 1 9886 1 roundabout, axon guidance receptor,
ROB02 6092
homolog 2 (Drosophila) 1
S100A11 SI 00 calcium binding protein Al 1 6282 1 stearoyl-CoA desaturase (delta-9-
SCD 6319
desaturase) 1
SCD5 stearoyl-CoA desaturase 5 79966 1
SDC2 syndecan 2 6383 1
SELI selenoprotein I 85465 1
SEPP1 selenoprotein P, plasma, 1 6414 1 serpin peptidase inhibitor, clade B
SERPINB9 5272
(ovalbumin), member 9 1 serum/glucocorticoid regulated kinase
SGK2 10110
2 1
SH3PXD2A SH3 and PX domains 2A 9644 1
SH3 domain and tetratricopeptide
SH3TC1 54436
repeats 1 1
SLC25A43 solute carrier family 25, member 43 203427 1 solute carrier family 26 (sulfate
SLC26A2 1836
transporter), member 2 i SLC44A1 solute carrier family 44, member 1 23446 1 solute carrier family 6
SLC6A4 (neurotransmitter transporter, 6532
serotonin), member 4
solute carrier family 6
SLC6A13 (neurotransmitter transporter, GABA), 6540
member 13
SPARC related modular calcium
SMOC2 64094
binding 2 1
SOST sclerosteosis 50964 1
SSR1 signal sequence receptor, alpha 6745 1 signal sequence receptor, gamma
SSR3 (translocon-associated protein 6747
gamma)
ST3 beta-galactoside alpha-2,3-
ST3GAL5 8869
sialyltransferase 5 1 six transmembrane epithelial antigen
STEAP1 26872
of the prostate 1 1 sulfotransferase family, cytosolic, 1C,
SULT1C2 6819
member 2 1
SURF4 surfeit 4 6836 1
THBS1 thrombospondin 1 7057 1
THEM4 thioesterase superfamily member 4 117145 1 thrombospondin, type I, domain
THSD7A 221981
containing 7A 1
TICAM2 toll-like receptor adaptor molecule 2 353376 1
TINAG tubulointerstitial nephritis antigen 27283 1 tight junction protein 2 (zona
TJP2 9414
occludens 2) 1 transmembrane emp24 protein
TMED5 50999
transport domain containing 5 1 transmembrane emp24-like trafficking
TMED10 10972
protein 10 (yeast) 1
TMEM9 transmembrane protein 9 252839 1
TMEM41B transmembrane protein 41B 440026 1
TMEM50B transmembrane protein 5 OB 757 1 tumor necrosis factor receptor
TNFRSF19 55504
superfamily, member 19 1 tumor necrosis factor receptor
TNFRSFIOD superfamily, member lOd, decoy with 8793
truncated death domain
tumor necrosis factor receptor
TNFRSF11A superfamily, member 11a, NFKB 8792
activator
tankyrase, TRFl -interacting ankyrin-
TNKS2 80351
related ADP-ribose polymerase 2 1
TRIB2 nibbles homolog 2 (Drosophila) 28951 1
UDP-glucose ceramide
UGCG 7357
glucosyltransferase 1
UDP-glucose ceramide
UGCGL1 56886
glucosyltransferase-like 1 1 vav 3 guanine nucleotide exchange
VAV3 10451
factor 1 vezatin, adherens junctions
VEZT 55591
transmembrane protein 1
WNT2B wingless-type MMTV integration site 7482 1
Figure imgf000098_0001
ZNF780A zinc finger protein 780A 284323 1
Example 4: Affymetrix array analysis of the KU95 cell line panel to identify genes correlating with olaparib sensitivity
Although PARP-1 and HRD have been proposed as predictive markers for PARP inhibitor sensitivity it remains possible that other factors might also regulate a cancer cell's response to a PARP inhibitor. To address this we conducted a genome wide search for genes correlating with olaparib response across all 95 cell lines within the KU95 panel.
RNA was extracted from frozen cell pellets (up to 1 x 107 cells) by guanidine- isothiocyanate lysis and silica-membrane purification using the RNeasy® Mini Kit from QIAGEN (Hilden, Germany) quantified by NanoDrop (NanoDrop
Technologies) and RNA quality assessed on the Agilent 2100 bioanalyser with the RNA 6000 LabChip kit (Agilent technologies) according to manufacturer's recommendations. Samples yielding >4μg of RNA and with a RNA integrity number (RIN) of >7.0 were progressed to Affymetrix profiling. This was performed using 4 sets of fluidic batches each of 24/25 chips (97 chips in total 95 for cell lines and 2 reference RNA controls). These batch effects were accounted for in the statistical analysis.
The biomarker hybridisation probes used to measure the expression levels of the biomarkers are those on the Affymetrix "HG-U133_Plus_2" array in the '3' IVT Expression Analysis Arrays'. The probe annotation and sequences are available from www.affymetrix.com/support/technical/annotationfilesmain.affx
4μ9 of cell line derived RNA was amplified using the One Cycle Target Labelling and Control reagents from Affymetrix (Santa Clara. CA) and hybridised to Affymetrix Human Genome U133 Plus 2.0 arrays using standard methods. "One Cycle Target Labelling and Control" reagents and "Eukaryotic Hybridisation, Wash and Scan" reagents from Affymetrix (Santa Clara. CA) were used to synthesis biotinylated probes for Affymetrix gene expression profiling. Briefly, single-strand cDNA was generated from 4 g of total RNA via T7 oligo-dT priming followed by second strand synthesis. The double-stranded cDNA product was purified by filtration (MinElute- QIAGEN) then subjected to in-vitro transcription to produce biotinylated cRNA. Purified cRNA was fragmented then hybridized to HG- U133plus2.0 Affymetrix chips for 16hrs using manufacturer's recommendations. Affymetrix .CEL files were exported for subsequent statistical analysis.
Affymetrix data were processed using the RMA algorithm (Irizarry et al., Biostat., 4, 249-264; 2003) and Informative filtering (Talloen et al., Bioinformatics. Nov 1 ;23 (21 ):2897-2902, 2007) was applied to the 54675 Affymetrix probe sets, leaving 2451 1 probe sets. To conduct the statistical analyses the following data were used: the gene expression levels for each probe, olaparib IC50 as a measure of sensitivity to olaparib, the tissue types of the cell lines and the chip and fluidics batches that the Affymetrix chips were processed in.
Each of these 2451 1 probe sets was then separately subjected to five analyses and the F statistic for the sensitivity to olaparib calculated. These five analyses included DEGNN (analysis of variance with gene expression as the response, and chip and fluidics batch and olaparib sensitivity as predictive variables); DEGTN (analysis of variance with gene expression as the response, and chip and fluidics batch, cell line tissue type and olaparib sensitivity as predictive variables); DEGNG (analysis of variance with gene expression as the response and chip and fluidics batch, HRD expression, PARP expression and olaparib sensitivity as predictive variables); DEGTG (analysis of variance with gene expression as the response and chip and fluidics batch, HRD expression, PARP expression, cell line tissue type and olaparib sensitivity as predictive variables. The final analysis was:
DES: F = f5|™mi maXM¾ Wirt > P> )l Where F[x, y) is the F statistic from an analysis of variance comparing the two sets of data x and and and s'(P) represent the highest and lowest p% of expression levels from sensitive cell lines, and ηρ) and r'(P) the highest and lowest p% of expression levels from resistant cell lines.
