US20100113299A1 - Gene and gene expressed protein targets depicting biomarker patterns and signature sets by tumor type - Google Patents

Gene and gene expressed protein targets depicting biomarker patterns and signature sets by tumor type Download PDF

Info

Publication number
US20100113299A1
US20100113299A1 US12/579,241 US57924109A US2010113299A1 US 20100113299 A1 US20100113299 A1 US 20100113299A1 US 57924109 A US57924109 A US 57924109A US 2010113299 A1 US2010113299 A1 US 2010113299A1
Authority
US
United States
Prior art keywords
gene
determining
expression level
data
identifying
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Abandoned
Application number
US12/579,241
Inventor
Daniel D. Von Hoff
Robert Penny
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Individual
Original Assignee
Individual
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority to US12/579,241 priority Critical patent/US20100113299A1/en
Application filed by Individual filed Critical Individual
Publication of US20100113299A1 publication Critical patent/US20100113299A1/en
Priority to US13/188,350 priority patent/US20120015843A1/en
Priority to US13/942,539 priority patent/US20140018254A1/en
Priority to US14/070,357 priority patent/US20140057986A1/en
Priority to US14/170,370 priority patent/US20140149136A1/en
Priority to US14/170,450 priority patent/US20140149137A1/en
Priority to US14/175,800 priority patent/US9064045B2/en
Priority to US14/175,781 priority patent/US9092392B2/en
Priority to US14/175,728 priority patent/US9053224B2/en
Priority to US14/187,015 priority patent/US9292660B2/en
Priority to US14/187,008 priority patent/US9058418B2/en
Priority to US14/187,020 priority patent/US20140244182A1/en
Priority to US14/187,028 priority patent/US20140244183A1/en
Priority to US14/249,261 priority patent/US9322067B2/en
Priority to US14/551,345 priority patent/US20150080268A1/en
Priority to US14/832,860 priority patent/US20150361508A1/en
Priority to US14/832,873 priority patent/US20160054325A1/en
Priority to US15/093,634 priority patent/US20160224742A1/en
Priority to US15/093,653 priority patent/US20160224725A1/en
Priority to US15/093,668 priority patent/US20160224726A1/en
Priority to US15/094,434 priority patent/US20160224727A1/en
Priority to US15/094,520 priority patent/US20160224747A1/en
Priority to US15/094,457 priority patent/US20160224728A1/en
Priority to US15/094,470 priority patent/US20160224729A1/en
Priority to US15/094,507 priority patent/US20160224746A1/en
Priority to US15/094,486 priority patent/US20160224745A1/en
Priority to US15/099,512 priority patent/US20160232287A1/en
Priority to US15/099,422 priority patent/US20160232283A1/en
Priority to US15/099,517 priority patent/US20160232288A1/en
Priority to US15/099,442 priority patent/US20160232284A1/en
Priority to US15/099,454 priority patent/US20160232285A1/en
Priority to US15/099,530 priority patent/US20160232289A1/en
Priority to US15/099,466 priority patent/US20160232286A1/en
Priority to US15/494,018 priority patent/US20170228522A1/en
Priority to US16/560,999 priority patent/US20200003796A1/en
Priority to US17/835,862 priority patent/US20230123908A1/en
Abandoned legal-status Critical Current

Links

Images

Classifications

    • 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
    • G01N33/57484—Immunoassay; Biospecific binding assay; Materials therefor for cancer involving compounds serving as markers for tumor, cancer, neoplasia, e.g. cellular determinants, receptors, heat shock/stress proteins, A-protein, oligosaccharides, metabolites
    • G01N33/57492—Immunoassay; Biospecific binding assay; Materials therefor for cancer involving compounds serving as markers for tumor, cancer, neoplasia, e.g. cellular determinants, receptors, heat shock/stress proteins, A-protein, oligosaccharides, metabolites involving compounds localized on the membrane of tumor or cancer cells
    • 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
    • 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
    • G01N33/57484—Immunoassay; Biospecific binding assay; Materials therefor for cancer involving compounds serving as markers for tumor, cancer, neoplasia, e.g. cellular determinants, receptors, heat shock/stress proteins, A-protein, oligosaccharides, metabolites
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B50/00—ICT programming tools or database systems specially adapted for bioinformatics
    • G16B50/30—Data warehousing; Computing architectures
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H15/00—ICT specially adapted for medical reports, e.g. generation or transmission thereof
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • 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
    • 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
    • C12Q2600/158—Expression markers
    • 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
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B50/00—ICT programming tools or database systems specially adapted for bioinformatics

Definitions

  • the present invention generally relates to the application of molecular profiling to identify biomarker patterns or biomarker signature sets for specific tumor types or cancers.
  • the present invention also provides a system and method for determining medical intervention for a particular tumor type, cancer, or disease state based on the biomarker patterns or biomarker signature sets.
  • the identification of biomarker patterns or biomarker signature sets can be conducted at any stage of the disease.
  • the present invention relates to the identification of biomarker patterns and biomarker signature sets for advanced stage cancers or diseases by tumor type or tissue type.
  • the present invention also relates to the identification of biomarkers to be used for detecting particular cancers or disease states and efficient detection methods for detecting particular cancers or disease states.
  • Disease states in patients are typically treated with treatment regimens or therapies that are selected based on clinical based criteria; that is, a treatment therapy or regimen is selected for a patient based on the determination that the patient has been diagnosed with a particular disease (which diagnosis has been made from classical diagnostic assays).
  • a treatment therapy or regimen is selected for a patient based on the determination that the patient has been diagnosed with a particular disease (which diagnosis has been made from classical diagnostic assays).
  • Some treatment regimens have been determined using molecular profiling in combination with clinical characterization of a patient such as observations made by a physician (such as a code from the International Classification of Diseases, for example, and the dates such codes were determined), laboratory test results, x-rays, biopsy results, statements made by the patient, and any other medical information typically relied upon by a physician to make a diagnosis in a specific disease.
  • a physician such as a code from the International Classification of Diseases, for example, and the dates such codes were determined
  • laboratory test results x-rays
  • biopsy results biopsy results
  • statements made by the patient and any other medical information typically relied upon by a physician to make a diagnosis in a specific disease.
  • any other medical information typically relied upon by a physician to make a diagnosis in a specific disease such as observations made by a physician (such as a code from the International Classification of Diseases, for example, and the dates such codes were determined), laboratory test results, x-rays, biopsy results, statements made by the patient, and
  • biomarker patterns or biomarker signature sets for specific tumor types or cancers and there is a particular need for drug resistant expression profiles for specific tumor types or cancers.
  • a system and method for determining medical intervention for a particular tumor type, cancer, or disease state based on the biomarker patterns or biomarker signature sets are also a need for determining medical intervention for a particular tumor type, cancer, or disease state based on the biomarker patterns or biomarker signature sets.
  • One aspect of the present invention involves a system and method for determining individualized medical intervention for a particular disease state.
  • One exemplary method for determining medical intervention for a disease state includes the steps of performing a test for a gene and/or a lest for a gene expressed protein from a biological sample of a diseased individual, determining which genes and/or gene expressed proteins exhibited change in expression compared to a reference, and identifying a drug therapy used to interact with the gene and/or gene expressed proteins that exhibited a change of expression that is not single disease restricted.
  • the step of identifying a drug therapy used to interact with a gene and/or gene expressed protein that exhibited a change in expression may include the step of identifying a drug therapy from an automated review of an extensive literature database and/or data generated from clinical trials.
  • the present invention is also directed to identifying biomarker patterns or biomarker signature sets for specific tumor types, cancers, or disease states by performing a test for at least one gene and/or a test for at least one gene expressed protein and determining which genes and/or gene expressed proteins exhibited a change in expression for a particular tumor type or tissue type compared to a normal reference for that particular tissue type.
  • the step of performing a test for at least one gene and/or a test tit east one gene expressed protein may include the step of performing an immunohistochemical (IHC) analysis and/or a micro array analysis.
  • IHC immunohistochemical
  • the step of performing a micro array analysis may include the step of performing an analysis using an expression micro array, a comparative genomic hybridization (CGH) micro array, a single nucleotide polymorphism (SNP) micro array, a fluorescent in-situ hybridization (ISH), an in-situ hybridization (ISH), and a proteomic array.
  • CGH comparative genomic hybridization
  • SNP single nucleotide polymorphism
  • ISH fluorescent in-situ hybridization
  • ISH in-situ hybridization
  • ISH in-situ hybridization
  • proteomic array proteomic array
  • the step of performing an IHC analysis may include the step of performing an IHC analysis for a gene expressed protein which includes at least one of Her2/Neu, FR, PR, c-kit, EGFR, MLH1, MSH2, CD20, p53, Cyclin D1, bcl2, COX-2, Androgen receptor, CD52, PDGFR, AR, CD25, VEGF, HSP90, PTEN, RRM1, SPARC, Survivin, TOP2A, and Topoisomerase II alpha.
  • a gene expressed protein which includes at least one of Her2/Neu, FR, PR, c-kit, EGFR, MLH1, MSH2, CD20, p53, Cyclin D1, bcl2, COX-2, Androgen receptor, CD52, PDGFR, AR, CD25, VEGF, HSP90, PTEN, RRM1, SPARC, Survivin, TOP2A, and Topoisomerase II alpha.
  • the step of performing a micro array analysis in the above-described exemplary method for determining medical intervention for a disease state may include the step of performing a micro array analysis for a gene which includes at least one of BCL2, HIF1A.
  • the step of performing a test for at east one gene and/or a test for at least one gene expressed protein from a biological sample of a diseased individual may include the step of performing an immunohistochemical aria lysis on a tumor and the step of determining which genes and/or gene expressed proteins exhibit a change in expression compared to a reference may include the step of determining whether 30% or more of the tumor cells were +2 or greater staining for a particular gene expressed protein.
  • the step of performing a test for at least one gene and/or a test for at least one gene expressed protein from a biological sample of a diseased individual may include the step of performing a micro array analysis on a tumor and the step of determining which genes and/or gene expressed proteins exhibit a change in expression compared to a reference may include the step of identifying which genes are up-regulated or down-regulated by determining whether the full change of expression for a particular gene relative to a normal tissue of origin reference is significant at p ⁇ 0.001.
  • the method of the present invention for determining individualized medical intervention for a disease state referred to above may also include the step of providing a patient profile report which identifies the change in expression for the genes and/or gene expressed proteins along with a possible drug therapy for interaction with each of the genes and/or gene expressed proteins that exhibit a change in expression.
  • Another exemplary embodiment of the present invention is directed to a method for identifying a drug therapy or protocol capable of interacting with one or more molecular targets which make up a biomarker pattern or biomarker signature set which includes the steps of identifying one or more molecular targets that exhibit a change in expression when compared to a normal reference which make up a biomarker pattern or biomarker signature set in a plurality of individuals having the same tumor type, cancer, or disease state, administrating a drug therapy or protocol to the diseased individuals that exhibit the biomarker pattern or biomarker signature set, and determining any changes in the biomarker pattern or biomarker signature set of the diseased individuals after the drug therapy.
  • the step of identifying one or more molecular targets that exhibit a change in expression when compared to a normal reference which make up a biomarker pattern or biomarker signature set in a plurality of individuals having the same tumor type, cancer, or disease state includes the step of performing a test for at least one gene and or a test for at least one gene expressed protein from a biological sample of the diseased individuals where the test comprises an it immunohistochemical (IHC) analysis and/or a micro array analysis.
  • IHC immunohistochemical
  • a system for determining individualized medical intervention for a disease state
  • the system includes a host server, a user interface for accessing the host server to access and input data, a processor for processing the inputted data, a memory coupled to the processor for storing the processed data and instructions for: a) accessing a molecular profile taken from a biological specimen of a patient b) determining whether at least one of a gene, a gene expressed protein, a molecular mechanism, and other molecular findings resulting from the molecular profile exhibit change in expression compared to a normal reference, and c) accessing a drug therapy database to identify one or more drug therapies that interact with a gene, a gene expressed protein, a molecular mechanism, and/or other molecular findings that exhibited a change in expression, and a display means for displaying a gene, a gene expressed protein, a molecular mechanism, and other molecular findings exhibiting a change in expression and the drug therapies that interact with them
  • the molecular profile taken from the biological specimen may include the same immunohistochemical (IHC) analysis and micro array analysis described above with reference to other exemplary embodiments of the present invention.
  • IHC immunohistochemical
  • micro array analysis described above with reference to other exemplary embodiments of the present invention.
  • the different types of these analyses along with the genes analyzed using these analyses may be the same as those described above with reference to other exemplary embodiments of the present invention.
  • Still another exemplary embodiment of the present invention is directed to a method for determining medical intervention for a disease state which includes the steps of performing at least one molecular test for at least one target from a biological sample of a diseased individual, determining whether the target exhibits a change in expression compared to a reference, and identifying at least one non-disease specific agent that interacts with the target that exhibits a change in expression.
  • the step of identifying at least one non-diseased specific agent that interacts with the target may include the step of identifying a drug therapy from an automated review of an extensive literature base and/or an automated review of data generated from clinical trials, in addition, the exemplary embodiment of the present invention directed to a method thr determining medical intervention for a disease state may also include the step of providing a patient profile report which includes the patient's test results for various targets and any proposed therapies based on those results.
  • the step of performing at least one molecular test for at least one target from a biological sample of a diseased individual in the exemplary embodiment of the present invention directed to a method for determining medical intervention for a disease state may include all of the above-described analyses relating to immunohistochemical (IHC) analysis and micro array analysis and the genes analyzed using those analyses.
  • IHC immunohistochemical
  • FIG. 1 illustrates a block diagram of an exemplary embodiment of a system for determining individualized medical intervention for a particular disease state that utilizes molecular profiling of a patient's biological specimen that is non disease specific.
  • FIG. 2 is a flowchart of an exemplary embodiment of a method for determining individualized medical intervention for a particular disease state that utilizes molecular profiling of a patient's biological specimen that is non disease specific.
  • FIGS. 3A through 3D illustrate an exemplary patient profile report in accordance with step 80 of FIG. 2 .
  • FIG. 4 is a flowchart of an exemplary embodiment of a method for identifying a drug therapy/agent capable of interacting with a target.
  • FIGS. 5-14 are flowcharts and diagrams illustrating various parts of an information-based personalized medicine drug discovery system and method in accordance with the present invention.
  • FIGS. 15-25 are computer screen print outs associated with various parts of the information-based personalized medicine drug discovery system and method shown in FIGS. 5-14 .
  • FIGS. 26A through 26H represent a table that shows the frequency of a significant change in expression of gene expressed proteins by tumor type.
  • FIGS. 27A through 27H represent a table that shows the frequency of a significant change in expression of certain genes by tumor type.
  • FIGS. 28A through 28O represent a table that shows the frequency of a significant change in expression for certain gene expressed proteins by tumor type.
  • FIG. 29 is a table which shows biomarkers (gene expressed proteins) tagged as targets in order of frequency based on FIG. 28 .
  • FIGS. 30A through 30O represent a table that shows the frequency of a significant change in expression for certain genes by tumor type.
  • FIG. 31 is a table which shows genes tagged as targets in order of frequency based on FIG. 30 .
  • a host server or other computing systems including a processor for processing digital data; a memory coupled to the processor for storing digital data; an input digitizer coupled t to the processor for inputting digital data; an application program stored in the memory and accessible by the processor for directing processing of digital data by the processor: a display device coupled to the processor and memory for displaying information derived from digital data processed by the processor; and a plurality of databases.
  • Various databases used herein may include: patient data such as family history, demography and environmental data, biological sample data, prior treatment and protocol data, patient clinical data, molecular profiling data of biological samples, data on therapeutic drug agents and/or investigative drugs, a gene library, a disease library, a drug library, patient tracking data, file management data, financial management data, billing data and/or like data useful in the operation of the system.
  • user computer may include an operating system (e.g., Windows NT, 95/98/2000, OS2, UNIX, Linux, Solaris, MacOS, etc.) as well as various conventional support software and drivers typically associated with computers.
  • the computer may include any suitable personal computer, network computer, workstation, minicomputer, mainframe or the like.
  • User computer can be in a home or medical/business environment with access to a network. In an exemplary embodiment, access is through a network or the Internet through a commercially-available web-browser software package.
  • network shall include any electronic communications means which incorporates both hardware and software components of such. Communication among the parties may be accomplished through any suitable communication channels, such as, for example, a telephone network, an extranet, an intranet, Internet, point of interaction device, personal digital assistant (e.g. Palm Pilot®, Blackberry®), cellular phone, kiosk, etc.), online communications, satellite communications, off-line communications, wireless communications, transponder communications, local area network (LAN), wide area network (WAN), networked or linked devices, keyboard, mouse and/or any suitable communication or data input modality.
  • a telephone network an extranet, an intranet, Internet, point of interaction device, personal digital assistant (e.g. Palm Pilot®, Blackberry®), cellular phone, kiosk, etc.)
  • online communications satellite communications
  • off-line communications wireless communications
  • transponder communications local area network (LAN), wide area network (WAN), networked or linked devices
  • keyboard, mouse and/or any suitable communication or data input modality.
  • the system is frequently described herein as being implemented with TCP/IP communications protocols, the system may also be implemented using IPX, Appletalk, IP-6, NetBIOS, OS1 or any number of existing or future protocols.
  • IPX IPX
  • Appletalk IP-6
  • NetBIOS NetBIOS
  • OS1 any number of existing or future protocols.
  • the network is in the nature of a public network, such as the Internet, it may be advantageous to presume the network to be insecure and open to eavesdroppers. Specific information related to the protocols, standards, and application software utilized in connection with the Internet is generally known to those skilled in the art and, as such, need not be detailed herein.
  • the various system components may be independently, separately or collectively suitably coupled to the network via data links which includes, for example, a connection to an Internet Service Provider (ISP) over the local loop as is typically used in connection with standard modem communication, cable modem.
  • ISP Internet Service Provider
  • Dish networks ISDN, Digital Subscriber Line (DSL), or various wireless communication methods, see, e.g., G ILBERT H ELD , U NDERSTANDING D ATA C OMMUNICATIONS (1996), which is hereby incorporated by reference.
  • the network may be implemented as other types of networks, such as an interactive television (ITV) network.
  • ITV interactive television
  • the system contemplates the use, sale or distribution of any goods, services or information over any network having similar functionality described herein.
  • “transmit” may include sending electronic data from one system component to another over a network connection.
  • “data” may include encompassing information such as commands, queries, files, data for storage, and the like in digital or any other form.
  • the system contemplates uses in association with web services, utility computing, pervasive and individualized computing, security and identity solutions, autonomic computing, commodity computing, mobility and wireless solutions, open source, biometrics, grid computing and/or mesh computing.
  • Any databases discussed herein may include relational, hierarchical, graphical, or object-oriented structure and/or any other database configurations.
  • Common database products that may be used to implement the databases include DB2 by IBM (White Plains, N.Y.), various database products available from Oracle Corporation (Redwood Shores, Calif.), Microsoft Access or Microsoft SQL Server by Microsoft Corporation (Redmond, Wash.), or any other suitable database product.
  • the databases may be organized in any suitable manner, for example, as data tables or lookup tables. Each record may be a single file, a series of files, a linked series of data fields or any other data structure. Association of certain data may be accomplished through any desired data association technique such as those known or practiced in the art. For example, the association may be accomplished either manually or automatically.
  • Automatic association techniques may include, for example, a database search, a database merge, GREP, AGREP, SQL, using a key field in the tables to speed searches, sequential searches through all the tables and files, sorting records in the file according to a known order to simplify lookup, and/or the like.
  • the association step may be accomplished by a database merge function, for example, using a “key field” in pre-selected databases or data sectors.
  • a “key field” partitions the database according to the high-level class of objects defined by the key field. For example, certain types of data may be designated as a key field in a plurality of related data tables and the data tables may then be linked on the basis of the type of data in the key field.
  • the data corresponding to the key field in each of the linked data tables is preferably the same or of the same type.
  • data tables having similar, though not identical, data in the key fields may also be linked by using AGREP, for example.
  • any suitable data storage technique may be utilized to store data without a standard format.
  • Data sets may be stored using any suitable technique, including, for example, storing individual files using an ISO/IEC 7816-4 file structure; implementing a domain whereby a dedicated file is selected that exposes one or more elementary files containing one or more data sets; using data sets stored in individual files using a hierarchical filing system; data sets stored as records in a single file (including compression, SQL accessible, hashed via one or more keys, numeric, alphabetical by first tuple, etc.): Binary Large Object (BLOB); stored as ungrouped data elements encoded using ISO/IEC 7816-6 data elements: stored as ungrouped data elements encoded using ISO/IEC Abstract Syntax Notation (ASN. 1) as in ISO/IEC 8824 and 8825: and/or other proprietary techniques that may include fractal compression methods, image compression methods, etc.
  • BLOB Binary Large Object
  • ASN. 1 ISO/IEC Abstract Syntax Notation
  • the ability to store a wide variety of information in different formats is facilitated by storing the information as a BLOB.