In order to maximise the power for identifying predictive genes, each analysis was performed using twelve different cut-offs defining olaparib sensitivity and
resistance and also considering the log of the olaparib IC50 as a continuous variable. The different cut-offs were (<1 μΜ,>1 μΜ) , (<1 .25μΜ,>1 .25μΜ) ,
(<1 .5μΜ >1 .5μΜ) , (<1 .75μΜ >1 .75μΜ) , (<2μΜ >2μΜ) , (<0.75μΜ >1 .5μΜ) , (<1 μΜ >2μΜ) , (<1 .25μΜ >2.5μΜ) , (<1 .5μΜ >3μΜ) , (<1 .75μΜ >3.5μΜ) ,
(<0.75μΜ,>2.25μΜ) , (<1 μΜ,>3μΜ). The maximal F value over the different cutoffs taken was calculated. Genes were accepted both where differential in expression was absolute and where it was restricted to cell line subsets.
A false discovery rate was calculated to provide confidence that these genes were truly associated with olaparib sensitivity and not due to chance. In order to calculate the false discovery rate, the IC5o values of the cell lines along with their corresponding sensitivity/resistance definitions, were permuted 100 times using the re-order function within R (A Language and Environment for Statistical
Computing. www.R-project.org) and the maximal F statistics recalculated to generate permutation p-values for each probe set. The ratio of the number of permuted to the number of observed probe sets with maximal F statistics less than or equal to each value were used to calculate a false discovery rate and probes with a false discovery rate of less than 0.5 were taken forward.
These probes translated into a total of 426 individual genes from the five analyses that demonstrated a correlation with olaparib sensitivity (see table 12). Further filtering these selected genes on whether or not they had achieved a differential expression between sensitive and resistant groups and indicating where the absolute level of correlation in expression between genes was greater than 0.55 (the Pearson correlation coefficient), identified two main clusters of genes (Figure 4). Both for the DEG list as a whole and for each correlated gene network, biological overlay was run to identify key mechanisms and pathways linked to response. Biological overlay included investigation for directionality-controlled enrichment of:
• Candidate BER/HR markers
• Canonical [Ingenuity Pathways Analysis (Ingenuity® Systems,
www.ingenuity.com); KEGG (www.genome.jp/kegg/pathway.html)] signatures for oncogenic signalling pathways
• Functional [IPA; GO (www.geneontology.org/)] processes linked to
oncogenic mechanisms
• Literature derived dynamic gene expression signatures reflective of
activation/inhibition of key oncogenic pathways
• Literature derived dynamic gene expression signatures reflective of
treatment with compounds targeting oncogenic pathways (Connectivity Map)
• Literature derived gene expression signatures predictive of core cancer disease sub-groups and treatment prognosis
• Internally generated signatures reflective of dynamic changes and
responsiveness to oncology compounds
• Evidence of known biological interactions between genes found co- expressed
Data were filtered for genes overlapping biological mechanisms identified as dominant in enrichment or most predictive of response. Candidate marker genes were then prioritised as those displaying:
• Rational linkage of biological overlay to DNA repair / drug response
• Consistency between the biological hypothesis and directionality/correlation of differential expression
• Strength of hypothesis and number of independent evidence sources
• Magnitude of differential expression with respect to response
• Consistency of differential expression with respect to pathway activity
across published and internally generated genelists Using Ingenuity software (Ingenuity® Systems, www.ingenuity.com) the first of these clusters could be seen to contain genes associated primarily with DNA repair, more specifically with BER (such as PARP-1 , MUTYH, POLD1 and POLE3) and HR functions (such as BRCA1 and ATM). The second cluster contained many genes associated with cell cycle and cell proliferation function and represents a new insight into the kind of genes that correlate with PARP inhibitor response. An example of such a gene in the proliferation cluster is Aurora Kinase A that is associated with the regulation of mitotic events. But all the genes identified in these two clusters are contained with Tables 1 , 2 or 3.
Table 12 shows the list of 426 genes correlating with olaparib response across the KU95 panel identified by Affymetrix analysis.
Biomarker Gene Symbol Entrez Gene Name Entrez Gene ID
V ATP-binding cassette, sub- family A (ABC1), member 7 10347
ATP-binding cassette, sub-family G (WHITE), member
ABCG2 2 9429
ACTL6A actin-like 6A 86
ADORA2A adenosine A2a receptor 135
AIP aryl hydrocarbon receptor interacting protein 9049
AK2 adenylate kinase 2 204
AKIPJN1 akirin 1 79647
ALDH1L2 aldehyde dehydrogenase 1 family, member L2 160428
ALKBH6 alkB, alkylation repair homolog 6 (E. coli) 84964
AMPD2 adenosine monophosphate deaminase 2 (isoform L) 271
ANKRD18A ankyrin repeat domain 18A 253650
ANLN anillin, actin binding protein 54443
ANOl anoctamin 1, calcium activated chloride channel 55107
ANXA8 annexin A8 653145
ANXA8L2 annexin A8-like 2 244
APLP2 amyloid beta (A4) precursor-like protein 2 334
AQP11 aquaporin 11 282679
ARHGDIA Rho GDP dissociation inhibitor (GDI) alpha 396
ARNT aryl hydrocarbon receptor nuclear translocator 405
ARSA arylsulfatase A 410
ArfGAP with SH3 domain, ankyrin repeat and PH
ASAP3 domain 3 55616
ATAD2 ATPase family, AAA domain containing 2 29028
ATG10 ATG10 autophagy related 10 homolog (S. cerevisiae) 83734
ATL1 atlastin GTPase 1 51062
ATM ataxia telangiectasia mutated 472
ATP2A3 ATPase, Ca++ transporting, ubiquitous 489
ATP synthase, H+ transporting, mitochondrial FO
ATP5G1 complex, subunit CI (subunit 9) 516
ATP7A ATPase, Cu++ transporting, alpha polypeptide 538