  • any binary information can be stored in a storage space associated with a data set.
  • the BLOB method may store data sets as ungrouped data elements formatted as a block of binary via a fixed memory offset using either fixed storage allocation, circular queue techniques, or best practices with respect to memory management (e.g., paged memory, least recently used, etc.).
  • the ability to store various data sets that have different formats facilitates the storage of data by multiple and unrelated owners of the data sets.
  • a first data set which may be stored may be provided by a first party
  • a second data set which may be stored may be provided by an unrelated second party
  • a third data set which may be stored may be provided by a third party unrelated to the first and second party.
  • Each of these three exemplary data sets may contain different information that is stored using different data storage formats and/or techniques. Further, each data set may contain subsets of data that also may be distinct from other subsets.
  • the data can be stored without regard to a common format.
  • the data set e.g., BLOB
  • the annotation may comprise a short header, trailer, or other appropriate indicator related to each data set, that is configured to convey information useful in managing the various data sets.
  • the annotation may be called a “condition header”, “header”, “trailer”, or “status”, herein, and may comprise an indication of the status of the data set or may include an identifier correlated to a specific issuer or owner of the data. Subsequent bytes of data may be used to indicate for example, the identity of the issuer or owner of the data, user, transaction/membership account identifier or the like.
  • the data set annotation may also be used for other types of status in formation as well as various other purposes.
  • the data set annotation may include security information establishing access levels.
  • the access levels may, for example, be configured to permit only certain individuals, levels of employees, companies, or other entities to access data sets, or to permit access to specific data sets based on the transaction, issuer or owner of data, user or the like.
  • the security information may restrict/permit only certain actions such as accessing, modifying, and/or deleting data sets.
  • the data set annotation indicates that only the data set owner or the user are permitted to delete a data set, various identified users may be permitted to access the data set for reading, and others are altogether excluded from accessing the data set.
  • access restriction parameters may also be used allowing various entities to access a data set with various permission levels as appropriate.
  • the data, including the header or trailer may be received by a stand alone interaction device configured to add, delete, modify, or augment the data in accordance with the header or trailer.
  • any databases, systems, devices, servers or other components of the system may consist of any combination thereof at a single location or at multiple locations, wherein each database or system includes any of various suitable security features, such as firewalls, access codes, encryption, decryption, compression, decompression, and/or the like.
  • the computing unit of the web client may be further equipped with an Internet browser connected to the Internet or an intranet using standard dial-up, cable, DSL or any other Internet protocol known in the art. Transactions originating at a web client may pass through a firewall in order to prevent unauthorized access from users of other networks. Further, additional firewalls may be deployed between the varying components of CMS to further enhance security.
  • Firewall may include any hardware and/or software suitably configured to protect CMS components and/or enterprise computing resources from users of other networks. Further, a firewall may be configured to limit or restrict access to various systems and components behind the firewall for web clients connecting through a web server. Firewall may reside in varying configurations including Stateful Inspection, Proxy based and Packet Filtering among others. Firewall may be integrated within an web server or any other CMS components or may further reside as a separate entity.
  • the computers discussed herein may provide a suitable website or other Internet-based graphical user interface which is accessible by users.
  • the Microsoft Internet Information Server (IIS), Microsoft Transaction Server (MTS), and Microsoft SQL Server are used in conjunction with the Microsoft operating system, Microsoft NT web server software, a Microsoft SQL Server database system, and a Microsoft Commerce Server.
  • components such as Access or Microsoft SQL Server, Oracle, Sybase, Informix My SQL, Interbase, etc., may be used to provide an Active Data Object (ADO) compliant database management system.
  • ADO Active Data Object
  • Any of the communications, inputs, storage, databases or displays discussed herein may be facilitated through a website having web pages.
  • the term “web page” as it is used herein is not meant to limit the type of documents and applications that might be used to interact with the user.
  • a typical website might include, in addition to standard HTML documents, various forms, Java applets, JavaScript, active server pages (ASP), common gateway interface scripts (CGI), extensible markup language (XML), dynamic HTML, cascading style sheets (CSS), helper applications, plug-ins, and the like.
  • a server may include a web service that receives a request from a web server, the request including a URL (http://yahoo.com/stockquotes/ge) and an IP address (123.56.789.234).
  • the web server retrieves the appropriate web pages and sends the data or applications for the web pages to the IP address.
  • Web services are applications that are capable of interacting with other applications over a communications means, such as the internet. Web services are typically based on standards or protocols such as XML, XSLT, SOAP, WSDL and UDDI. Web services methods are well known in the art, and are covered in many standard texts. See e.g., A LEX N GHIEM . IT W EB S ERVICES : A R OADMAP FOR THE E NTERPRISE (2003), hereby incorporated by reference.
  • the web-based clinical database for the system and method of the present invention preferably has the ability to upload and store clinical data files in native formats and is searchable on any clinical parameter.
  • the database is also scalable and may utilize an EAV data model (metadata) to enter clinical annotations from any study for easy integration with other studies.
  • the web-based clinical database is flexible and may be XML and XSLT enabled to be able to add user customized questions dynamically.
  • the database includes exportability to CDISC ODM.
  • Data may be represented as standard text or within a fixed list, scrollable list, drop-down list, editable text field, fixed text field, pop-up window, and the like.
  • methods for modifying data in a web page such as, for example, free text entry using a keyboard, selection of menu items, check boxes, option boxes, and the like.
  • system and method may be described herein in terms of functional block components, screen shots, optional selections and various processing steps. It should be appreciated that such functional blocks may be realized by any number of hardware and/or software components configured to perform the specified functions.
  • the system may employ various integrated circuit components. e.g., memory elements, processing elements, logic elements, look-up tables, and the like, which may carry out a variety of functions under the control of one or more microprocessors or other control devices.
  • the software elements of the system may be implemented with any programming or scripting language such as C, C(++, Macromedia Cold Fusion, Microsoft Active Server Pages, Java, COBOL, assembler, PERL, Visual Basic, SQL Stored Procedures, extensible markup language (XML), with the various algorithms being implemented with any combination of data structures, objects, processes, routines or other programming elements.
  • the system may employ any number of conventional techniques for data transmission, signaling, data processing, network control, and the like.
  • the system could be used to detect or prevent security issues with a client-side scripting language, such as JavaScript, VBScript or the like.
  • the term “end user”, “consumer”, “customer”, “client”, “treating physician”, “hospital”, or “business” may be used interchangeably with each other, and each shall mean any person, entity, machine, hardware, software or business.
  • Each participant is equipped with a computing device in order to interact with the system and facilitate online data access and data input.
  • the customer has a computing unit in the form of a personal computer, although other types of computing units may be used including laptops, notebooks, hand held computers, set-top boxes, cellular telephones, touch-tone telephones and the like.
  • the owner/operator of the system and method of the present invention has a computing unit implemented in the form of a computer-server, although other implementations are contemplated by the system including a computing center shown as a main frame computer a mini-computer, a PC server, a network of computers located in the same of different geographic locations, or the like. Moreover, the system contemplates the use, sale or distribution of any goods, services or information over any network having similar functionality described herein.
  • each client customer may be issued an “account” or “account number”.
  • the account or account number may include any device, code, number, letter, symbol, digital certificate, smart chip, digital signal, analog signal, biometric or other identifier/indicia suitably configured to allow the consumer to access, interact with or communicate with the system (e.g., one or more of an authorization/access code, personal identification number (PIN), Internet code, other identification code, and/or the like).
  • the account number may optionally be located on or associated with a charge card, credit card, debit card, prepaid card, embossed card, smart card magnetic stripe magnetic card, bar code, card, transponder, radio frequency card or an associated account.
  • the system may include or interface with any of the foregoing cards or devices, or a fob having a transponder and RFID reader in RF communication with the fob.
  • the system may include a bob embodiment, the invention is not to be so limited.
  • system may include any device having a transponder which is configured to communicate with RFID reader via RF communication.
  • Typical devices may include, for example, a key ring, tag, card, cell phone, wristwatch or any such firm capable of being presented for interrogation.
  • the system, computing unit or device discussed herein may include a “pervasive computing device,” which may include a traditionally non-computerized device that is embedded with a computing unit.
  • the account number may be distributed and stored in any form of plastic, electronic, magnetic, radio frequency, wireless, audio and/or optical device capable of transmitting or downloading data from itself to a second device.
  • the system may be embodied as a customization of an existing system, an add-on product, upgraded software, a stand alone system, a distributed system, a method, a data processing system, a device for data processing, and/or a computer program product. Accordingly, the system may take the farm of an entirely software embodiment: an entirely hardware embodiment, or an embodiment combining aspects of both software and hardware. Furthermore, the system may take the form of a computer program product on a computer-readable storage medium having computer-readable program code means embodied in the storage medium. Any suitable computer-readable storage medium may be utilized, including hard disks, CD-ROM, optical storage devices, magnetic storage devices, and/or the like.
  • FIGS. 2-25 the process flows and screenshots depicted are merely embodiments and are not intended to limit the scope of the invention as described herein.
  • the steps recited in any of the method or process descriptions may be executed in any order and are not limited to the order presented. It will be appreciated that the following description makes appropriate references not only to the steps and user interface elements depicted in FIGS. 2-25 , but also to the various system components as described above with reference to FIG. 1 .
  • These computer program instructions may be loaded onto a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions that execute on the computer or other programmable data processing apparatus create means for implementing the functions specified in the flowchart block or blocks.
  • These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart block or blocks.
  • the computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks.
  • steps described herein may comprise in any number of con figurations including use of windows, webpages, web forms, popup windows, prompts and the like, it should be further appreciated that the multiple steps as illustrated and described may be combined into single webpages and/or windows but have been expanded for the sake of simplicity. In other cases, steps illustrated and described as single process steps may be separated into multiple webpages and/or windows but have been combined for simplicity.
  • FIG. 1 is a block diagram of an exemplary embodiment of a system 10 for determining individualized medical intervention for a particular disease state that utilizes molecular profiling of a patient's biological specimen.
  • System 10 includes a user interface 12 , a host server 14 including a processor 16 for processing data, a memory 18 coupled to the processor, an application program 20 stored in the memory 18 and accessible by the processor 16 for directing processing of the data by the processor 16 , a plurality of internal databases 22 and external databases 24 , and an interface with a wired or wireless communications network 26 (such as the Internet, for example).
  • System 10 may also include an input digitizer 28 coupled to the processor 16 for inputting digital data from data that is received from user interface 12 .
  • User interface 12 includes an input device 30 and a display 32 for inputting data into system and for displaying information derived from the data processed by processor 16 .
  • User interface 12 may also include a printer 34 for printing the information derived from the data processed by the processor 16 such as patient reports that may include test results for targets and proposed drug therapies based on the test results.
  • Internal databases 22 may include, but are not limited to, patient biological sample/specimen information and tracking, clinical data, patient data, patient tracking, file management, study protocols, patient test results from molecular profiling, and billing information and tracking.
  • External databases 24 may include, but are not limited to, drug libraries, gee libraries, disease libraries, and public and private databases such as UniGene, OMIM, GO, TIGR, GenBank, KEGG and Biocarta.
  • FIG. 2 shows a flowchart of an exemplary embodiment of a method 50 for determining individualized medical intervention for a particular disease state that utilizes molecular profiling of a patient's biological specimen that is non disease specific.
  • at least one test is performed for at least one target from a biological sample of a diseased patient in step 52 .
  • a target is defined as any molecular finding that may be obtained from molecular testing.
  • a target may include one or more genes, one or more gene expressed proteins, one or more molecular mechanisms, and or combinations of such.
  • the expression level of a target can be determined by the analysis of mRNA levels or the target or gene, or protein levels of the gene.
  • Tests for finding such targets may include, but are not limited, fluorescent in-situ hybridization (FISH), an in-situ hybridization (ISH), and other molecular tests known to those skilled in the art.
  • FISH fluorescent in-situ hybridization
  • ISH in-situ hybridization
  • PCR-based methods such as real-time PCR or quantitative PCR can be used.
  • microarray analysis such as a comparative genomic hybridization (CGH) micro array, a single nucleotide polymorphism (SNP) microarray, a proteomic array, or antibody array analysis can also be used in the methods disclosed herein, in some embodiments, microarray analysis comprises identifying whether a gene is up-regulated or down-regulated relative to a reference with a significance of p ⁇ 0.001. Tests or analyses of targets can also comprise immunohistochemical (IHC) analysis. In some embodiments, IHC analysis comprises determining whether 30% or more of a sample is stained, if the staining intensity is +2 or greater, or both.
  • the methods disclosed herein also including profiling more than one target.
  • the expression of a plurality of genes can be identified.
  • identification of a plurality of targets in a sample can be by one method or by various means.
  • the expression of a first gene can be determined by one method and the expression level of a second gene determined by a different method.
  • the same method can be used to detect the expression level of the first and second gene.
  • the first method can be IHC and the second by microarray analysis, such as detecting the gene expression of a gene.
  • molecular profiling can also including identifying a genetic variant, such as a mutation, polymorphism (such as a SNP), deletion, or insertion of a target.
  • identifying a SNP in a gene can be determined by microarray analysis, real-time PCR, or sequencing. Other methods disclosed herein can also be used to identify variants of one or more targets.
  • an IHC analysis in step 54 may be performed: an IHC analysis in step 54 , a microanalysis in step 56 , and other molecular tests know to those skilled in the art in step 58 .
  • Biological samples are obtained from diseased patients by taking a biopsy of a tumor, conducting minimally invasive surgery if no recent tumor is available, obtaining a sample of the patient's blood, or a sample of any other biological fluid including, but not limited to, cell extracts, nuclear extracts, cell lysates or biological products or substances of biological origin such as excretions, blood, sera, plasma, urine, sputum, tears, feces, saliva, membrane extracts, and the like.
  • step 60 a determination is made as to whether one or more of the targets that were tested for in step 52 exhibit a change in expression compared to a normal reference for that particular target.
  • an IHC analysis may be performed in step 54 and a determination as to whether any targets from the IHC analysis exhibit a change in expression is made in step 64 by determining whether 30% or more of the biological sample cells were +2 or greater staining for the particular target. It will be understood by those skilled in the art that there will be instances where +1 or greater staining will indicate a change in expression in that staining results may vary depending on the technician performing the test and type of target being tested.
  • a micro array analysis may be performed in step 56 and a determination as to whether any targets from the micro array analysis exhibit a change in expression is made in step 66 by identifying which targets are up-regulated or down-regulated by determining whether the fold change in expression for a particular target relative to a normal tissue of origin reference is significant at p ⁇ 0.001.
  • a change in expression may also be evidenced by an absence of one or more genes, gene expressed proteins, molecular mechanisms, or other molecular findings.
  • At least one non-disease specific agent is identified that interacts with each target having a changed expression in step 70 .
  • An agent may be any drug or compound having a therapeutic effect.
  • a non-disease specific agent is a therapeutic drug or compound not previously associated with treating the patient's diagnosed disease that is capable of interacting with the target from the patient's biological sample that has exhibited a change in expression.
  • a patient profile report may be provided which includes the patient's test results for various targets and any proposed therapies based on those results.
  • An exemplary patient profile report 100 is shown in FIGS. 3A-3D .
  • Patient profile report 100 shown in FIG. 3A identifies the targets tested 102 , those targets tested that exhibited significant changes in expression 104 , and proposed non-disease specific agents for interacting with the targets 106 .
  • Patient profile report 100 shown in FIG. 3B identifies the results 108 of immunohistochemical analysis for certain gene expressed proteins 110 and whether a gene expressed protein is a molecular target 112 by determining whether 30% or more of the tumor cells were +2 or greater staining. Report 100 also identifies immunohistochemical tests that were not performed 114 .
  • Patient profile report 100 shown in FIG. 3C identifies the genes analyzed 116 with a micro array analysis and whether the genes were under expressed or over expressed 11 compared to a reference.
  • patient profile report 100 shown in FIG. 3D identifies the clinical history 120 of the patient and the specimens that were submitted 122 from the patient.
  • FIG. 4 shows a flowchart of an exemplary embodiment of a method 200 for identifying a drug therapy/agent capable of interacting with a target.
  • a molecular target is identified which exhibits a change in expression in a number of diseased individuals.
  • a drug therapy/agent is administered to the diseased individuals.