ATXN3 ataxin 3 4287 AURKA aurora kinase A 6790
AXL AXL receptor tyrosine kinase 558
B4GALNT4 beta-l,4-N-acetyl-galactosaminyl transferase 4 338707
BCL2A1 BCL2 -related protein Al 597
BCL2L1 BCL2-like 1 598
BEX4 brain expressed, X-linked 4 56271
BHMT2 betaine-homocysteine methyltransferase 2 23743
BID BH3 interacting domain death agonist 637
BIRC3 baculoviral IAP repeat-containing 3 330
BMI1 BMI1 polycomb ring finger oncogene 648
BNIP3 BCL2/adenovirus EIB 19kDa interacting protein 3 664
BOC Boc homolog (mouse) 91653
BRCA1 breast cancer 1, early onset 672
BSDC1 BSD domain containing 1 55108
BTBD10 BTB (POZ) domain containing 10 84280
CHORF17 chromosome 11 open reading frame 17 56672
C120RF48 chromosome 12 open reading frame 48 55010
C14ORF106 chromosome 14 open reading frame 106 55320
C150RF61 chromosome 15 open reading frame 61 145853
C160RF5 chromosome 16 open reading frame 5 29965
C170RF37 chromosome 17 open reading frame 37 84299
C190RF33 chromosome 19 open reading frame 33 64073
C1ORF50 chromosome 1 open reading frame 50 79078
C10RF52 chromosome 1 open reading frame 52 148423
C10RF96 chromosome 1 open reading frame 96 126731
C10RF149 chromosome 1 open reading frame 149 64769
C20ORF43 chromosome 20 open reading frame 43 51507
C210RF56 chromosome 21 open reading frame 56 84221
C30RF14 chromosome 3 open reading frame 14 57415
C30RF21 chromosome 3 open reading frame 21 152002
C40RF27 chromosome 4 open reading frame 27 54969
C50RF13 chromosome 5 open reading frame 13 9315
C60RF48 chromosome 6 open reading frame 48 50854
C60RF64 chromosome 6 open reading frame 64 55776
C7ORF10 chromosome 7 open reading frame 10 79783
C70RF42 chromosome 7 open reading frame 42 55069
C90RF122 chromosome 9 open reading frame 122 158228
CALM1 calmodulin 1 (phosphorylase kinase, delta) 801
CALM2 calmodulin 2 (phosphorylase kinase, delta) 805
CALM3 calmodulin 3 (phosphorylase kinase, delta) 808
CAPN6 calpain 6 827
CARD 10 caspase recruitment domain family, member 10 29775 caspase 1, apoptosis-related cysteine peptidase
CASP1 (interleukin 1, beta, convertase) 834
CASP4 caspase 4, apoptosis-related cysteine peptidase 837
CASP8 caspase 8, apoptosis-related cysteine peptidase 841
CBS cystathionine-beta-synthase 875
CCDC76 coiled-coil domain containing 76 54482
CCDC149 coiled-coil domain containing 149 91050
CCNE2 cyclin E2 9134
CCNG2 cyclin G2 901
CCNL2 cyclin L2 81669
CCPG1 cell cycle progression 1 9236
CDC6 cell division cycle 6 homolog (S. cerevisiae) 990
CDCA4 cell division cycle associated 4 55038 CDK2 cyclin-dependent kinase 2 1017
CDK 1C cyclin-dependent kinase inhibitor 1C (p57, Kip2) 1028 cadherin, EGF LAG seven-pass G-type receptor 1
CELSR1 (flamingo homolog, Drosophila) 9620
CEP55 centrosomal protein 55kDa 55165
CEP 192 centrosomal protein 192kDa 55125
CHEK1 CHEK1 checkpoint homolog (S. pombe) 1111
CIB2 calcium and integrin binding family member 2 10518
CLCN3 chloride channel 3 1182
CLN3 ceroid-lipofuscinosis, neuronal 3 1201
CLPTM1 cleft lip and palate associated transmembrane protein 1 1209
COMMD3 COMM domain containing 3 23412
COR02A coronin, actin binding protein, 2A 7464
CPSF1 cleavage and polyadenylation specific factor 1, 160kDa 29894
CSDE1 cold shock domain containing El, RNA-binding 7812
CSGALNACT1 chondroitin sulfate N-acetylgalactosaminyltransferase 1 55790
CT45A1 cancer/testis antigen family 45, member Al 541466
CT45A2 cancer/testis antigen family 45, member A2 728911
CT45A3 cancer/testis antigen family 45, member A3 441519
CT45A4 cancer/testis antigen family 45, member A4 441520
CT45A6 cancer/testis antigen family 45, member A6 541465
CXORF15 chromosome X open reading frame 15 55787
CXXC1 CXXC finger 1 (PHD domain) 30827
CYB561D2 cytochrome b-561 domain containing 2 11068
CYFIP2 cytoplasmic FMR1 interacting protein 2 26999
CYTSA cytospin A 23384
CYTSB cytospin B 92521
D site of albumin promoter (albumin D-box) binding
DBP protein 1628
DDR2 discoidin domain receptor tyrosine kinase 2 4921
DECR1 2,4-dienoyl CoA reductase 1, mitochondrial 1666
DHRSX dehydrogenase/reductase (SDR family) X-linked 207063
DIRAS3 DIRAS family, GTP-binding RAS-like 3 9077
DOCK1 dedicator of cytokinesis 1 1793
DOCK3 dedicator of cytokinesis 3 1795
DSTYK dual serine/threonine and tyrosine protein kinase 25778
DVL1 dishevelled, dsh homolog 1 (Drosophila) 1855
DZIP1 DAZ interacting protein 1 22873
DZIP3 DAZ interacting protein 3, zinc finger 9666
EBP emopamil binding protein (sterol isomerase) 10682
ECT2 epithelial cell transforming sequence 2 oncogene 1894
EFCAB4B EF-hand calcium binding domain 4B 84766
EFHD2 EF-hand domain family, member D2 79180
EGFL8 EGF-like-domain, multiple 8 80864
EIF2C1 eukaryotic translation initiation factor 2C, 1 26523
EIF2C3 eukaryotic translation initiation factor 2C, 3 192669
ENAH enabled homolog (Drosophila) 55740
EPS 15 epidermal growth factor receptor pathway substrate 15 2060 excision repair cross-complementing rodent repair
deficiency, complementation group 1 (includes
ERCC1 overlapping antisense sequence) 2067
ERI3 exoribonuclease 3 79033
ETFA electron-transfer-flavoprotein, alpha polypeptide 2108
ETFB electron-transfer-flavoprotein, beta polypeptide 2109
EXOl exonuclease 1 9156 family with sequence similarity 10, member A4
FAM10A4 pseudogene 145165 family with sequence similarity 10, member A5
FAM10A5 pseudogene 144106
FAM111B family with sequence similarity 111, member B 374393
FAM129B family with sequence similarity 129, member B 64855
FBP1 fructose- 1,6-bisphosphatase 1 2203
FEN1 flap structure-specific endonuclease 1 2237
FGD6 FYVE, RhoGEF and PH domain containing 6 55785
FGFR3 fibroblast growth factor receptor 3 2261
FKBP1B FK506 binding protein IB, 12.6 kDa 2281
FLOT1 flotillin 1 10211
FNBP1L formin binding protein 1 -like 54874
FRG1 FSHD region gene 1 2483
FTSJ1 FtsJ homolog 1 (E. coli) 24140
FXYD6 FXYD domain containing ion transport regulator 6 53826