  • any changes in the molecular target identified in step 202 are identified in step 206 in order to determine if the drug therapy/agent administered in step 204 interacts with the molecular targets identified in step 202 .
  • the drug therapy/agent administered in step 204 may be approved for treating patients exhibiting a change in expression of the identified molecular target instead of approving the drug therapy/agent for a particular disease.
  • FIGS. 5-14 are flowcharts and diagrams illustrating various parts of an information-based personalized medicine drug discovery system and method in accordance with the present invention.
  • FIG. 5 is a diagram showing an exemplary clinical decision support system of the information-based personalized medicine drug discovery system and method of the present invention.
  • Data obtained through clinical research and clinical care such as clinical trial data, biomedical/molecular imaging data, genomics/proteomics/chemical library/literature/expert curation, biospecimen tracking/LIMS, family history/environmental records, and clinical data are collected and stored as databases and datamarts within a data warehouse.
  • FIG. 6 is a diagram showing the flow of information through the clinical decision support system of the information-based personalized medicine drug discovery system and method of the present invention using web services
  • a user interacts with the system by entering data into the system via form-based entry/upload of data sets, formulating queries and executing data analysis jobs, an a acquiring and evaluating representations of output data.
  • the data warehouse in the web based system is where data is extracted, transformed, and loaded from various database systems.
  • the data warehouse is also where common formats, mapping and transformation occurs.
  • the web based system also includes datamarts which are created based on data views of interest.
  • FIG. 7 A flow chart of an exemplary clinical decision support system of the information-based personalized medicine drug discovery system and method of the present invention is shown in FIG. 7 .
  • the clinical information management system includes the laboratory information management system and the medical information contained in the data warehouses and databases includes medical information libraries, such as drug libraries, gene libraries, and disease libraries, in addition to literature text mining. Both the information management systems relating to particular patients and the medical information databases and data warehouses come together at a data junction center where diagnostic information and therapeutic options can be obtained.
  • a financial management system may also be incorporated in the clinical decision support system of the information-based personalized medicine drug discovery system and method of the present invention.
  • FIG. 8 is a diagram showing an exemplary biospecimen tracking and management system which may be utilized as part of the in formation-based personalized medicine drug discovery system and method of the present invention.
  • FIG. 8 shows two host medical centers which forward specimens to a tissue/blood bank. The specimens may go through laboratory analysis prior to shipment. Research may also be conducted on the samples via micro array, genotyping, and proteomic analysis. This information can be redistributed to, the tissue/blood bank.
  • FIG. 9 depicts a flow chart of an exemplary biospecimen tracking and management system which may be utilized with the information-based personalized medicine drug discovery system and method of the present invention.
  • the host medical center obtains samples from patients and then ships the patient samples to a molecular profiling laboratory which may also perform RNA and DNA isolation and analysis.
  • FIG. 10 A diagram showing a method for maintaining a clinical standardized vocabulary for use with the information-based personalized medicine drug discovery system and method of the present invention is shown in FIG. 10 , FIG. 10 illustrates how physician observations and patient information associated with one physician's patient may be made accessible to another physician to enable the other physician to utilize the data in making diagnostic and therapeutic decisions for their patients.
  • FIG. 11 shows a schematic of an exemplary micro array gene expression database which may be used as part of the information-based personalized medicine drug discovery system and method of the present invention.
  • the micro array gene expression database includes both external databases and internal databases which can be accessed via the web based system.
  • External databases may include, but are not limited to, UniGene, GO, TIGR, GenBank. KEGG.
  • the internal databases may include, but are not limited to, tissue tracking, LIMS, clinical data, and patient tracking.
  • FIG. 12 shows a diagram of an exemplary micro array gene expression database data warehouse which may be used as part of the information-based personalized medicine drug discovery system and method of the present invention.
  • Laboratory data, clinical data, and patient data may all be housed in the micro array gene expression database data warehouse and the data may in turn be accessed by public/private release and utilized by data analysis tools.
  • FIG. 13 Another schematic showing the flow of information through an information-based personalized medicine drug discovery system and method of the present invention is shown in FIG. 13 .
  • the schematic includes clinical information management, medical and literature information management, aid financial management of the information-based personalized medicine drug discovery system and method of the present invention.
  • FIG. 14 is a schematic showing an exemplary network of the information-based personalized medicine drug discovery system and method of the present invention. Patients, medical practitioners, host medical centers, and labs all share and exchange a variety of information in order to provide a patient with a proposed therapy or agent based on various identified targets.
  • FIGS. 15-25 are computer screen print outs associated with various parts of the information-based personalized medicine drug discovery system and method shown in FIGS. 5-14 .
  • FIGS. 15 and 16 show computer screens where physician information and insurance company in formation is entered on behalf of a client.
  • FIGS. 17-19 show computer screens in which information can be entered for ordering analysis and tests on patient samples.
  • FIG. 20 is a computer screen showing micro array analysis results of specific genes tested with patient samples. This information and computer screen is similar to the information detailed in the patient profile report shown in FIG. 3C .
  • FIG. 22 is a computer screen that shows immunohistochemistry test results for a particular patient for various genes. This information is similar to the information contained in the patient profile report shown in FIG. 3B .
  • FIG. 21 is a computer screen showing selection options for finding particular patterns, ordering tests and/or results, issuing patient reports, and tracking current cases/patients.
  • FIG. 23 is a computer screen which outlines some of the steps for creating a patient profile report as shown in FIGS. 3A through 3D .
  • FIG. 24 shows a computer screen for ordering an immunohistochemistry test on a patient sample and
  • FIG. 25 shows a computer screen for entering information regarding a primary tumor site for micro array analysis. It will be understood by those skilled in the art that any number and variety of computer screens may be utilized to enter the in formation necessary tot utilizing the information-based personalized medicine drug discovery system and method of the present invention and to obtain information resulting from utilizing the information-based personalized medicine drug discovery system and method of the present invention.
  • FIGS. 26-31 represent tables that show the frequency of a significant change in expression of certain genes and/or gene expressed proteins by tumor type, i.e. the number of times that a gene and/or gene expressed protein was flagged as a target by tumor type as being significantly overexpressed or underexpressed (see also Examples 1-3).
  • the tables show the total number of times a gene and/or gene expressed protein was overexpressed or underexpressed in a particular tumor type and whether the change in expression was determined by immunohistochemistry analysis ( FIG. 26 , FIG. 28 ) or microarray analysis ( FIGS. 27 , 30 ).
  • the tables also identify the total number of times an overexpression of any gene expressed protein occurred in a particular tumor type using immunohistochemistry and the total number of times an overexpression or underexpression of any gene occurred in a particular tumor type using gene microarray analysis.
  • the present invention provides methods and systems for analyzing diseased tissue using IHC testing and gene microarray testing in accordance with IHC and microarray testing as previously described above.
  • the patients can be in an advanced stage of disease.
  • biomarker patterns or biomarker signature sets in a number of tumor types, diseased tissue types, or diseased cells including accessory, sinuses, middle and inner ear, adrenal glands, appendix, hematopoietic system, bones and joints, spinal cord, breast, cerebellum, cervix uteri, connective and soft tissue, corpus uteri, esophagus, eye, nose, eyeball, fallopian tube, extrahepatic bile ducts, other mouth, intrahepatic bile ducts, kidney, appendix-colon, larynx, lip, liver, hung and bronchus, lymph nodes, cerebral, spinal, nasal cartilage, excl.
  • biomarker patterns or biomarker signature sets can be used to determine a therapeutic agent or therapeutic protocol that is capable of interacting with the biomarker pattern or signature set.
  • a therapeutic agent or therapeutic protocol can be identified which is capable of interacting with the biomarker pattern or signature set.
  • biomarker patterns or biomarker signature sets for advanced stage breast cancer are just one example of the extensive number of biomarker patterns or biomarker signature sets for a number of advanced stage diseases or cancers that can be identified from the tables depicted in FIGS. 26-31 .
  • a number of non disease specific therapies or therapeutic protocols may be identified for treating patients with these biomarker patterns or biomarker signature sets by utilizing method steps of the present invention described above such as depicted in FIGS. 1-2 and FIGS. 5-14 .
  • the biomarker patterns and/or biomarker signature sets disclosed in the table depicted in FIGS. 26 and 28 , and the tables depicted in FIGS. 27 and 30 may be used for a number of purposes including, but not limited to, specific cancer/disease detection, specific cancer/disease treatment, and identification of new drug therapies or protocols for specific cancers/diseases.
  • the biomarker patterns and/or biomarker signature sets disclosed in the table depicted in FIGS. 26 and 28 , and the tables depicted in FIGS. 27 and 30 can also represent drug resistant expression profiles for the specific tumor type or cancer type.
  • the biomarker patterns and/or biomarker signature sets disclosed in the table depicted in FIGS. 26 and 28 , and the tables depicted in FIGS. 27 and 30 represent advanced stage drug resistant profiles.
  • the biomarker patterns and/or biomarker signature sets can comprise at least one biomarker.
  • the biomarker patterns or signature sets can comprise at least 2, 3, 4, 5, 6, 7, 8, 9, or 10 biomarkers.
  • the biomarker signature sets or biomarker patterns can comprise at least 15, 20, 30, 40, 50, or 60 biomarkers.
  • Analysis of the one or more biomarkers can be by one or more methods. For example, analysis of 2 biomarkers can be performed using microarrays. Alternatively, one biomarker may be analyzed by IHC and another by microarray. Various combinations of methods and biomarkers are contemplated herein.
  • the one or more biomarkers can be selected from the group consisting of but not limited to Her2/Neu, ER, PR, c-kit, EGFR, MLH1, MSH2, CD20, p53, Cychn D1, bcl2, COX-2, Androgen receptor, CD52, PDGFR, AR, CD25, VEGF, HSP90, PTEN, RRM1, SPARC, Survivin, TOP2A, BCL2, HIF1A, AR, ESR1, PDGFRA, KIT, PDGFRB, CDW52, ZAP70, PGR, SPARC, GART, GSTP1, NFKB1A, MSH2, TXNRD1, HDAC1, PDGFC, PTEN, CD33, TYMS, RXRB, ADA, TNF, ERCC3, RAF1, VEGF, TOP1, TOP2A, BRCA2, TK1, FOLR2, TOP2B, MLH1, IL2RA, DNMT1, HSPCA, ERBR2, ERBB2, SSTR1, V
  • a biological sample from an individual can be analyzed to determine a biomarker pattern or biomarker signature set that comprises a biomarker such as HSP90, Survivin, RRM1, SSTRS3, DNMT3B, VEGFA, SSTR4, RRM2, SRC, RRM2B, HSP90AA1, STR2, FLIT, SSTR5, YES1, BiRCA1, RRM1, DHFR, KDR, EPHA2, RXRG, or LCK.
  • the biomarker SPARC, HSP90, TOP2A, PTEN, Survivin, or RRM1 forms part of the biomarker pattern or biomarker signature set.
  • the biomarker MGMT, SSTRS3, DNMNT3B, VEGFA, SSTR4, RRM2, SRC, RRMB, HSP90AA1, STR2, FTL1, SSTR5, YES1, SRCA1, RRM1, DHFR, KDR, EPHA2, RXRG, CD52, or LCK is included in a biomarker pattern or biomarker signature set.
  • STR2, FLT1, SSTR5, YES1, BRCA1, RRM1, DHFR KDR, EPHA2, RXRG, or LCK can be determined and used to identify a therapeutic for an individual.
  • the expression level of the biomarker can be used to form a biomarker pattern or biomarker signature set. Determining the expression level can be by analyzing the levels of mRNA or protein, such as by microarray analysis or IHC.
  • the expression level of a biomarker is performed by IHC, such as for SPARC, TOP2A, or PTEN, and used to identify a therapeutic for an individual.
  • the results of the IHC can be used to form a biomarker pattern or biomarker signature set.
  • a biological sample from an individual or subject is analyzed for the expression level of CD52, such as by determining the mRNA expression level by methods including, but not limited to, microarray analysis.
  • the expression level of CD52 can be used to identify a therapeutic for the individual.
  • the expression level of CD52 can be used to firm a biomarker pattern or biomarker signature set.
  • the molecular profiling of one or more targets can be used to determine or identify a therapeutic for an individual.
  • the expression level of one or more biomarkers can be used to determine or identify a therapeutic for an individual.
  • the one or more biomarkers such as those disclosed herein, can be used to form a biomarker pattern or biomarker signature set, which is used to identify a therapeutic for an individual.
  • the therapeutic identified is one that the individual has not previously been treated with.
  • a reference biomarker pattern has been established for a particular therapeutic, such that individuals with the reference biomarker pattern will be responsive to that therapeutic.
  • An individual with a biomarker pattern that differs from the reference for example the expression of a gene in the biomarker pattern is changed or different from that of the reference, would not be administered that therapeutic, in another example, an individual exhibiting a biomarker pattern that is the same or substantially the same as the reference is advised to be treated with that therapeutic.
  • the individual has not previously been treated with that therapeutic and thus a new therapeutic has been identified for the individual.
  • FIGS. 26A-H and FIGS. 27A-27H relate to 544 patients whose diseased tissue underwent IHC testing ( FIG. 26 ) and 540 patients whose diseased tissue underwent gene microarray testing ( FIG. 27 ) in accordance with IHC and microarray testing as previously described above. The patients were all in advanced stages of disease.
  • the data show biomarker patterns or biomarker signature sets in a number of tumor types, diseased tissue types, or diseased cells including adipose, adrenal cortex, adrenal gland, adrenal gland—medulla, appendix, bladder, blood vessel, bone, bone cartilage, brain, breast, cartilage, cervix, colon, colon sigmoid, dendritic cells, skeletal muscle, endometrium, esophagus, fallopian tube, fibroblast, gallbladder, kidney, larynx, liver, lung, lymph node, melanocytes, mesothelial lining, myoepithelial cells, osteoblasts, ovary, pancreas, parotid, prostate, salivary gland, sinus tissue, skeletal muscle, skin, small intestine, smooth muscle, stomach, synovium joint lining tissue, tendon, testis, thymus, thyroid, uterus, and uterus corpus.
  • adipose adrenal cortex, adrenal gland, adrenal gland—medul
  • a biomarker pattern or biomarker signature set can be identified for advanced stage breast cancer and a therapeutic agent or therapeutic protocol can be identified which is capable of interacting with the biomarker pattern or signature set.
  • FIGS. 27A-H Another biomarker pattern or biomarker signature set for advanced stage breast cancer is shown from the microarray data in the table represented by FIGS. 27A-H .
  • FIGS. 27A-H Another biomarker pattern or biomarker signature set for advanced stage breast cancer is shown from the microarray data in the table represented by FIGS. 27A-H .
  • FIGS. 27A-H Another biomarker pattern or biomarker signature set for advanced stage breast cancer is shown from the microarray data in the table represented by FIGS. 27A-H .
  • FIGS. 27A-H Another biomarker pattern or biomarker signature set for advanced stage breast cancer is shown from the microarray data in the table represented by FIGS. 27A-H .
  • FIGS. 28A through 28O represent a table that shows the frequency of a significant change in expression of certain gene expressed proteins by tumor type, the number of times that a gene expressed protein was flagged as a target by tumor type as being significantly overexpressed by immunohistochemistry analysis. The table also identifies the total number of times an overexpression of any gene expressed protein occurred in a particular tumor type using immunohistochemistry.
  • the data reflected in the table depicted in FIGS. 28A through 28O relates to 1392 patients whose diseased tissue underwent IHC testing in accordance with IHC testing as previously described above. The patients were all in advanced stages of disease.
  • the data show biomarker patterns or biomarker signature sets in a number of tumor types, diseased tissue types, or diseased cells including accessory, sinuses, middle and inner ear, adrenal glands, appendix, hematopoietic system, bones and joints, spinal cord, breast, cerebellum, cervix uteri, connective and soil tissue, corpus uteri, esophagus, eye, nose, eyeball, fallopian tube, extrahepatic bile ducts, other mouth, intrahepatic bile ducts, kidney, appendix-colon, larynx, lip, liver, lung and bronchus, lymph nodes, cerebral, spinal nasal cartilage, excl.
  • a biomarker pattern or biomarker signature set can be identified for advanced stage breast cancer and a therapeutic agent or therapeutic protocol can be identified which is capable of interacting with the biomarker pattern or signature set.
  • FIG. 29 depicts a table showing biomarkers (gene expressed proteins) tagged as targets in order of frequency in all tissues that were IHC tested. Immunohistochemistry of the 19 gene expressed proteins showed that the 19 gene expressed proteins were tagged 3878 times as targets in the various tissues tested and that EGFR was the gene expressed protein that was overexpressed the most frequently followed by SPARC.
  • FIGS. 30A through 30O represent a table that shows the frequency of a significant change in expression of certain genes by tumor type, i.e. the number of times that a gene was flagged as a target by tumor type as being significantly overexpressed or underexpressed by microarray analysis.
  • the table also identifies the total number of lines an overexpression or underexpression of any gene occurred in a particular tumor type using gene microarray analysis.
  • the data reflected in the table depicted in FIGS. 30A through 30O relates to 379 patients whose diseased tissue underwent gene microarray testing in accordance microarray testing as previously described above.
  • the patients were all in advanced stages of disease.
  • the data show biomarker patterns or biomarker signature sets in a number of tumor types, diseased tissue types, or diseased cells including accessory, sinuses, middle and inner ear, adrenal glands, anal canal and anus, appendix, blood, bone marrow & hematopoietic sys, bones and joints, brain & cranial nerves and spinal cord (excl.
  • ventricle & cerebellum breast, cerebellum, cervix, uteri connective & soft tissue, corpus uteri, esophagus, eye, nos, eyeball, fallopian tube, gallbladder 7 extrahepatic bile ducts, gum, floor of mouth & other mouth, intrahepatic bile ducts, kidney, large intestine (excl. appendix-colon), larynx, lip, liver, lung & bronchus, lymph nodes, meninges (cerebral, spinal, nasal cavity (including nasal cartilage), orbit & lacrimal gland (excl.
  • retina, eye, nos), oropharynx other endocrine glands, other female genital, ovary, pancreas, penis & scrotum, pituitary gland, pleura, prostate gland, rectum, renal pelvis & ureter, retroperitoneum & peritoneum, salivary gland, skin, small intestine, stomach, testis, thymus, thyroid gland, tongue, unknown, unspecified digestive organs, urinary bladder, uterus, nos, vagina & labia, and vulva, nos.
  • microarray analysis of 63 genes showed that the genes analyzed were either overexpressed or underexpressed a total of 1863 times and that 5.05% of that total change in expression was attributable to SSTR3 change in expression followed by 4.83% of the change in expression being attributable to NKFB1A change in expression and 4.62% of the change in expression being attributable to VDR.
  • 4.35% of the change in expression was attributable to MGMT change in expression
  • 4.19% of the change in expression was attributable to ADA change in expression
  • 3.97% of the change in expression was attributable to CES2 change in expression.
  • FIG. 31 depicts a table showing biomarkers as targets in order of frequency in all tissues that were tested.