FZD6 frizzled homolog 6 (Drosophila) 8323
G6PC3 glucose 6 phosphatase, catalytic, 3 92579
GAS1 growth arrest-specific 1 2619 glucosaminyl (N-acetyl) transferase 2, 1-branching
GCNT2 enzyme (I blood group) 2651
GINS1 GINS complex subunit 1 (Psfl homolog) 9837
GINS2 GINS complex subunit 2 (Psf2 homolog) 51659
GINS3 GINS complex subunit 3 (PsB homolog) 64785
GLIPR1 GLI pathogenesis-related 1 11010
GLT8D2 glycosyltransferase 8 domain containing 2 83468
GNL3 guanine nucleotide binding protein-like 3 (nucleolar) 26354
GPBP1L1 GC-rich promoter binding protein 1 -like 1 60313
GPC3 glypican 3 2719
GPR137C G protein-coupled receptor 137C 283554
GSG2 germ cell associated 2 (haspin) 83903
GSTOl glutathione S-transferase omega 1 9446
HAS2 hyaluronan synthase 2 3037
HDAC4 histone deacetylase 4 9759 homogentisate 1,2-dioxygenase (homogentisate
HGD oxidase) 3081
HIPK2 homeodomain interacting protein kinase 2 28996
HIST1H2AC histone cluster 1, H2ac 8334
HNRNPA3 heterogeneous nuclear ribonucleoprotein A3 220988
HS6ST2 heparan sulfate 6-O-sulfotransferase 2 90161
IFI16 interferon, gamma-inducible protein 16 3428 immunoglobulin-like and fibronectin type III domain
IGFN1 containing 1 91156
IL17RB interleukin 17 receptor B 55540
IL1R1 interleukin 1 receptor, type I 3554
INPP5B inositol polyphosphate-5-phosphatase, 75kDa 3633
IP6K2 inositol hexakisphosphate kinase 2 51447
IRX3 iroquois homeobox 3 79191
ISL1 ISL LIM homeobox 1 3670
ISYNA1 inositol-3 -phosphate synthase 1 51477
ITGB4 integrin, beta 4 3691
JUP junction plakoglobin 3728
KDM3A lysine (K)-specific demethylase 3A 55818
KDM4A lysine (K)-specific demethylase 4A 9682
KDM5B lysine (K)-specific demethylase 5B 10765
Figure imgf000106_0001
NADH dehydrogenase (ubiquinone) 1 alpha
NDUFAFl subcomplex, assembly factor 1 51103
NEK3 NIMA (never in mitosis gene a)-related kinase 3 4752 nuclear factor of kappa light polypeptide gene enhancer
NFKB2 in B-cells 2 (p49/pl00) 4791
NIPA1 non imprinted in Prader- Willi/ Angelman syndrome 1 123606
NOTCH3 Notch homolog 3 (Drosophila) 4854
NP nucleoside phosphorylase 4860
NPAS2 neuronal PAS domain protein 2 4862 nudix (nucleoside diphosphate linked moiety X)-type
NUDT1 motif 1 4521 nudix (nucleoside diphosphate linked moiety X)-type
NUDT3 motif 3 11165
NUP210 nucleoporin 21 OkDa 23225
NUPL2 nucleoporin like 2 11097
NUSAP1 nucleolar and spindle associated protein 1 51203
OGG1 8-oxoguanine DNA glycosylase 4968
OIP5 Opa interacting protein 5 11339
OPA1 optic atrophy 1 (autosomal dominant) 4976
ORMDL2 ORMl-like 2 (S. cerevisiae) 29095
PABPC4 poly(A) binding protein, cytoplasmic 4 (inducible form) 8761
PANK3 pantothenate kinase 3 79646
PAPSS1 3'-phosphoadenosine 5'-phosphosulfate synthase 1 9061
PARP6 poly (ADP-ribose) polymerase family, member 6 56965
PBX1 pre-B-cell leukemia homeobox 1 5087
PBX2 pre-B-cell leukemia homeobox 2 5089
PCBP4 poly(rC) binding protein 4 57060
PCDHA6 protocadherin alpha 6 56142
PCYT1A phosphate cytidylyltransferase 1 , choline, alpha 5130 phosphodiesterase 4B, cAMP-specific
PDE4B (phosphodiesterase E4 dunce homolog, Drosophila) 5142
PEAR1 platelet endothelial aggregation receptor 1 375033
PHACTR2 phosphatase and actin regulator 2 9749
PHF13 PHD finger protein 13 148479
PHF15 PHD finger protein 15 23338
PHF21A PHD finger protein 21 A 51317
PIAS2 protein inhibitor of activated STAT, 2 9063
PIGB phosphatidylinositol glycan anchor biosynthesis, class B 9488
PIGL phosphatidylinositol glycan anchor biosynthesis, class L 9487
PLAUR plasminogen activator, urokinase receptor 5329
PLD1 phospholipase Dl, phosphatidylcholine-specific 5337
PLXNA2 plexin A2 5362
PMS1 postmeiotic segregation increased 1 (S.
PMS1 cerevisiae) 5378
PODXL podocalyxin-like 5420
POLB polymerase (DNA directed), beta 5423 polymerase (DNA directed), delta 1, catalytic subunit
POLD1 125kDa 5424
POLE2 polymerase (DNA directed), epsilon 2 (p59 subunit) 5427
POLE3 polymerase (DNA directed), epsilon 3 (pi 7 subunit) 54107
POLH polymerase (DNA directed), eta 5429
POLQ polymerase (DNA directed), theta 10721
PORCN porcupine homolog (Drosophila) 64840 protein phosphatase 1, regulatory (inhibitor) subunit
PPP1R15A 15A 23645 PPT2 palmitoyl-protein thioesterase 2 9374
PRIM1 primase, DNA, polypeptide 1 (49kDa) 5557 protein kinase, AMP-activated, beta 2 non-catalytic
PRKAB2 subunit 5565 protein kinase, cAMP-dependent, regulatory, type II,
PRKAR2B beta 5577
PRKCA protein kinase C, alpha 5578
PROSAPIP1 ProSAPiPl protein 9762
PRR3 proline rich 3 80742 proteasome (prosome, macropain) subunit, beta type, 8
PSMB8 (large multifunctional peptidase 7) 5696
PTCD2 pentatricopeptide repeat domain 2 79810
PTTG1 pituitary tumor-transforming 1 9232
PYCARD PYD and CARD domain containing 29108 glutaminyl-tRNA synthase (glutamine-hydrolyzing)-like
QRSL1 1 55278
QSER1 glutamine and serine rich 1 79832
QSK serine/threonine-protein kinase QSK 23387
QTRTD1 queuine tRNA-ribosyltransferase domain containing 1 79691
RAB7A RAB7A, member RAS oncogene family 7879
RABGAP1L RAB GTPase activating protein 1 -like 9910
RAD52 RAD52 homolog (S. cerevisiae) 5893
RAE1 RAEl RNA export 1 homolog (S. pombe) 8480
RANBP9 RAN binding protein 9 10048
RAPGEF2 Rap guanine nucleotide exchange factor (GEF) 2 9693
RASA3 RAS p21 protein activator 3 22821
RCHY1 ring finger and CHY zinc finger domain containing 1 25898
RCOR3 REST corepressor 3 55758
RDH10 retinol dehydrogenase 10 (all-trans) 157506
RELB v-rel reticuloendotheliosis viral oncogene homolog B 5971 regulatory factor X, 5 (influences HLA class II
RFX5 expression) 5993
RGNEF Rho-guanine nucleotide exchange factor 64283
RIMS3 regulating synaptic membrane exocytosis 3 9783
RIPK2 receptor-interacting serine-threonine kinase 2 8767
RLF rearranged L-myc fusion 6018
RND2 Rho family GTPase 2 8153
RPL17 ribosomal protein LI 7 6139
RPL31 ribosomal protein L31 6160
RPP30 ribonuclease P/MRP 30kDa subunit 10556
RRM2 ribonucleotide reductase M2 polypeptide 6241
RSBN1 round spermatid basic protein 1 54665
RTN4IP1 reticulon 4 interacting protein 1 84816
S100PBP SI OOP binding protein 64766
SAMD1 sterile alpha motif domain containing 1 90378
SCMH1 sex comb on midleg homolog 1 (Drosophila) 22955
SDAD1 SDA1 domain containing 1 55153 sema domain, immunoglobulin domain (Ig),
transmembrane domain (TM) and short cytoplasmic
SEMA4C domain, (semaphorin) 4C 54910 sema domain, immunoglobulin domain (Ig),
transmembrane domain (TM) and short cytoplasmic
SEMA4D domain, (semaphorin) 4D 10507 sema domain, transmembrane domain (TM), and
SEMA6A cytoplasmic domain, (semaphorin) 6A 57556 SERINC3 serine incorporator 3 10955 serpin peptidase inhibitor, clade E (nexin, plasminogen
SERPINE1 activator inhibitor type 1), member 1 5054
Src homology 3 domain-containing guanine nucleotide
SGEF exchange factor 26084
SH3PXD2B SH3 and PX domains 2B 285590
SLC22A17 solute carrier family 22, member 17 51310
SLC26A11 solute carrier family 26, member 11 284129 solute carrier family 2 (facilitated glucose transporter),
SLC2A11 member 11 66035
SLFN12 schlafen family member 12 55106
SMAP1 small ArfGAP 1 60682
SWI/SNF related, matrix associated, actin dependent
SMARCA5 regulator of chromatin, subfamily a, member 5 8467
SWI/SNF related, matrix associated, actin dependent
SMARCD3 regulator of chromatin, subfamily d, member 3 6604
SMC2 structural maintenance of chromosomes 2 10592
SNX27 sorting nexin family member 27 81609
SOCS4 suppressor of cytokine signaling 4 122809
SOLH small optic lobes homolog (Drosophila) 6650
SOS1 son of sevenless homolog 1 (Drosophila) 6654
SOX7 SRY (sex determining region Y)-box 7 83595
SP1 Spl transcription factor 6667
SPAG5 sperm associated antigen 5 10615
SPTLC2 serine palmitoyltransferase, long chain base subunit 2 9517
SRA1 steroid receptor RNA activator 1 10011
SSH3 slingshot homolog 3 (Drosophila) 54961
SSX2IP synovial sarcoma, X breakpoint 2 interacting protein 117178 suppression of tumorigenicity 13 (colon carcinoma)
ST13 (Hsp70 interacting protein) 6767
STAU2 staufen, RNA binding protein, homolog 2 (Drosophila) 27067
STC2 stanniocalcin 2 8614
STRBP spermatid perinuclear RNA binding protein 55342
SUMF2 sulfatase modifying factor 2 25870
SUV39H1 suppressor of variegation 3-9 homolog 1 (Drosophila) 6839
SYNE2 spectrin repeat containing, nuclear envelope 2 23224
SYNJ1 synaptojanin 1 8867
TBC1D2 TBC1 domain family, member 2 55357
TBC1D10A TBC1 domain family, member 10A 83874
TET1 tet oncogene 1 80312
TEX 15 testis expressed 15 56154
THBD thrombomodulin 7056
TIAl TIAl cytotoxic granule-associated RNA binding protein 7072
TIMELESS timeless homolog (Drosophila) 8914 translocase of inner mitochondrial membrane 10
TIMM10 homolog (yeast) 26519
TLR4 toll-like receptor 4 7099
TM4SF1 transmembrane 4 L six family member 1 4071
TMEM93 transmembrane protein 93 83460
TMEM97 transmembrane protein 97 27346
TMEM111 transmembrane protein 111 55831
TMEM41B transmembrane protein 41B 440026
TMSB15A thymosin beta 15a 11013 tankyrase, TRFl -interacting ankyrin -related ADP-ribose
TNKS polymerase 8658 TP53BP2 tumor protein p53 binding protein, 2 7159
TPD52 tumor protein D52 7163
TPX2, microtubule-associated, homolog (Xenopus
TPX2 laevis) 22974
TREX1 three prime repair exonuclease 1 11277
TRIM 14 tripartite motif-containing 14 9830
TPJTl tRNA isopentenyltransferase 1 54802
TRM2 tRNA methyltransferase 2 homolog B (S.
TRMT2B cerevisiae) 79979
TROAP trophinin associated protein (tastin) 10024
TST thiosulfate sulfurtransferase (rhodanese) 7263
TTC3 tetratricopeptide repeat domain 3 7267
TYSND1 trypsin domain containing 1 219743
UCP2 uncoupling protein 2 (mitochondrial, proton carrier) 7351
UFM1 ubiquitin-fold modifier 1 51569
UFSP2 UFM1 -specific peptidase 2 55325
ULK1 unc-51 -like kinase 1 (C. elegans) 8408
USP8 ubiquitin specific peptidase 8 9101
USP42 ubiquitin specific peptidase 42 84132
USP46 ubiquitin specific peptidase 46 64854
USP34 ubiquitin specific peptidase 34 9736
VARS2 valyl-tRNA synthetase 2, mitochondrial (putative) 57176
VASH1 vasohibin 1 22846
VCAN versican 1462
VPS29 vacuolar protein sorting 29 homolog (S. cerevisiae) 51699
WDHD1 WD repeat and HMG-box DNA binding protein 1 11169
WDR34 WD repeat domain 34 89891
WDR41 WD repeat domain 41 55255
WDR60 WD repeat domain 60 55112
X-ray repair complementing defective repair in Chinese
XRCC3 hamster cells 3 7517 tyrosine 3-monooxygenase/tryptophan 5-
YWHAB monooxygenase activation protein, beta polypeptide 7529
ZBTB5 zinc finger and BTB domain containing 5 9925
ZBTB7A zinc finger and BTB domain containing 7A 51341
ZC3H6 zinc finger CCCH-type containing 6 376940
ZC3H13 zinc finger CCCH-type containing 13 23091
ZIC1 Zic family member 1 (odd-paired homolog, Drosophila) 7545
ZIC2 Zic family member 2 (odd-paired homolog, Drosophila) 7546
ZMYM2 zinc finger, MYM-type 2 7750
ZMYM4 zinc finger, MYM-type 4 9202
ZMYM6 zinc finger, MYM-type 6 9204
ZMYM3 zinc finger, MYM-type 3 9203
ZNF14 zinc finger protein 14 7561
ZNF43 zinc finger protein 43 7594
ZNF74 zinc finger protein 74 7625
ZNF137 zinc finger protein 137 7696
ZNF175 zinc finger protein 175 7728
ZNF287 zinc finger protein 287 57336
ZNF382 zinc finger protein 382 84911
ZNF397 zinc finger protein 397 84307
ZNF436 zinc finger protein 436 80818
ZNF607 zinc finger protein 607 84775
ZNF682 zinc finger protein 682 91120
ZNF518B zinc finger protein 518B 85460 ZWINT ZW10 interactor 11130
ZZZ3 zinc finger, ZZ-t pe containing 3 26009
Example 5: Improved predictive power provided by combining biomarkers from BER, HR and Proliferation functions
The identification of genes associated with three distinct functions: BER, HR and proliferation from the Affymetrix analysis has led to the generation of three distinct gene lists represented by Table 1 , Table 2 and Table 3 respectively which have been derived according to the scheme presented in Figure 5.