Abstract

Provided herein are methods and systems for identifying a therapeutic for an individual, such as a therapeutic not previously identified for treating the individual. The therapeutic can be identified by molecular profiling, such as determining the biomarker patterns or signature sets of a biological sample of an individual.

Description

    RELATED APPLICATIONS
  • This application claims the benefit of U.S. provisional applications 61/105,335, filed Oct. 14, 2008 and 61/106,921, filed Oct. 20, 2008, both of which are incorporated herein in its entirety.
    • FIELD OF INVENTION
  • The present invention generally relates to the application of molecular profiling to identify biomarker patterns or biomarker signature sets for specific tumor types or cancers. The present invention also provides a system and method for determining medical intervention for a particular tumor type, cancer, or disease state based on the biomarker patterns or biomarker signature sets. The identification of biomarker patterns or biomarker signature sets can be conducted at any stage of the disease. In particular, the present invention relates to the identification of biomarker patterns and biomarker signature sets for advanced stage cancers or diseases by tumor type or tissue type. The present invention also relates to the identification of biomarkers to be used for detecting particular cancers or disease states and efficient detection methods for detecting particular cancers or disease states.
    • BACKGROUND
  • Disease states in patients are typically treated with treatment regimens or therapies that are selected based on clinical based criteria; that is, a treatment therapy or regimen is selected for a patient based on the determination that the patient has been diagnosed with a particular disease (which diagnosis has been made from classical diagnostic assays). Although the molecular mechanisms behind various disease states have been the subject of studies for years, the specific application of a diseased individual's molecular profile in determining treatment regimens and therapies for that individual has been disease specific and not widely pursued.
  • Some treatment regimens have been determined using molecular profiling in combination with clinical characterization of a patient such as observations made by a physician (such as a code from the International Classification of Diseases, for example, and the dates such codes were determined), laboratory test results, x-rays, biopsy results, statements made by the patient, and any other medical information typically relied upon by a physician to make a diagnosis in a specific disease. However, using a combination of selection material based on molecular profiling and clinical characterizations (such as the diagnosis of a particular type of cancer) to determine a treatment regimen or therapy presents a risk that an effective treatment regimen may be overlooked for a particular individual since some treatment regimens may work well for different disease states even though they are associated with treating a particular type of disease state.
  • Patients with metastatic cancer are of particular concern for treating physicians. The majority of patients with metastatic cancer eventually run out of treatment options for their tumors. These patients have very limited options a ter their tumor has progressed on standard front line and second line (and sometimes third line and beyond) therapies. Although these patients may participate in Phase I and Phase II clinical trials for new anticancer agents, they must usually meet very strict eligibility criteria to do so. Studies have shown that when patients participate in these types of trials, the new anticancer agent may give response rates of anywhere from 5% to 10% on average in Phase I settings to 12% in Phase II settings. These patients also have the option of electing to receive the best supportive care to treat their symptoms.
  • There has recently been an explosion of interest in developing new anticancer agents that are more targeted against a cell surface receptor or an up regulated or amplified gene product. This approach has met with some success (e.g. Herceptin against HER2/neu in breast cancer cells, rituximab against CD20 in lymphoma cells, bevacizamab against VEGF, Cetuximab against EGFR, etc.). However, patients' tumors still eventually progress on these therapies. If a larger number of targets or molecular findings such as molecular mechanisms, genes, gene expressed proteins, and/or combinations of such were measured in a patient's tumor, one may find additional targets or molecular findings that can be exploited by using specific therapeutic agents. Identifying multiple agents that can treat multiple targets or underlying mechanisms would provide a metastatic cancer patient with a viable therapeutic alternative to those treatment regimens which currently exist.
  • Accordingly, there is a need for the identification of biomarker patterns or biomarker signature sets for specific tumor types or cancers and there is a particular need for drug resistant expression profiles for specific tumor types or cancers. There is also a need for a system and method for determining medical intervention for a particular tumor type, cancer, or disease state based on the biomarker patterns or biomarker signature sets.
    • SUMMARY
  • One aspect of the present invention involves a system and method for determining individualized medical intervention for a particular disease state. One exemplary method for determining medical intervention for a disease state includes the steps of performing a test for a gene and/or a lest for a gene expressed protein from a biological sample of a diseased individual, determining which genes and/or gene expressed proteins exhibited change in expression compared to a reference, and identifying a drug therapy used to interact with the gene and/or gene expressed proteins that exhibited a change of expression that is not single disease restricted. In one aspect of this exemplary embodiment of the invention, the step of identifying a drug therapy used to interact with a gene and/or gene expressed protein that exhibited a change in expression may include the step of identifying a drug therapy from an automated review of an extensive literature database and/or data generated from clinical trials.
  • The present invention is also directed to identifying biomarker patterns or biomarker signature sets for specific tumor types, cancers, or disease states by performing a test for at least one gene and/or a test for at least one gene expressed protein and determining which genes and/or gene expressed proteins exhibited a change in expression for a particular tumor type or tissue type compared to a normal reference for that particular tissue type. The step of performing a test for at least one gene and/or a test tit east one gene expressed protein may include the step of performing an immunohistochemical (IHC) analysis and/or a micro array analysis.
  • Further, the step of performing a micro array analysis may include the step of performing an analysis using an expression micro array, a comparative genomic hybridization (CGH) micro array, a single nucleotide polymorphism (SNP) micro array, a fluorescent in-situ hybridization (ISH), an in-situ hybridization (ISH), and a proteomic array. In addition, the step of performing an IHC analysis may include the step of performing an IHC analysis for a gene expressed protein which includes at least one of Her2/Neu, FR, PR, c-kit, EGFR, MLH1, MSH2, CD20, p53, Cyclin D1, bcl2, COX-2, Androgen receptor, CD52, PDGFR, AR, CD25, VEGF, HSP90, PTEN, RRM1, SPARC, Survivin, TOP2A, and Topoisomerase II alpha.
  • In another aspect of the invention, the step of performing a micro array analysis in the above-described exemplary method for determining medical intervention for a disease state may include the step of performing a micro array analysis for a gene which includes at least one of BCL2, HIF1A. AR, ESR1, PDGFRA, KIT, PDGFRB, CDW52, ZAP70, PGR, SPARC, GART, GSTP1, NFKB1A, MSH2, TXNRD1, IHDAC, PDGFC, PTEN, CD33, TYMS, RXRB, ADA, TNF, ERCC3, RAF1, VEGF, TOP1, TOP2A, BRCA2, TK1, POLR2, TOP2B, MLH1, IL2RA, DNMT1, HSPCA, ERBR2, ERBB2, SSTR1, VHL, VDR, PTGS2, POLA, CES2, EGFR, OGFR, ASNS, NFKB2, RARA, MS4A1, DCK, DNMT3A, EREG, Epiregulin, FOLR1, GNRH1, GNRHR1, FSHB, FSHR, FSHPRH1, folate receptor, HGF, HIG1, IL13RA1, LTB, ODC1, PPARG, PPARGC1, Lymphotoxin Beta Receptor, Myc, Topoisomerase II, TOPO2B, TXN, VEGFC, ACE2, ADH1C, ADH4, AGT, AREG, CA2, CDK2, caveolin, NFKB1, ASNS, BDCA1, CD52, DHFR, DNMT3B, EPHA2, FLT1, HSP90AA1, KDR, LCK, MGMT, RRM1, RRM2, RXRG, SRC, SSTR SSTR2, SSTR3, SSTR4, SSTR5, VEGFA, and YES1.
  • In yet another aspect of the above-described exemplary method of the present invention, the step of performing a test for at east one gene and/or a test for at least one gene expressed protein from a biological sample of a diseased individual may include the step of performing an immunohistochemical aria lysis on a tumor and the step of determining which genes and/or gene expressed proteins exhibit a change in expression compared to a reference may include the step of determining whether 30% or more of the tumor cells were +2 or greater staining for a particular gene expressed protein. In still another aspect of the above-described exemplary method of the present invention, the step of performing a test for at least one gene and/or a test for at least one gene expressed protein from a biological sample of a diseased individual may include the step of performing a micro array analysis on a tumor and the step of determining which genes and/or gene expressed proteins exhibit a change in expression compared to a reference may include the step of identifying which genes are up-regulated or down-regulated by determining whether the full change of expression for a particular gene relative to a normal tissue of origin reference is significant at p<0.001.
  • The method of the present invention for determining individualized medical intervention for a disease state referred to above may also include the step of providing a patient profile report which identifies the change in expression for the genes and/or gene expressed proteins along with a possible drug therapy for interaction with each of the genes and/or gene expressed proteins that exhibit a change in expression.
  • Another exemplary embodiment of the present invention is directed to a method for identifying a drug therapy or protocol capable of interacting with one or more molecular targets which make up a biomarker pattern or biomarker signature set which includes the steps of identifying one or more molecular targets that exhibit a change in expression when compared to a normal reference which make up a biomarker pattern or biomarker signature set in a plurality of individuals having the same tumor type, cancer, or disease state, administrating a drug therapy or protocol to the diseased individuals that exhibit the biomarker pattern or biomarker signature set, and determining any changes in the biomarker pattern or biomarker signature set of the diseased individuals after the drug therapy. Further, in one aspect of this exemplary embodiment of a method for identifying a drug therapy or protocol capable of interacting with one or more molecular targets, the step of identifying one or more molecular targets that exhibit a change in expression when compared to a normal reference which make up a biomarker pattern or biomarker signature set in a plurality of individuals having the same tumor type, cancer, or disease state includes the step of performing a test for at least one gene and or a test for at least one gene expressed protein from a biological sample of the diseased individuals where the test comprises an it immunohistochemical (IHC) analysis and/or a micro array analysis.
  • In yet another exemplary embodiment of the present invention, a system is provided for determining individualized medical intervention for a disease state where the system includes a host server, a user interface for accessing the host server to access and input data, a processor for processing the inputted data, a memory coupled to the processor for storing the processed data and instructions for: a) accessing a molecular profile taken from a biological specimen of a patient b) determining whether at least one of a gene, a gene expressed protein, a molecular mechanism, and other molecular findings resulting from the molecular profile exhibit change in expression compared to a normal reference, and c) accessing a drug therapy database to identify one or more drug therapies that interact with a gene, a gene expressed protein, a molecular mechanism, and/or other molecular findings that exhibited a change in expression, and a display means for displaying a gene, a gene expressed protein, a molecular mechanism, and other molecular findings exhibiting a change in expression and the drug therapies that interact with them. With respect to the exemplary embodiment of the present invention directed to the system for determining individualized medical intervention for a disease state, the molecular profile taken from the biological specimen may include the same immunohistochemical (IHC) analysis and micro array analysis described above with reference to other exemplary embodiments of the present invention. In addition, the different types of these analyses along with the genes analyzed using these analyses may be the same as those described above with reference to other exemplary embodiments of the present invention.
  • Still another exemplary embodiment of the present invention is directed to a method for determining medical intervention for a disease state which includes the steps of performing at least one molecular test for at least one target from a biological sample of a diseased individual, determining whether the target exhibits a change in expression compared to a reference, and identifying at least one non-disease specific agent that interacts with the target that exhibits a change in expression. The step of identifying at least one non-diseased specific agent that interacts with the target may include the step of identifying a drug therapy from an automated review of an extensive literature base and/or an automated review of data generated from clinical trials, in addition, the exemplary embodiment of the present invention directed to a method thr determining medical intervention for a disease state may also include the step of providing a patient profile report which includes the patient's test results for various targets and any proposed therapies based on those results.
  • The step of performing at least one molecular test for at least one target from a biological sample of a diseased individual in the exemplary embodiment of the present invention directed to a method for determining medical intervention for a disease state may include all of the above-described analyses relating to immunohistochemical (IHC) analysis and micro array analysis and the genes analyzed using those analyses.
    • BRIEF DESCRIPTION OF THE DRAWINGS
  • FIG. 1 illustrates a block diagram of an exemplary embodiment of a system for determining individualized medical intervention for a particular disease state that utilizes molecular profiling of a patient's biological specimen that is non disease specific.
  • FIG. 2 is a flowchart of an exemplary embodiment of a method for determining individualized medical intervention for a particular disease state that utilizes molecular profiling of a patient's biological specimen that is non disease specific.
  • FIGS. 3A through 3D illustrate an exemplary patient profile report in accordance with step 80 of FIG. 2.
  • FIG. 4 is a flowchart of an exemplary embodiment of a method for identifying a drug therapy/agent capable of interacting with a target.
  • FIGS. 5-14 are flowcharts and diagrams illustrating various parts of an information-based personalized medicine drug discovery system and method in accordance with the present invention.
  • FIGS. 15-25 are computer screen print outs associated with various parts of the information-based personalized medicine drug discovery system and method shown in FIGS. 5-14.
  • FIGS. 26A through 26H represent a table that shows the frequency of a significant change in expression of gene expressed proteins by tumor type.
  • FIGS. 27A through 27H represent a table that shows the frequency of a significant change in expression of certain genes by tumor type.
  • FIGS. 28A through 28O represent a table that shows the frequency of a significant change in expression for certain gene expressed proteins by tumor type.
  • FIG. 29 is a table which shows biomarkers (gene expressed proteins) tagged as targets in order of frequency based on FIG. 28.
  • FIGS. 30A through 30O represent a table that shows the frequency of a significant change in expression for certain genes by tumor type.
  • FIG. 31 is a table which shows genes tagged as targets in order of frequency based on FIG. 30.
    •  DETAILED DESCRIPTION
  • The detailed description of exemplary embodiments herein makes reference to the accompanying drawings and pictures which show the exemplary embodiment by way of illustration and its best mode. While these exemplary embodiments are described in sufficient detail to enable those skilled in the art to practice the invention, it should be understood that other embodiments may be realized and that logical and mechanical changes may be made without departing from the spirit and scope of the invention. Thus, the detailed description herein is presented for purposes of illustration only and not of limitation. For example, the steps recited in any of the method or process descriptions my be executed in any order and are not limited to the order presented. Moreover, any of the functions or steps may be outsourced to or performed by one or more third parties. Furthermore, any reference to singular includes plural embodiments, and any reference to more than one component may include a singular embodiment.
  • For the sake of brevity, conventional data networking, application development and other functional aspects of the systems (and components of the individual operating components of the systems) may not be described in detail herein. Furthermore, the connecting lines shown in the various figures contained herein are intended to represent exemplary functional relationships and/or physical couplings between the various elements. It should be noted that many alternative or additional functional relationships or physical connections may be present in a practical system.
  • The various system components discussed herein may include one or more of the following: a host server or other computing systems including a processor for processing digital data; a memory coupled to the processor for storing digital data; an input digitizer coupled t to the processor for inputting digital data; an application program stored in the memory and accessible by the processor for directing processing of digital data by the processor: a display device coupled to the processor and memory for displaying information derived from digital data processed by the processor; and a plurality of databases. Various databases used herein may include: patient data such as family history, demography and environmental data, biological sample data, prior treatment and protocol data, patient clinical data, molecular profiling data of biological samples, data on therapeutic drug agents and/or investigative drugs, a gene library, a disease library, a drug library, patient tracking data, file management data, financial management data, billing data and/or like data useful in the operation of the system. As those skilled in the art will appreciate, user computer may include an operating system (e.g., Windows NT, 95/98/2000, OS2, UNIX, Linux, Solaris, MacOS, etc.) as well as various conventional support software and drivers typically associated with computers. The computer may include any suitable personal computer, network computer, workstation, minicomputer, mainframe or the like. User computer can be in a home or medical/business environment with access to a network. In an exemplary embodiment, access is through a network or the Internet through a commercially-available web-browser software package.
  • As used herein, the term “network” shall include any electronic communications means which incorporates both hardware and software components of such. Communication among the parties may be accomplished through any suitable communication channels, such as, for example, a telephone network, an extranet, an intranet, Internet, point of interaction device, personal digital assistant (e.g. Palm Pilot®, Blackberry®), cellular phone, kiosk, etc.), online communications, satellite communications, off-line communications, wireless communications, transponder communications, local area network (LAN), wide area network (WAN), networked or linked devices, keyboard, mouse and/or any suitable communication or data input modality. Moreover, although the system is frequently described herein as being implemented with TCP/IP communications protocols, the system may also be implemented using IPX, Appletalk, IP-6, NetBIOS, OS1 or any number of existing or future protocols. If the network is in the nature of a public network, such as the Internet, it may be advantageous to presume the network to be insecure and open to eavesdroppers. Specific information related to the protocols, standards, and application software utilized in connection with the Internet is generally known to those skilled in the art and, as such, need not be detailed herein. See, for example, DILIP NAIK, INTERNET STANDARDS AND PROTOCOLS (1998); JAVA 2 COMPLETE, various authors, (Sybex 1999); DEBORAH RAY AND ERIC RAY, MASTERING HTML 4.0 (1997); and LOSHIN, TCP/IP CLEARLY EXPLAINED (1997) and DAVID GOURLEY AND BRIAN TOTTY, HTTP, THE DEFINITIVE GUIDE (2002), the contents of which are hereby incorporated by reference.
  • The various system components may be independently, separately or collectively suitably coupled to the network via data links which includes, for example, a connection to an Internet Service Provider (ISP) over the local loop as is typically used in connection with standard modem communication, cable modem. Dish networks, ISDN, Digital Subscriber Line (DSL), or various wireless communication methods, see, e.g., GILBERT HELD, UNDERSTANDING DATA COMMUNICATIONS (1996), which is hereby incorporated by reference. It is noted that the network may be implemented as other types of networks, such as an interactive television (ITV) network. Moreover, the system contemplates the use, sale or distribution of any goods, services or information over any network having similar functionality described herein.
  • As used herein, “transmit” may include sending electronic data from one system component to another over a network connection. Additionally, as used herein, “data” may include encompassing information such as commands, queries, files, data for storage, and the like in digital or any other form.
  • The system contemplates uses in association with web services, utility computing, pervasive and individualized computing, security and identity solutions, autonomic computing, commodity computing, mobility and wireless solutions, open source, biometrics, grid computing and/or mesh computing.
  • Any databases discussed herein may include relational, hierarchical, graphical, or object-oriented structure and/or any other database configurations. Common database products that may be used to implement the databases include DB2 by IBM (White Plains, N.Y.), various database products available from Oracle Corporation (Redwood Shores, Calif.), Microsoft Access or Microsoft SQL Server by Microsoft Corporation (Redmond, Wash.), or any other suitable database product. Moreover, the databases may be organized in any suitable manner, for example, as data tables or lookup tables. Each record may be a single file, a series of files, a linked series of data fields or any other data structure. Association of certain data may be accomplished through any desired data association technique such as those known or practiced in the art. For example, the association may be accomplished either manually or automatically. Automatic association techniques may include, for example, a database search, a database merge, GREP, AGREP, SQL, using a key field in the tables to speed searches, sequential searches through all the tables and files, sorting records in the file according to a known order to simplify lookup, and/or the like. The association step may be accomplished by a database merge function, for example, using a “key field” in pre-selected databases or data sectors.
  • More particularly, a “key field” partitions the database according to the high-level class of objects defined by the key field. For example, certain types of data may be designated as a key field in a plurality of related data tables and the data tables may then be linked on the basis of the type of data in the key field. The data corresponding to the key field in each of the linked data tables is preferably the same or of the same type. However, data tables having similar, though not identical, data in the key fields may also be linked by using AGREP, for example. In accordance with one embodiment, any suitable data storage technique may be utilized to store data without a standard format. Data sets may be stored using any suitable technique, including, for example, storing individual files using an ISO/IEC 7816-4 file structure; implementing a domain whereby a dedicated file is selected that exposes one or more elementary files containing one or more data sets; using data sets stored in individual files using a hierarchical filing system; data sets stored as records in a single file (including compression, SQL accessible, hashed via one or more keys, numeric, alphabetical by first tuple, etc.): Binary Large Object (BLOB); stored as ungrouped data elements encoded using ISO/IEC 7816-6 data elements: stored as ungrouped data elements encoded using ISO/IEC Abstract Syntax Notation (ASN. 1) as in ISO/IEC 8824 and 8825: and/or other proprietary techniques that may include fractal compression methods, image compression methods, etc.
  • In one exemplary embodiment, the ability to store a wide variety of information in different formats is facilitated by storing the information as a BLOB. Thus, any binary information can be stored in a storage space associated with a data set. The BLOB method may store data sets as ungrouped data elements formatted as a block of binary via a fixed memory offset using either fixed storage allocation, circular queue techniques, or best practices with respect to memory management (e.g., paged memory, least recently used, etc.). By using BLOB methods, the ability to store various data sets that have different formats facilitates the storage of data by multiple and unrelated owners of the data sets. For example, a first data set which may be stored may be provided by a first party, a second data set which may be stored may be provided by an unrelated second party, and yet a third data set which may be stored, may be provided by a third party unrelated to the first and second party. Each of these three exemplary data sets may contain different information that is stored using different data storage formats and/or techniques. Further, each data set may contain subsets of data that also may be distinct from other subsets.
  • As stated above, in various embodiments, the data can be stored without regard to a common format. However, in one exemplary embodiment, the data set (e.g., BLOB) may be annotated in a standard manner when provided for manipulating the data. The annotation may comprise a short header, trailer, or other appropriate indicator related to each data set, that is configured to convey information useful in managing the various data sets. For example, the annotation may be called a “condition header”, “header”, “trailer”, or “status”, herein, and may comprise an indication of the status of the data set or may include an identifier correlated to a specific issuer or owner of the data. Subsequent bytes of data may be used to indicate for example, the identity of the issuer or owner of the data, user, transaction/membership account identifier or the like. Each of these condition annotations are further discussed herein.
  • The data set annotation may also be used for other types of status in formation as well as various other purposes. For example, the data set annotation may include security information establishing access levels. The access levels may, for example, be configured to permit only certain individuals, levels of employees, companies, or other entities to access data sets, or to permit access to specific data sets based on the transaction, issuer or owner of data, user or the like. Furthermore, the security information may restrict/permit only certain actions such as accessing, modifying, and/or deleting data sets. In one example, the data set annotation indicates that only the data set owner or the user are permitted to delete a data set, various identified users may be permitted to access the data set for reading, and others are altogether excluded from accessing the data set. However, other access restriction parameters may also be used allowing various entities to access a data set with various permission levels as appropriate. The data, including the header or trailer may be received by a stand alone interaction device configured to add, delete, modify, or augment the data in accordance with the header or trailer.
  • One skilled in the art will also appreciate that, for security reasons, any databases, systems, devices, servers or other components of the system may consist of any combination thereof at a single location or at multiple locations, wherein each database or system includes any of various suitable security features, such as firewalls, access codes, encryption, decryption, compression, decompression, and/or the like.
  • The computing unit of the web client may be further equipped with an Internet browser connected to the Internet or an intranet using standard dial-up, cable, DSL or any other Internet protocol known in the art. Transactions originating at a web client may pass through a firewall in order to prevent unauthorized access from users of other networks. Further, additional firewalls may be deployed between the varying components of CMS to further enhance security.
  • Firewall may include any hardware and/or software suitably configured to protect CMS components and/or enterprise computing resources from users of other networks. Further, a firewall may be configured to limit or restrict access to various systems and components behind the firewall for web clients connecting through a web server. Firewall may reside in varying configurations including Stateful Inspection, Proxy based and Packet Filtering among others. Firewall may be integrated within an web server or any other CMS components or may further reside as a separate entity.
  • The computers discussed herein may provide a suitable website or other Internet-based graphical user interface which is accessible by users. In one embodiment, the Microsoft Internet Information Server (IIS), Microsoft Transaction Server (MTS), and Microsoft SQL Server, are used in conjunction with the Microsoft operating system, Microsoft NT web server software, a Microsoft SQL Server database system, and a Microsoft Commerce Server. Additionally, components such as Access or Microsoft SQL Server, Oracle, Sybase, Informix My SQL, Interbase, etc., may be used to provide an Active Data Object (ADO) compliant database management system.
  • Any of the communications, inputs, storage, databases or displays discussed herein may be facilitated through a website having web pages. The term “web page” as it is used herein is not meant to limit the type of documents and applications that might be used to interact with the user. For example, a typical website might include, in addition to standard HTML documents, various forms, Java applets, JavaScript, active server pages (ASP), common gateway interface scripts (CGI), extensible markup language (XML), dynamic HTML, cascading style sheets (CSS), helper applications, plug-ins, and the like. A server may include a web service that receives a request from a web server, the request including a URL (http://yahoo.com/stockquotes/ge) and an IP address (123.56.789.234). The web server retrieves the appropriate web pages and sends the data or applications for the web pages to the IP address. Web services are applications that are capable of interacting with other applications over a communications means, such as the internet. Web services are typically based on standards or protocols such as XML, XSLT, SOAP, WSDL and UDDI. Web services methods are well known in the art, and are covered in many standard texts. See e.g., ALEX NGHIEM. IT WEB SERVICES: A ROADMAP FOR THE ENTERPRISE (2003), hereby incorporated by reference.
  • The web-based clinical database for the system and method of the present invention preferably has the ability to upload and store clinical data files in native formats and is searchable on any clinical parameter. The database is also scalable and may utilize an EAV data model (metadata) to enter clinical annotations from any study for easy integration with other studies. In addition, the web-based clinical database is flexible and may be XML and XSLT enabled to be able to add user customized questions dynamically. Further, the database includes exportability to CDISC ODM.
  • Practitioners will also appreciate that there are a number of methods for displaying data within a browser-based document. Data may be represented as standard text or within a fixed list, scrollable list, drop-down list, editable text field, fixed text field, pop-up window, and the like. Likewise, there are a number of methods available for modifying data in a web page such as, for example, free text entry using a keyboard, selection of menu items, check boxes, option boxes, and the like.
  • The system and method may be described herein in terms of functional block components, screen shots, optional selections and various processing steps. It should be appreciated that such functional blocks may be realized by any number of hardware and/or software components configured to perform the specified functions. For example, the system may employ various integrated circuit components. e.g., memory elements, processing elements, logic elements, look-up tables, and the like, which may carry out a variety of functions under the control of one or more microprocessors or other control devices. Similarly, the software elements of the system may be implemented with any programming or scripting language such as C, C(++, Macromedia Cold Fusion, Microsoft Active Server Pages, Java, COBOL, assembler, PERL, Visual Basic, SQL Stored Procedures, extensible markup language (XML), with the various algorithms being implemented with any combination of data structures, objects, processes, routines or other programming elements. Further, it should be noted that the system may employ any number of conventional techniques for data transmission, signaling, data processing, network control, and the like. Still further, the system could be used to detect or prevent security issues with a client-side scripting language, such as JavaScript, VBScript or the like. For a basic introduction of cryptography and network security, see any of the following references: (1) “Applied Cryptography: Protocols, Algorithms, And Source Code In C,” by Bruce Schneier published by John Wiley & Sons (second edition, 1995); (2) “Java Cryptography” by Jonathan Knudson, published by O'Reilly & Associates (1998); (3) “Cryptography & Network Security: Principles & Practice” by William Stallings, published by Prentice Hall; all of which are hereby incorporated by reference.
  • As used herein, the term “end user”, “consumer”, “customer”, “client”, “treating physician”, “hospital”, or “business” may be used interchangeably with each other, and each shall mean any person, entity, machine, hardware, software or business. Each participant is equipped with a computing device in order to interact with the system and facilitate online data access and data input. The customer has a computing unit in the form of a personal computer, although other types of computing units may be used including laptops, notebooks, hand held computers, set-top boxes, cellular telephones, touch-tone telephones and the like. The owner/operator of the system and method of the present invention has a computing unit implemented in the form of a computer-server, although other implementations are contemplated by the system including a computing center shown as a main frame computer a mini-computer, a PC server, a network of computers located in the same of different geographic locations, or the like. Moreover, the system contemplates the use, sale or distribution of any goods, services or information over any network having similar functionality described herein.
  • In one exemplary embodiment, each client customer may be issued an “account” or “account number”. As used herein, the account or account number may include any device, code, number, letter, symbol, digital certificate, smart chip, digital signal, analog signal, biometric or other identifier/indicia suitably configured to allow the consumer to access, interact with or communicate with the system (e.g., one or more of an authorization/access code, personal identification number (PIN), Internet code, other identification code, and/or the like). The account number may optionally be located on or associated with a charge card, credit card, debit card, prepaid card, embossed card, smart card magnetic stripe magnetic card, bar code, card, transponder, radio frequency card or an associated account. The system may include or interface with any of the foregoing cards or devices, or a fob having a transponder and RFID reader in RF communication with the fob. Although the system may include a bob embodiment, the invention is not to be so limited. Indeed, system may include any device having a transponder which is configured to communicate with RFID reader via RF communication. Typical devices may include, for example, a key ring, tag, card, cell phone, wristwatch or any such firm capable of being presented for interrogation. Moreover, the system, computing unit or device discussed herein may include a “pervasive computing device,” which may include a traditionally non-computerized device that is embedded with a computing unit. The account number may be distributed and stored in any form of plastic, electronic, magnetic, radio frequency, wireless, audio and/or optical device capable of transmitting or downloading data from itself to a second device.
  • As will be appreciated by one of ordinary skill in the art, the system may be embodied as a customization of an existing system, an add-on product, upgraded software, a stand alone system, a distributed system, a method, a data processing system, a device for data processing, and/or a computer program product. Accordingly, the system may take the farm of an entirely software embodiment: an entirely hardware embodiment, or an embodiment combining aspects of both software and hardware. Furthermore, the system may take the form of a computer program product on a computer-readable storage medium having computer-readable program code means embodied in the storage medium. Any suitable computer-readable storage medium may be utilized, including hard disks, CD-ROM, optical storage devices, magnetic storage devices, and/or the like.
  • The system and method is described herein with reference to screen shots, block diagrams and flowchart illustrations of methods, apparatus (e.g., systems) and computer program products according to various embodiments. It will be understood that each functional block of the block diagrams and the flowchart illustrations, and combinations of functional blocks in the block diagrams and flowchart illustrations, respectively, can be implemented by computer program instructions.
  • Referring now to FIGS. 2-25 the process flows and screenshots depicted are merely embodiments and are not intended to limit the scope of the invention as described herein. For example, the steps recited in any of the method or process descriptions may be executed in any order and are not limited to the order presented. It will be appreciated that the following description makes appropriate references not only to the steps and user interface elements depicted in FIGS. 2-25, but also to the various system components as described above with reference to FIG. 1.
  • These computer program instructions may be loaded onto a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions that execute on the computer or other programmable data processing apparatus create means for implementing the functions specified in the flowchart block or blocks. These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart block or blocks. The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks.
  • Accordingly, functional blocks of the block diagrams and flowchart illustrations support combinations of means for performing the specified functions, combinations of steps for performing the specified functions, and program instruction means for performing the specified functions. It will also be understood that each functional block of the block diagrams and flowchart illustrations, and combinations of functional blocks in the block diagrams and flowchart illustrations, can be implemented by either special purpose hardware-based computer systems which perform the specified functions or steps, or suitable combinations of special purpose hardware and computer instructions. Further, illustrations of the process flows and the descriptions thereof may make reference to user windows, webpages, websites, web forms, prompts, etc. Practitioners will appreciate that the illustrated steps described herein may comprise in any number of con figurations including use of windows, webpages, web forms, popup windows, prompts and the like, it should be further appreciated that the multiple steps as illustrated and described may be combined into single webpages and/or windows but have been expanded for the sake of simplicity. In other cases, steps illustrated and described as single process steps may be separated into multiple webpages and/or windows but have been combined for simplicity.
  • Benefits, other advantages, and solutions to problems have been described herein with regard to specific embodiments. However, the benefits, advantages, solutions to problems, and any element(s) that may cause any benefit, advantage, or solution to occur or become more pronounced are not to be construed as critical, required or essential features or elements of any or all the claims or the invention. The scope of the invention is accordingly to be limited by nothing other than the appended claims, in which reference to an element in the singular is not intended to mean “one and only one” unless explicitly so stated, but rather “one or more.” All structural, chemical, and functional equivalents to the elements of the above-described exemplary embodiments that are known to those of ordinary skill in the art are expressly incorporated herein by reference and are intended to be encompassed by the present claims. Moreover, it is not necessary for a device or method to address each and every problem sought to be solved by the present invention, for it to be encompassed by the present claims. Furthermore, no element, component, or method step in the present disclosure is intended to be dedicated to the public regardless of whether the element, component, or method step is explicitly recited in the claims. No claim element herein is to be construed under the provisions of 35 U.S.C. 112, sixth paragraph, unless the element is expressly recited using the phrase “means for.” As used herein, the terms “comprises”, “comprising”, or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Further, no element described herein is required for the practice of the invention unless expressly described as “essential” or “critical”.
  • FIG. 1 is a block diagram of an exemplary embodiment of a system 10 for determining individualized medical intervention for a particular disease state that utilizes molecular profiling of a patient's biological specimen. System 10 includes a user interface 12, a host server 14 including a processor 16 for processing data, a memory 18 coupled to the processor, an application program 20 stored in the memory 18 and accessible by the processor 16 for directing processing of the data by the processor 16, a plurality of internal databases 22 and external databases 24, and an interface with a wired or wireless communications network 26 (such as the Internet, for example). System 10 may also include an input digitizer 28 coupled to the processor 16 for inputting digital data from data that is received from user interface 12.
  • User interface 12 includes an input device 30 and a display 32 for inputting data into system and for displaying information derived from the data processed by processor 16. User interface 12 may also include a printer 34 for printing the information derived from the data processed by the processor 16 such as patient reports that may include test results for targets and proposed drug therapies based on the test results.
  • Internal databases 22 may include, but are not limited to, patient biological sample/specimen information and tracking, clinical data, patient data, patient tracking, file management, study protocols, patient test results from molecular profiling, and billing information and tracking. External databases 24 may include, but are not limited to, drug libraries, gee libraries, disease libraries, and public and private databases such as UniGene, OMIM, GO, TIGR, GenBank, KEGG and Biocarta.
  • Various methods may be used in accordance with system 10. FIG. 2 shows a flowchart of an exemplary embodiment of a method 50 for determining individualized medical intervention for a particular disease state that utilizes molecular profiling of a patient's biological specimen that is non disease specific. In order to determine a medical intervention for a particular disease state using molecular profiling that is independent of disease lineage diagnosis (i.e. not single disease restricted), at least one test is performed for at least one target from a biological sample of a diseased patient in step 52. A target is defined as any molecular finding that may be obtained from molecular testing. For example, a target may include one or more genes, one or more gene expressed proteins, one or more molecular mechanisms, and or combinations of such. For example, the expression level of a target can be determined by the analysis of mRNA levels or the target or gene, or protein levels of the gene. Tests for finding such targets may include, but are not limited, fluorescent in-situ hybridization (FISH), an in-situ hybridization (ISH), and other molecular tests known to those skilled in the art. PCR-based methods, such as real-time PCR or quantitative PCR can be used. Furthermore, microarray analysis, such as a comparative genomic hybridization (CGH) micro array, a single nucleotide polymorphism (SNP) microarray, a proteomic array, or antibody array analysis can also be used in the methods disclosed herein, in some embodiments, microarray analysis comprises identifying whether a gene is up-regulated or down-regulated relative to a reference with a significance of p<0.001. Tests or analyses of targets can also comprise immunohistochemical (IHC) analysis. In some embodiments, IHC analysis comprises determining whether 30% or more of a sample is stained, if the staining intensity is +2 or greater, or both.
  • Furthermore, the methods disclosed herein also including profiling more than one target. For example, the expression of a plurality of genes can be identified. Furthermore, identification of a plurality of targets in a sample can be by one method or by various means. For example, the expression of a first gene can be determined by one method and the expression level of a second gene determined by a different method. Alternatively, the same method can be used to detect the expression level of the first and second gene. For example, the first method can be IHC and the second by microarray analysis, such as detecting the gene expression of a gene.
  • In some embodiments, molecular profiling can also including identifying a genetic variant, such as a mutation, polymorphism (such as a SNP), deletion, or insertion of a target. For example, identifying a SNP in a gene can be determined by microarray analysis, real-time PCR, or sequencing. Other methods disclosed herein can also be used to identify variants of one or more targets.
  • Accordingly, one or more of the following may be performed: an IHC analysis in step 54, a microanalysis in step 56, and other molecular tests know to those skilled in the art in step 58.
  • Biological samples are obtained from diseased patients by taking a biopsy of a tumor, conducting minimally invasive surgery if no recent tumor is available, obtaining a sample of the patient's blood, or a sample of any other biological fluid including, but not limited to, cell extracts, nuclear extracts, cell lysates or biological products or substances of biological origin such as excretions, blood, sera, plasma, urine, sputum, tears, feces, saliva, membrane extracts, and the like.
  • In step 60, a determination is made as to whether one or more of the targets that were tested for in step 52 exhibit a change in expression compared to a normal reference for that particular target. In one exemplary method of the invention, an IHC analysis may be performed in step 54 and a determination as to whether any targets from the IHC analysis exhibit a change in expression is made in step 64 by determining whether 30% or more of the biological sample cells were +2 or greater staining for the particular target. It will be understood by those skilled in the art that there will be instances where +1 or greater staining will indicate a change in expression in that staining results may vary depending on the technician performing the test and type of target being tested. In another exemplary embodiment of the invention, a micro array analysis may be performed in step 56 and a determination as to whether any targets from the micro array analysis exhibit a change in expression is made in step 66 by identifying which targets are up-regulated or down-regulated by determining whether the fold change in expression for a particular target relative to a normal tissue of origin reference is significant at p<0.001. A change in expression may also be evidenced by an absence of one or more genes, gene expressed proteins, molecular mechanisms, or other molecular findings.
  • After determining which targets exhibit a change in expression in step 60, at least one non-disease specific agent is identified that interacts with each target having a changed expression in step 70. An agent may be any drug or compound having a therapeutic effect. A non-disease specific agent is a therapeutic drug or compound not previously associated with treating the patient's diagnosed disease that is capable of interacting with the target from the patient's biological sample that has exhibited a change in expression. Some of the non-disease specific agents that have been found to Interact with specific targets found in different cancer patients are shown in Table 1 below.
  • TABLE 1
    Patients Target(s) Found Treatment(s)
    Advanced Pancreatic Cancer HER 2/neu (IHC/Array) Herceptin ™
    Advanced Pancreatic Cancer EGFR (IHC), HIF 1α Erbitux ™,
    Rapamycin ™
    Advanced Ovarian Cancer ERCC3 (Array) Irofulvene
    Advanced Adenoid Cystic Vitamin D receptors, Calcitriol ™,
    Carcinoma Androgen receptors Flutamide ™
  • Finally, in step 80, a patient profile report may be provided which includes the patient's test results for various targets and any proposed therapies based on those results. An exemplary patient profile report 100 is shown in FIGS. 3A-3D. Patient profile report 100 shown in FIG. 3A identifies the targets tested 102, those targets tested that exhibited significant changes in expression 104, and proposed non-disease specific agents for interacting with the targets 106. Patient profile report 100 shown in FIG. 3B identifies the results 108 of immunohistochemical analysis for certain gene expressed proteins 110 and whether a gene expressed protein is a molecular target 112 by determining whether 30% or more of the tumor cells were +2 or greater staining. Report 100 also identifies immunohistochemical tests that were not performed 114. Patient profile report 100 shown in FIG. 3C identifies the genes analyzed 116 with a micro array analysis and whether the genes were under expressed or over expressed 11 compared to a reference. Finally, patient profile report 100 shown in FIG. 3D identifies the clinical history 120 of the patient and the specimens that were submitted 122 from the patient.