To determine whether genes within this proliferation cluster could add to the predictive value of PARP-1 and HRD as biomarkers we looked at various combinations of three markers (one from each of Tables 1 , 2 and 3) where each marker makes a significant contribution to the overall prediction. The results of this analysis demonstrated many different combinations that had a significantly greater predictive power than either a BER or HR biomarker alone or even together. The top 152 examples are shown in Table 13. The p-values quoted in this list represent the enhancement to prediction when that gene is added to the other two genes in the triplet in a logistic regression model of the sensitivity or resistance of cell lines within the KU95 cell line panel.
This analysis identified the MUTYH gene as a significant predictor of olaparib response that is associated with BER as well as highlighting POLD1 and POLE3. Also exemplified by Table 13 is the predictive power of the HR genes ATM, ATR, MCM2, XRCC3, BRCA1 , MDC1 , NBN, RAD51 and MRE1 1 A. Finally, this analysis demonstrates that a wide variety of proliferation associated genes can add significantly to the predictive power of BER and HR biomarkers as well as providing a clear indication that using multiple biomarkers from the three functional groups (BER, HR and proliferation) results in a much more effective predictor than either a BER or HR biomarker together or individually. Figures 6-10 provides some visual examples of this point using Receiver Operating Characteristic (ROC) curves based on different combinations of biomarkers, namely PARP-1 , BRCA1 and Aurora kinase A (AURKA; Figure 6); MUTYH, BRCA1 and SMARCD3 (Figure 7); MUTYH, ATM and ZIC1 (Figure 8); POLD1 , ATM and SSX2IP (Figure 9);
POLE3, BRCA1 and BOC (Figure 10).
Table 13 shows the list of 152 combinations of biomarkers where the addition of a proliferation biomarker adds to the predictive power of the BER and HR
biomarkers.
BER HR Proliferation p-Value of p-Value of p-Value of Gene Gene Gene enhancement enhancement enhancement to prediction to prediction to prediction by by BER Gene by HR Gene Proliferation
Gene
PARP- MCM2 SMARCD3
1 0.00223 0.00212 0.00076
PARP- MCM2 IP6K2
1 0.00252 0.00130 0.00284
PARP- MCM2 GTF2H4;VA
1 RS2 0.00189 0.00054 0.00299
MUTYH ATM SMARCD3 0.001 15 0.00403 0.00004
PARP- MCM2 MBD1
1 0.00436 0.00297 0.00262
PARP- XRCC IP6K2
1 3 0.00562 0.00286 0.00180
PARP- MCM2 ZMYM4
1 0.00601 0.00100 0.00134
MUTYH XRCC SMARCD3
3 0.00088 0.00617 0.00018
PARP- MCM2 SMARCA5
1 0.00155 0.00053 0.00619
PARP- MCM2 SCMH1
1 0.00197 0.00225 0.00685
MUTYH MCM2 SMARCD3 0.00297 0.00699 0.0001 1
MUTYH XRCC IP6K2
3 0.00740 0.00268 0.00287
PARP- MDC1 MRAS
1 0.00201 0.00791 0.00364
MUTYH BRCA TLR4
1 0.00677 0.00835 0.00297
MUTYH MCM2 POLH 0.00563 0.00921 0.00480
PARP- MDC1 POLH
1 0.00271 0.00927 0.00473
PARP- MCM2 AURKA
1 0.00007 0.00988 0.00075 PARP- XRCC MBD1
1 3 0.01004 0.00334 0.00285
MUTYH BRCA RASA3
1 0.00325 0.00535 0.01075
PARP- MCM2 POLH
1 0.00087 0.00134 0.01 101
PARP- NBN POLH
1 0.00573 0.01 109 0.00328
MUTYH MCM2 MRAS 0.00793 0.01 153 0.00702
PARP- MDC1 SCMH1
1 0.00461 0.01212 0.00432
PARP- XRCC SMARCA5
1 3 0.01261 0.00412 0.00973
PARP- XRCC SCMH1
1 3 0.00834 0.01291 0.01201
PARP- BRCA AURKA
1 1 0.00017 0.01329 0.00030
PARP- RAD5 GTF2H4;VA
1 1 RS2 0.00977 0.01339 0.00704
PARP- MDC1 GTF2H4;VA
1 RS2 0.01 1 19 0.01360 0.00529
PARP- MCM2 SSX2IP
1 0.01391 0.00130 0.00027
PARP- MCM2 BOC
1 0.00894 0.00213 0.01424
PARP- BRCA MBD1
1 1 0.01430 0.00656 0.00375
PARP- XRCC ZMYM4
1 3 0.01433 0.00626 0.00025
PARP- MCM2 MRAS
1 0.00058 0.00109 0.01448
MUTYH XRCC POLH
3 0.00214 0.00843 0.01466
MUTYH MCM2 PHF13 0.01341 0.00420 0.01471
PARP- MCM2 ARNT
1 0.01499 0.00271 0.00535
PARP- MCM2 KDM4A
1 0.00613 0.00332 0.01506
MUTYH XRCC ARNT
3 0.01520 0.00526 0.00190
PARP- BRCA RASA3
1 1 0.00542 0.00554 0.01580
PARP- BRCA SCMH1
1 1 0.00996 0.01608 0.01261
PARP- XRCC GTF2H4;VA
1 3 RS2 0.01779 0.00405 0.00420
MUTYH BRCA MRAS 0.00919 0.01814 0.01588 1
PARP- BRCA NUDT1
1 1 0.00038 0.01839 0.01333
MUTYH ATM ZIC1 0.01843 0.01294 0.01041
PARP- BRCA IP6K2
1 1 0.01441 0.01849 0.01558
MUTYH RAD5 BOC
1 0.01854 0.01056 0.01348
PARP- BRCA GTF2H4;VA
1 1 RS2 0.01744 0.01665 0.01858
PARP- MCM2 ZMYM6
1 0.0001 1 0.00035 0.01961
MUTYH BRCA POLH
1 0.00580 0.01931 0.01981
MUTYH MCM2 TP53BP2 0.01212 0.00853 0.02029
MUTYH MCM2 RASA3 0.00519 0.01201 0.02034
PARP- XRCC KDM4A
1 3 0.01933 0.01687 0.02046
MUTYH NBN POLH 0.01047 0.02132 0.00204
PARP- MDC1 SMARCD3
1 0.00972 0.02168 0.00046
PARP- MDC1 IP6K2
1 0.00518 0.02235 0.00357
MUTYH XRCC TRIM14
3 0.00069 0.01016 0.02264