  • FIG. 4 shows a flowchart of an exemplary embodiment of a method 200 for identifying a drug therapy/agent capable of interacting with a target. In step 202, a molecular target is identified which exhibits a change in expression in a number of diseased individuals. Next, in step 204, a drug therapy/agent is administered to the diseased individuals. After drug therapy/agent administration, any changes in the molecular target identified in step 202 are identified in step 206 in order to determine if the drug therapy/agent administered in step 204 interacts with the molecular targets identified in step 202. If it is determined that the drug therapy/agent administered in step 204 interacts with a molecular target identified in step 202, the drug therapy/agent may be approved for treating patients exhibiting a change in expression of the identified molecular target instead of approving the drug therapy/agent for a particular disease.
  • FIGS. 5-14 are flowcharts and diagrams illustrating various parts of an information-based personalized medicine drug discovery system and method in accordance with the present invention. FIG. 5 is a diagram showing an exemplary clinical decision support system of the information-based personalized medicine drug discovery system and method of the present invention. Data obtained through clinical research and clinical care such as clinical trial data, biomedical/molecular imaging data, genomics/proteomics/chemical library/literature/expert curation, biospecimen tracking/LIMS, family history/environmental records, and clinical data are collected and stored as databases and datamarts within a data warehouse. FIG. 6 is a diagram showing the flow of information through the clinical decision support system of the information-based personalized medicine drug discovery system and method of the present invention using web services A user interacts with the system by entering data into the system via form-based entry/upload of data sets, formulating queries and executing data analysis jobs, an a acquiring and evaluating representations of output data. The data warehouse in the web based system is where data is extracted, transformed, and loaded from various database systems. The data warehouse is also where common formats, mapping and transformation occurs. The web based system also includes datamarts which are created based on data views of interest.
  • A flow chart of an exemplary clinical decision support system of the information-based personalized medicine drug discovery system and method of the present invention is shown in FIG. 7. The clinical information management system includes the laboratory information management system and the medical information contained in the data warehouses and databases includes medical information libraries, such as drug libraries, gene libraries, and disease libraries, in addition to literature text mining. Both the information management systems relating to particular patients and the medical information databases and data warehouses come together at a data junction center where diagnostic information and therapeutic options can be obtained. A financial management system may also be incorporated in the clinical decision support system of the information-based personalized medicine drug discovery system and method of the present invention.
  • FIG. 8 is a diagram showing an exemplary biospecimen tracking and management system which may be utilized as part of the in formation-based personalized medicine drug discovery system and method of the present invention. FIG. 8 shows two host medical centers which forward specimens to a tissue/blood bank. The specimens may go through laboratory analysis prior to shipment. Research may also be conducted on the samples via micro array, genotyping, and proteomic analysis. This information can be redistributed to, the tissue/blood bank. FIG. 9 depicts a flow chart of an exemplary biospecimen tracking and management system which may be utilized with the information-based personalized medicine drug discovery system and method of the present invention. The host medical center obtains samples from patients and then ships the patient samples to a molecular profiling laboratory which may also perform RNA and DNA isolation and analysis.
  • A diagram showing a method for maintaining a clinical standardized vocabulary for use with the information-based personalized medicine drug discovery system and method of the present invention is shown in FIG. 10, FIG. 10 illustrates how physician observations and patient information associated with one physician's patient may be made accessible to another physician to enable the other physician to utilize the data in making diagnostic and therapeutic decisions for their patients.
  • FIG. 11 shows a schematic of an exemplary micro array gene expression database which may be used as part of the information-based personalized medicine drug discovery system and method of the present invention. The micro array gene expression database includes both external databases and internal databases which can be accessed via the web based system. External databases may include, but are not limited to, UniGene, GO, TIGR, GenBank. KEGG. The internal databases may include, but are not limited to, tissue tracking, LIMS, clinical data, and patient tracking. FIG. 12 shows a diagram of an exemplary micro array gene expression database data warehouse which may be used as part of the information-based personalized medicine drug discovery system and method of the present invention, Laboratory data, clinical data, and patient data may all be housed in the micro array gene expression database data warehouse and the data may in turn be accessed by public/private release and utilized by data analysis tools.
  • Another schematic showing the flow of information through an information-based personalized medicine drug discovery system and method of the present invention is shown in FIG. 13. Like FIG. 7, the schematic includes clinical information management, medical and literature information management, aid financial management of the information-based personalized medicine drug discovery system and method of the present invention. FIG. 14 is a schematic showing an exemplary network of the information-based personalized medicine drug discovery system and method of the present invention. Patients, medical practitioners, host medical centers, and labs all share and exchange a variety of information in order to provide a patient with a proposed therapy or agent based on various identified targets.
  • FIGS. 15-25 are computer screen print outs associated with various parts of the information-based personalized medicine drug discovery system and method shown in FIGS. 5-14. FIGS. 15 and 16 show computer screens where physician information and insurance company in formation is entered on behalf of a client. FIGS. 17-19 show computer screens in which information can be entered for ordering analysis and tests on patient samples.
  • FIG. 20 is a computer screen showing micro array analysis results of specific genes tested with patient samples. This information and computer screen is similar to the information detailed in the patient profile report shown in FIG. 3C. FIG. 22 is a computer screen that shows immunohistochemistry test results for a particular patient for various genes. This information is similar to the information contained in the patient profile report shown in FIG. 3B.
  • FIG. 21 is a computer screen showing selection options for finding particular patterns, ordering tests and/or results, issuing patient reports, and tracking current cases/patients.
  • FIG. 23 is a computer screen which outlines some of the steps for creating a patient profile report as shown in FIGS. 3A through 3D. FIG. 24 shows a computer screen for ordering an immunohistochemistry test on a patient sample and FIG. 25 shows a computer screen for entering information regarding a primary tumor site for micro array analysis. It will be understood by those skilled in the art that any number and variety of computer screens may be utilized to enter the in formation necessary tot utilizing the information-based personalized medicine drug discovery system and method of the present invention and to obtain information resulting from utilizing the information-based personalized medicine drug discovery system and method of the present invention.
  • FIGS. 26-31 represent tables that show the frequency of a significant change in expression of certain genes and/or gene expressed proteins by tumor type, i.e. the number of times that a gene and/or gene expressed protein was flagged as a target by tumor type as being significantly overexpressed or underexpressed (see also Examples 1-3). The tables show the total number of times a gene and/or gene expressed protein was overexpressed or underexpressed in a particular tumor type and whether the change in expression was determined by immunohistochemistry analysis (FIG. 26, FIG. 28) or microarray analysis (FIGS. 27, 30). The tables also identify the total number of times an overexpression of any gene expressed protein occurred in a particular tumor type using immunohistochemistry and the total number of times an overexpression or underexpression of any gene occurred in a particular tumor type using gene microarray analysis.
  • Thus the present invention provides methods and systems for analyzing diseased tissue using IHC testing and gene microarray testing in accordance with IHC and microarray testing as previously described above. The patients can be in an advanced stage of disease. The biomarker patterns or biomarker signature sets in a number of tumor types, diseased tissue types, or diseased cells including adipose, adrenal cortex, adrenal gland, adrenal gland—medulla, appendix, bladder, blood vessel, bone, bone cartilage, brain, breast, cartilage, cervix, colon, colon sigmoid, dendritic cells, skeletal muscle, enodmetrium, esophagus, fallopian tube, fibroblast, gallbladder, kidney, larynx, liver, lung, lymph node, melanocytes, mesothelial lining, myoepithelial cells, osteoblasts, ovary, pancreas, parotid, prostate, salivary gland, sinus tissue, skeletal muscle, skin, small intestine, smooth muscle, stomach, synovium, joint lining tissue, tendon, testis, thymus, thyroid, uterus, and uterus corpus can be determined.
  • The biomarker patterns or biomarker signature sets in a number of tumor types, diseased tissue types, or diseased cells including accessory, sinuses, middle and inner ear, adrenal glands, appendix, hematopoietic system, bones and joints, spinal cord, breast, cerebellum, cervix uteri, connective and soft tissue, corpus uteri, esophagus, eye, nose, eyeball, fallopian tube, extrahepatic bile ducts, other mouth, intrahepatic bile ducts, kidney, appendix-colon, larynx, lip, liver, hung and bronchus, lymph nodes, cerebral, spinal, nasal cartilage, excl. retina, eye, nos, oropharynx, other endocrine glands, other female genital, ovary, pancreas, penis and scrotum, pituitary gland, pleura, prostate gland, rectum renal pelvis, ureter, peritonem, salivary gland, skin, small intestine, stomach, testis, thymus, thyroid gland, tongue, unknown, urinary bladder, uterus, nos, vagina & labia, and vulva.nos can also be determined.
  • Thus the biomarker patterns or biomarker signature sets can be used to determine a therapeutic agent or therapeutic protocol that is capable of interacting with the biomarker pattern or signature set. For example, with advanced breast cancer, immunohistochemistry analysis can be used to determine one or more gene expressed proteins that are overexpressed. Accordingly, a biomarker pattern or biomarker signature set can be identified for advanced stage breast cancer and a therapeutic agent or therapeutic protocol can be identified which is capable of interacting with the biomarker pattern or signature set.
  • These examples of biomarker patterns or biomarker signature sets for advanced stage breast cancer are just one example of the extensive number of biomarker patterns or biomarker signature sets for a number of advanced stage diseases or cancers that can be identified from the tables depicted in FIGS. 26-31. In addition, a number of non disease specific therapies or therapeutic protocols may be identified for treating patients with these biomarker patterns or biomarker signature sets by utilizing method steps of the present invention described above such as depicted in FIGS. 1-2 and FIGS. 5-14.
  • The biomarker patterns and/or biomarker signature sets disclosed in the table depicted in FIGS. 26 and 28, and the tables depicted in FIGS. 27 and 30 may be used for a number of purposes including, but not limited to, specific cancer/disease detection, specific cancer/disease treatment, and identification of new drug therapies or protocols for specific cancers/diseases. The biomarker patterns and/or biomarker signature sets disclosed in the table depicted in FIGS. 26 and 28, and the tables depicted in FIGS. 27 and 30 can also represent drug resistant expression profiles for the specific tumor type or cancer type. The biomarker patterns and/or biomarker signature sets disclosed in the table depicted in FIGS. 26 and 28, and the tables depicted in FIGS. 27 and 30 represent advanced stage drug resistant profiles.
  • The biomarker patterns and/or biomarker signature sets can comprise at least one biomarker. In yet other embodiments, the biomarker patterns or signature sets can comprise at least 2, 3, 4, 5, 6, 7, 8, 9, or 10 biomarkers. In some embodiments, the biomarker signature sets or biomarker patterns can comprise at least 15, 20, 30, 40, 50, or 60 biomarkers. Analysis of the one or more biomarkers can be by one or more methods. For example, analysis of 2 biomarkers can be performed using microarrays. Alternatively, one biomarker may be analyzed by IHC and another by microarray. Various combinations of methods and biomarkers are contemplated herein.
  • The one or more biomarkers can be selected from the group consisting of but not limited to Her2/Neu, ER, PR, c-kit, EGFR, MLH1, MSH2, CD20, p53, Cychn D1, bcl2, COX-2, Androgen receptor, CD52, PDGFR, AR, CD25, VEGF, HSP90, PTEN, RRM1, SPARC, Survivin, TOP2A, BCL2, HIF1A, AR, ESR1, PDGFRA, KIT, PDGFRB, CDW52, ZAP70, PGR, SPARC, GART, GSTP1, NFKB1A, MSH2, TXNRD1, HDAC1, PDGFC, PTEN, CD33, TYMS, RXRB, ADA, TNF, ERCC3, RAF1, VEGF, TOP1, TOP2A, BRCA2, TK1, FOLR2, TOP2B, MLH1, IL2RA, DNMT1, HSPCA, ERBR2, ERBB2, SSTR1, VHL, VDR, PTGS2, POLA, CES2, EGFR, OGFR, ASNS, NFKB2, RARA, MS4A1, DCK, DNMT3A, EREG, Epiregulin, FOLR1, GNRH1, GNRHR1, FSHB, FSHR, FSHPRH1, folate receptor, HGF, HIG1, IL13RA1, LTB, ODC1, PPARG, PPARGC1, Lymphotoxin Beta Receptor, Myc, Topoisomerase II, TOPO2B, TXN, VEGFC, ACE2, ADH1C, ADH4, AGT, AREG, CA2 CDK2, caveolin, NFKB1, ASNS, BDCA1, CD52, DHFR, DNMT3B, EPHA2, FLT1, HSP90AA1, KDR, LCK, MGMT, RRM1, RRM2, RRM2B, RXRG, SRC, SSTR2, SSTR3, SSTR4, SSTR5, VEGFA, or YES1.
  • For example, a biological sample from an individual can be analyzed to determine a biomarker pattern or biomarker signature set that comprises a biomarker such as HSP90, Survivin, RRM1, SSTRS3, DNMT3B, VEGFA, SSTR4, RRM2, SRC, RRM2B, HSP90AA1, STR2, FLIT, SSTR5, YES1, BiRCA1, RRM1, DHFR, KDR, EPHA2, RXRG, or LCK. In other embodiments, the biomarker SPARC, HSP90, TOP2A, PTEN, Survivin, or RRM1 forms part of the biomarker pattern or biomarker signature set. In yet other embodiments, the biomarker MGMT, SSTRS3, DNMNT3B, VEGFA, SSTR4, RRM2, SRC, RRMB, HSP90AA1, STR2, FTL1, SSTR5, YES1, SRCA1, RRM1, DHFR, KDR, EPHA2, RXRG, CD52, or LCK is included in a biomarker pattern or biomarker signature set.
  • The expression level of HSP90, Survivin, RRM1, SSTRS3, DNMT3B, VEGFA, SSTR4, RRM2, SRC, RRM2B, HSP90AA1. STR2, FLT1, SSTR5, YES1, BRCA1, RRM1, DHFR KDR, EPHA2, RXRG, or LCK can be determined and used to identify a therapeutic for an individual. The expression level of the biomarker can be used to form a biomarker pattern or biomarker signature set. Determining the expression level can be by analyzing the levels of mRNA or protein, such as by microarray analysis or IHC. In some embodiments, the expression level of a biomarker is performed by IHC, such as for SPARC, TOP2A, or PTEN, and used to identify a therapeutic for an individual. The results of the IHC can be used to form a biomarker pattern or biomarker signature set. In yet other embodiments, a biological sample from an individual or subject is analyzed for the expression level of CD52, such as by determining the mRNA expression level by methods including, but not limited to, microarray analysis. The expression level of CD52 can be used to identify a therapeutic for the individual. The expression level of CD52 can be used to firm a biomarker pattern or biomarker signature set.
  • As described herein, the molecular profiling of one or more targets can be used to determine or identify a therapeutic for an individual. For example, the expression level of one or more biomarkers can be used to determine or identify a therapeutic for an individual. The one or more biomarkers, such as those disclosed herein, can be used to form a biomarker pattern or biomarker signature set, which is used to identify a therapeutic for an individual. In some embodiments, the therapeutic identified is one that the individual has not previously been treated with.
  • For example, a reference biomarker pattern has been established for a particular therapeutic, such that individuals with the reference biomarker pattern will be responsive to that therapeutic. An individual with a biomarker pattern that differs from the reference, for example the expression of a gene in the biomarker pattern is changed or different from that of the reference, would not be administered that therapeutic, in another example, an individual exhibiting a biomarker pattern that is the same or substantially the same as the reference is advised to be treated with that therapeutic. In some embodiments, the individual has not previously been treated with that therapeutic and thus a new therapeutic has been identified for the individual.
  • It will be understood that the foregoing description is of preferred exemplary embodiments of the invention and that the invention is not limited to the specific forms shown or described herein. Various modifications may be made in the design, arrangement, and type of elements disclosed herein, as well as the steps of utilizing the invention.
    • EXAMPLES Example 1 IHC and Microarray Testing of Over 500 Patients
  • The data reflected in the table depicted in FIGS. 26A-H and FIGS. 27A-27H relates to 544 patients whose diseased tissue underwent IHC testing (FIG. 26) and 540 patients whose diseased tissue underwent gene microarray testing (FIG. 27) in accordance with IHC and microarray testing as previously described above. The patients were all in advanced stages of disease.
  • The data show biomarker patterns or biomarker signature sets in a number of tumor types, diseased tissue types, or diseased cells including adipose, adrenal cortex, adrenal gland, adrenal gland—medulla, appendix, bladder, blood vessel, bone, bone cartilage, brain, breast, cartilage, cervix, colon, colon sigmoid, dendritic cells, skeletal muscle, endometrium, esophagus, fallopian tube, fibroblast, gallbladder, kidney, larynx, liver, lung, lymph node, melanocytes, mesothelial lining, myoepithelial cells, osteoblasts, ovary, pancreas, parotid, prostate, salivary gland, sinus tissue, skeletal muscle, skin, small intestine, smooth muscle, stomach, synovium joint lining tissue, tendon, testis, thymus, thyroid, uterus, and uterus corpus.
  • In 99 individuals with advanced breast cancer, immunohistochemistry analysis of 20 gene expressed proteins (FIG. 26B) showed that the gene expressed proteins analyzed were overexpressed a total of 367 times and that 16.35% of that total overexpression was attributable to HSP90 overexpression followed by 12.53% of the overexpression being attributable to TOP2A overexpression and 11.17% of the overexpression being attributable to SPARC. In addition, 9.81% the overexpression was attributable to androgen receptor overexpression, 9.54% of the overexpression was attributable to PDGFR overexpression, and 9.26% of the overexpression was attributable to c-kit overexpression.
  • Accordingly, a biomarker pattern or biomarker signature set can be identified for advanced stage breast cancer and a therapeutic agent or therapeutic protocol can be identified which is capable of interacting with the biomarker pattern or signature set.
  • Another biomarker pattern or biomarker signature set for advanced stage breast cancer is shown from the microarray data in the table represented by FIGS. 27A-H. For example, in 100 individuals with advanced breast cancer (FIG. 27B), gene microarray analysis of 64 genes showed that the genes analyzed exhibited a change in expression a total of 1,158 times and that 6.39% of that total change in expression was attributable to SSTR3 change in expression followed by 5.79% of the change in expression being attributable to VDR change in expression and 5.35% of the change in expression being attributable to BRCA2 change in expression. Accordingly, another biomarker pattern or biomarker signature set can be identified for advanced stage breast cancer and another therapeutic agent or therapeutic protocol can be identified which is capable of interacting with this biomarker pattern or signature set.
    • Example 2 IHC Testing of Over 1300 Patients
  • FIGS. 28A through 28O represent a table that shows the frequency of a significant change in expression of certain gene expressed proteins by tumor type, the number of times that a gene expressed protein was flagged as a target by tumor type as being significantly overexpressed by immunohistochemistry analysis. The table also identifies the total number of times an overexpression of any gene expressed protein occurred in a particular tumor type using immunohistochemistry.
  • The data reflected in the table depicted in FIGS. 28A through 28O relates to 1392 patients whose diseased tissue underwent IHC testing in accordance with IHC testing as previously described above. The patients were all in advanced stages of disease.
  • The data show biomarker patterns or biomarker signature sets in a number of tumor types, diseased tissue types, or diseased cells including accessory, sinuses, middle and inner ear, adrenal glands, appendix, hematopoietic system, bones and joints, spinal cord, breast, cerebellum, cervix uteri, connective and soil tissue, corpus uteri, esophagus, eye, nose, eyeball, fallopian tube, extrahepatic bile ducts, other mouth, intrahepatic bile ducts, kidney, appendix-colon, larynx, lip, liver, lung and bronchus, lymph nodes, cerebral, spinal nasal cartilage, excl. retina, eye, nos, oropharynx, other endocrine glands, other female genital, ovary, pancreas, penis and scrotum, pituitary gland, pleura, prostate gland, rectum renal pelvis, ureter, peritonem, salivary gland, skin, small intestine, stomach, testis, thymus, thyroid gland, tongue, unknown, urinary bladder, uterus, nos, vagina & labia, and vulva, nos.
  • In 254 individuals with advanced breast cancer, immunohistochemistry analysis of 19 gene expressed proteins (FIG. 28C) showed that the gene expressed proteins analyzed were overexpressed a total of 767 limes and that 13.43% of that total overexpression was attributable to SPARC overexpression followed by 12.26% of the overexpression being attributable to c-kit overexpression and 11.47% of the overexpression being attributable to EGFR. In addition, 10.34% of the overexpression was attributable to androgen receptor overexpression, 11.08% of the overexpression was attributable to HSP90 overexpression, and 11.43% of the overexpression was attributable to PDGFR overexpression. Accordingly, a biomarker pattern or biomarker signature set can be identified for advanced stage breast cancer and a therapeutic agent or therapeutic protocol can be identified which is capable of interacting with the biomarker pattern or signature set.
  • FIG. 29 depicts a table showing biomarkers (gene expressed proteins) tagged as targets in order of frequency in all tissues that were IHC tested. Immunohistochemistry of the 19 gene expressed proteins showed that the 19 gene expressed proteins were tagged 3878 times as targets in the various tissues tested and that EGFR was the gene expressed protein that was overexpressed the most frequently followed by SPARC.
    • Example 3 Microarray Testing of Over 300 Patients
  • FIGS. 30A through 30O represent a table that shows the frequency of a significant change in expression of certain genes by tumor type, i.e. the number of times that a gene was flagged as a target by tumor type as being significantly overexpressed or underexpressed by microarray analysis. The table also identifies the total number of lines an overexpression or underexpression of any gene occurred in a particular tumor type using gene microarray analysis.
  • The data reflected in the table depicted in FIGS. 30A through 30O relates to 379 patients whose diseased tissue underwent gene microarray testing in accordance microarray testing as previously described above. The patients were all in advanced stages of disease. The data show biomarker patterns or biomarker signature sets in a number of tumor types, diseased tissue types, or diseased cells including accessory, sinuses, middle and inner ear, adrenal glands, anal canal and anus, appendix, blood, bone marrow & hematopoietic sys, bones and joints, brain & cranial nerves and spinal cord (excl. ventricle & cerebellum), breast, cerebellum, cervix, uteri connective & soft tissue, corpus uteri, esophagus, eye, nos, eyeball, fallopian tube, gallbladder 7 extrahepatic bile ducts, gum, floor of mouth & other mouth, intrahepatic bile ducts, kidney, large intestine (excl. appendix-colon), larynx, lip, liver, lung & bronchus, lymph nodes, meninges (cerebral, spinal, nasal cavity (including nasal cartilage), orbit & lacrimal gland (excl. retina, eye, nos), oropharynx, other endocrine glands, other female genital, ovary, pancreas, penis & scrotum, pituitary gland, pleura, prostate gland, rectum, renal pelvis & ureter, retroperitoneum & peritoneum, salivary gland, skin, small intestine, stomach, testis, thymus, thyroid gland, tongue, unknown, unspecified digestive organs, urinary bladder, uterus, nos, vagina & labia, and vulva, nos.
  • For example, in 168 individuals with advanced breast cancer (FIG. 30C), microarray analysis of 63 genes showed that the genes analyzed were either overexpressed or underexpressed a total of 1863 times and that 5.05% of that total change in expression was attributable to SSTR3 change in expression followed by 4.83% of the change in expression being attributable to NKFB1A change in expression and 4.62% of the change in expression being attributable to VDR. In addition, 4.35% of the change in expression was attributable to MGMT change in expression, 4.19% of the change in expression was attributable to ADA change in expression, and 3.97% of the change in expression was attributable to CES2 change in expression.
  • FIG. 31 depicts a table showing biomarkers as targets in order of frequency in all tissues that were tested.