PARP- RAD5 POLH
1 1 0.00273 0.02315 0.01725
PARP- BRCA PMS1
1 1 0.02325 0.00361 0.02215
MUTYH BRCA TP53BP2
1 0.00665 0.00565 0.02343
PARP- MDC1 PCBP4
1 0.00132 0.01667 0.02359
PARP- RAD5 MBD1
1 1 0.01 105 0.02363 0.00175
PARP- XRCC PMS1
1 3 0.02369 0.00232 0.00901
PARP- MDC1 ZMYM4
1 0.02407 0.01 167 0.00107
PARP- NBN TP53BP2
1 0.01759 0.02425 0.01886
PARP- BRCA SMARCA5
1 1 0.01264 0.00806 0.02446
MUTYH ATR POLH 0.00348 0.02450 0.00481
MUTYH XRCC SMARCA5
3 0.00939 0.00252 0.02489
MUTYH XRCC RASA3 0.00139 0.00515 0.02528 3
PARP- MCM2 PMS1
1 0.00634 0.00156 0.02559
PARP- XRCC NUDT1
1 3 0.00035 0.02594 0.01251
MUTYH MCM2 ZIC1 0.02608 0.01269 0.01 181
PARP- XRCC SMARCD3
1 3 0.01709 0.02617 0.00129
MUTYH BRCA IP6K2
1 0.02649 0.02268 0.01460
MUTYH BRCA TRIM14
1 0.00187 0.02575 0.02709
MUTYH XRCC GTF2H4;VA
3 RS2 0.02737 0.00351 0.00855
PARP- NBN SCMH1
1 0.01488 0.02740 0.00593
MUTYH MCM2 TRIM14 0.00258 0.02771 0.02030
PARP- BRCA KDM4A
1 1 0.02771 0.02293 0.02292
MUTYH XRCC TP53BP2
3 0.00566 0.00390 0.02799
MUTYH MCM2 IP6K2 0.02839 0.01025 0.00423
MUTYH BRCA AURKA
1 0.00497 0.02854 0.02595
PARP- XRCC POLH
1 3 0.00561 0.01883 0.02872
MUTYH BRCA SMARCA5
1 0.02884 0.01335 0.02877
POLD1 ATM SSX2IP 0.00304 0.02889 0.00001
PARP- RAD5 KDM4A
1 1 0.01 125 0.02957 0.01666
PARP- MDC1 BOC
1 0.03001 0.02362 0.01601
MUTYH XRCC MRAS
3 0.00468 0.02100 0.03046
PARP- MCM2 ZIC1
1 0.01801 0.00591 0.03065
PARP- XRCC TP53BP2
1 3 0.01777 0.01070 0.031 14
PARP- MDC1 TP53BP2
1 0.00783 0.02425 0.03222
PARP- MCM2 RASA3
1 0.001 14 0.00271 0.03233
PARP- NBN ZIC1
1 0.03246 0.00878 0.02522
PARP- MDC1 MBD1
1 0.01675 0.03267 0.00386 MUTYH MCM2 SMARCA5 0.03309 0.00582 0.02007
PARP- NBN SMARCA5
1 0.02257 0.03328 0.02485
PARP- RAD5 IP6K2
1 1 0.00558 0.03349 0.00674
PARP- RAD5 SCMH1
1 1 0.00516 0.03395 0.01656
PARP- RAD5 BOC
1 1 0.02488 0.01407 0.03396
MUTYH XRCC SCMH1
3 0.01200 0.01017 0.03405
PARP- MDC1 TRIM14
1 0.00180 0.02301 0.03409
MUTYH MCM2 SCMH1 0.03464 0.01947 0.02258
MUTYH ATR TP53BP2 0.01 149 0.03482 0.02452
PARP- MDC1 RASA3
1 0.00297 0.02880 0.03525
PARP- NBN MRAS
1 0.01082 0.03532 0.00727
MUTYH MCM2 BCL2L1 0.00133 0.00798 0.03547
PARP- BRCA ZMYM4
1 1 0.03588 0.01678 0.00041
PARP- MCM2 NUDT1
1 0.00028 0.01875 0.03589
PARP- BRCA BOC
1 1 0.02750 0.00220 0.03625
MUTYH ATR SCMH1 0.02874 0.03635 0.01466
MUTYH XRCC BOC
3 0.03666 0.01046 0.03268
MUTYH BRCA SMARCD3
1 0.00497 0.03679 0.00048
PARP- MDC1 SMARCA5
1 0.01057 0.03692 0.03432
MUTYH NBN ZIC1 0.03753 0.01510 0.02520
PARP- NBN KDM4A
1 0.03757 0.03676 0.00837
PARP- RAD5 TP53BP2
1 1 0.00739 0.02251 0.03765
MUTYH BRCA SCMH1
1 0.02181 0.02219 0.03781
PARP- BRCA MRAS
1 1 0.00469 0.01363 0.03786
PARP- RAD5 SMARCA5
1 1 0.00849 0.031 18 0.03809
PARP- XRCC PHF13
1 3 0.03879 0.01355 0.02754
MUTYH BRCA ARNT 0.03895 0.02193 0.00325 1
PARP- NBN GTF2H4;VA
1 RS2 0.03901 0.02878 0.00624
MUTYH ATM PCBP4 0.00703 0.03916 0.02392
MUTYH XRCC TLR4
3 0.00658 0.03939 0.00649
MUTYH ATM POLH 0.00873 0.03992 0.00583
MUTYH ATM SCMH1 0.04005 0.03471 0.00947
MUTYH XRCC MBD1
3 0.04015 0.00643 0.00882
PARP- MCM2 TP53BP2
1 0.00171 0.00164 0.04073
PARP- BRCA TLR4
1 1 0.03843 0.01 108 0.04084
PARP- MCM2 PHF13
1 0.00503 0.00140 0.041 1 1
MUTYH MCM2 ARNT 0.04147 0.00717 0.001 1 1
MUTYH NBN TP53BP2 0.04214 0.04195 0.01293
MUTYH XRCC PHF13
3 0.00473 0.00393 0.04283
PARP- RAD5 MRAS
1 1 0.00492 0.04284 0.02029
PARP- XRCC RASA3
1 3 0.00724 0.02032 0.04425
PARP- NBN MBD1
1 0.03695 0.04442 0.00420
MUTYH BRCA PHF13
1 0.01023 0.00902 0.04445
PARP- XRCC MRAS
1 3 0.00715 0.03371 0.04459
MUTYH BRCA GTF2H4;VA
1 RS2 0.04465 0.03086 0.03812
MUTYH MRE1 TP53BP2
1A 0.04564 0.03981 0.01302
PARP- BRCA POLH
1 1 0.00526 0.02025 0.04593
PARP- MCM2 PCBP4
1 0.00038 0.00206 0.04606
PARP- XRCC PCBP4
1 3 0.00205 0.01389 0.04670
MUTYH ATM ARNT 0.04244 0.04685 0.00129
MUTYH XRCC TMSL8
3 0.02847 0.00341 0.04688
PARP- MRE1 POLH
1 1A 0.01209 0.04725 0.01 131
MUTYH MCM2 BOC 0.04777 0.00777 0.00719
PARP- NBN ZMYM4 0.04788 0.04649 0.00033 1
MUTYH XRCC PRKAR2B
3 0.00387 0.00344 0.04833
PARP- RAD5 PCBP4
1 1 0.00146 0.03033 0.04883
PARP- BRCA TP53BP2
1 1 0.01501 0.01242 0.04903
POLE3 BRCA BOC
1 0.04679 0.04933 0.01640
MUTYH RAD5 POLH
1 0.00554 0.04948 0.00631

Claims

Claims
1 . A method for selecting a cancer patient for treatment with a PARP inhibitor comprising measuring the expression level of PARP-1 and/or MUTYH and at least one biomarker from Table 2 in a tumour sample obtained from the patient, and selecting the patient for treatment with a PARP inhibitor if the expression profile of the biomarkers identifies the patient as being a likely responder to treatment with the PARP inhibitor.
2. The method as claimed in claim 1 , wherein the tumour sample does not exhibit low levels of PARP-1 and/or MUTYH expression.
3. The method as claimed in claim 2, wherein the at least one biomarker from Table 2 is selected from: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and
MRE1 1 A and said biomarker does exhibit low levels of expression.
4. The method as claimed in claim 1 , wherein the expression level of at least one biomarker from Table 1 , in addition to PARP-1 and/or MUTYH, is also measured.
5. The method as claimed in claim 4, wherein the expression level of PARP-1 and MUTYH is measured.
6. A method for selecting a cancer patient for treatment with a PARP inhibitor comprising measuring the expression level of at least one base excision repair biomarker from Table 1 , at least one homologous recombination biomarker from Table 2 and at least one proliferation biomarker from Table 3, in a tumour sample obtained from the patient and selecting the patient for treatment with a PARP inhibitor if the expression profile of the at least three biomarkers identifies the patient as being a likely responder to treatment with the PARP inhibitor, wherein the biomarker(s) from Table 1 must include PARP-1 .
7. The method as claimed in any of the preceding claims, wherein at least one base excision repair biomarker in addition to PARP-1 is selected from the group consisting of: first 10 biomarkers listed in Table 1 .
8. The method as claimed in any of the preceding claims, wherein the at least one base excision repair biomarker in addition to PARP-1 in Table 1 is selected from: MUTYH, POLD1 and POLE3.
9. The method as claimed in any of the preceding claims, wherein the at least one homologous recombination repair biomarker is selected from the first 12 biomarkers listed in Table 2.
10. The method as claimed in any of the preceding claims, wherein the at least one homologous recombination repair biomarker is selected from the group consisting of: MCM2, XRCC3, BRCA1 , MDC1 , ATM, ATR, NBN, RAD51 and MRE1 1A.
1 1 . The method as claimed in any of the preceding claims, wherein at least 2 homologous recombination repair biomarkers from Table 2 are assessed.
12. The method as claimed in any of the preceding claims, wherein a panel of homologous recombination repair biomarkers are measured, which panel includes: BRCA1 , BRCA2, MDC1 and ATM.
13. The method as claimed in any of the preceding claims, wherein the at least one proliferation biomarker is selected form the first 20 biomarkers listed in Table 3.
14. The method as claimed in any of the preceding claims, wherein the at least one biomarker from Table 3 is selected from the group consisting of: AURKA, SMARCD3, ZIC1 , SSX2IP, BOC, POLH, TP53BP2, SCMH1 , SMARCA5, MRAS, IP6K2, GTF2H4, MBD1 , RASA3, ZMYM4, PHF13, ARNT, KDM4A, PCBP4, TLR4, NUDT1 , PMS1 and ZMYM6.
15. The method as claimed in any of the preceding claims, wherein at least 2 proliferation biomarkers from Table 3 are assessed.
16. The method as claimed in any of the previous claims wherein the cancer is selected from the group consisting of: breast cancer, colorectal cancer, head and neck cancer, lung cancer, gastric cancer, prostate, haematological cancers, pancreatic cancer and ovarian cancer.
17. The method as claimed in any of the preceding claims, wherein the tumour sample is obtained from a fresh tissue sample, a frozen tissue sample or a formalin-fixed, paraffin-embedded tissue sample.
18. The method as claimed in any of the preceding claims, wherein the expression level is determined from tumour cell RNA.
19. The method as claimed in any of the preceding claims, wherein the expression level is determined by reverse phase polymerase chain reaction (RT- PCR).
20. The method of claim 19, wherein said RNA is fragmented.
21 . The method as claimed in any of the preceding claims, wherein the expression levels are determined by microarray analysis.
22. The method as claimed in any of claims 1 to 17, wherein the expression level is determined from protein levels of the biomarkers.
23. The method as claimed in claim 22, wherein the protein levels of the biomarkers are determined using immunohistochemistry.
24. The method as claimed in any of the preceding claims, wherein the PARP inhibitor is selected from the group consisting of: benzamide, quinolone, isoquinolone, benzopyrone, methyl 3,5-diiodo-4-(4'-methoxyphenoxy)benzoate, and methyl-3,5-diiodo-4-(4'-methoxy-3',5'-diiodo-phenoxy)benzoate, cyclic benzamide, benzimidazole and indole.
25. The method as claimed in any of the preceding claims wherein the inhibitor is selected from the group consisting of: 4-[3-(4-cyclopropanecarbonyl-piperazine- 1 -carbonyl)-4-fluoro-benzyl]-2H-phthalazin-1 -one, 4-(4-Fluoro-3-(4- methoxypiperidine-1 -carbonyl)benzyl)phthalazin-1 (2H)-one, 2-{4-[(3S)-Piperidin-3- yl]phenyl}-2H-indazole-7-carboxamide, 8-fluoro-2-{4-
[(methylamino)methyl]phenyl}-1 ,3,4,5-tetrahydro-6H-azepino[5,4,3-cd]indol-6-one, 4-iodo-3-nitrobenzamide, BSI-401 , CEP9881 , INO-1001 , INO-50065 and BSI-101 .
26. The method according to any of the preceding claims, wherein the expression level of each biomarker is normalised by comparison to one or more housekeeping genes.
27. The method of any of the preceding claims, further comprising
administering an amount of a PARP inhibitor to the patient.
28. The method of claim 27, wherein the PARP inhibitor is added after the determination step.
29. A method of treating a patient suffering from cancer comprising determining whether or not the patient will respond favourably to a PARP inhibitor according the method as claimed in any of claims 1 to 26, and administering an effective amount of a PARP inhibitor to said patient if they are identified as likely to be responsive to treatment with a PARP inhibitor.
30. Use of a PARP inhibitor in the manufacture of a medicament for the treatment of patient identified as likely to be responsive to treatment with a PARP inhibitor according to the method of claim 1 to 26.
31 . Use of a PARP inhibitor in the manufacture of a medicament for the treatment of patient with cancer whose cancer cells do not exhibit low expression levels of PARP-1 or MUTYH but do exhibit low expression levels of a homologous recombination repair biomarker selected from: BRCA1 , BRCA2, MDC1 , ATM, ATR, CHEK2 and MRE1 1A.
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