Claims (27)

1. A method for identifying a therapeutic for an individual with a condition comprising:
(a) determining an expression level of a gene from a biological sample of said individual,
wherein said gene is selected from the group consisting of HSP90, Survivin, RRM1, SSTRS3, DNMT3B, VEGFA, SSTR4, RRM2, SRC, RRM2B, HSP90AA1, STR2, FLT1, SSTR5, YES1, BRCA1, RRM1, DHFR, KDR, EPHA2, RXRG, and LCK; and,
(b) identifying a therapeutic that said individual has not previously been treated with for said condition, when said gene exhibits a change in expression as compared to a reference.
2. The method of claim 1, wherein said expression level is determined by analysis of mRNA levels of said gene or protein levels of said gene.
3. The method of claim 1, further comprising determining an expression level of a second gene.
4. The method of claim 1 or 3, wherein determining is by immunohistochemistry (IHC) analysis, microarray analysis, in-situ hybridization (ISH) or real-time PCR.
5. The method of claim 3, wherein said ISH is fluorescent in-situ hybridization (FISH).
6. The method of claim 3, wherein determining an expression level of said second gene is by the same method used for said first gene.
7. The method of claim 3, wherein determining an expression level of said second gene is by a different method than that used for said first gene.
8. The method of claim 3, wherein determining an expression level of said first gene is by IHC and said second gene is by microarray.
9. The method of claim 1, further comprising identifying a mutation, polymorphism, or deletion, or insertion in a gene.
10. The method of claim 9, wherein said identifying is by IHC analysis, microarray analysis, ISH, PCR, real-time PCR, or sequencing.
11. A method for identifying a therapeutic for an individual with a condition comprising:
(a) determining an expression level of a gene by IHC from a biological sample of said individual,
wherein said protein is selected from the group consisting of: SPARC, TOP2A, or PTEN; and,
(b) identifying a therapeutic that said individual has not previously been treated with for said condition, when said protein exhibits a change in expression as compared to a reference.
12. The method of claim 11, further comprising determining an expression level of a second gene.
13. The method of claim 12, wherein determining an expression level of said second gene is by IHC analysis, microarray analysis, ISH, or real-time PCR.
14. The method of claim 12, wherein said ISH is FISH.
15. The method of claim 11, further comprising identifying a mutation, polymorphism, deletion, or insertion in a gene.
16. The method of claim 15, wherein said identifying is by IHC analysis, microarray analysis, ISH, PCR, real-time PCR, or sequencing.
17. A method for identifying a therapeutic for an individual with a condition comprising:
(a) determining an mRNA expression level of CD52 from a biological sample of said individual; and,
(b) identifying a therapeutic that said individual has not previously been treated with for said condition, when said mRNA expression level exhibits a change as compared to a reference.
18. The method of claim 17, further comprising determining an expression level of a second gene.
19. The method of claim 18, wherein determining an expression level of said second gene is by a same method used for determining said mRNA expression level of CD52.
20. The method of claim 18, wherein determining an expression level of said second gene is by a different method than used for determining said mRNA expression level of CD52.
21. The method of claim 18, wherein determining an expression level of said second gene is by IHC analysis, microarray analysis, ISH, or real-time PCR.
22. The method of claim 21, wherein said ISH is FISH.
23. The method of claim 17, further comprising identifying a mutation, polymorphism, deletion, or insertion in a gene.
24. The method of claim 23, wherein said identifying is by IHC analysis, microarray analysis, ISH, PCR, real-time PCR, or sequencing.
25. The method of claim 4, 13, or 21, wherein said microarray analysis comprises using an expression microarray, a comparative genomic hybridization (CGH) microarray, a single nucleotide polymorphism (SNP) microarray, a proteomic array or an antibody array.
26. The method of claim 4, 13, or 21, wherein said microarray analysis comprises identifying whether said gene is up-regulated or down-regulated relative to a reference with a significance of p<0.001.
27. The method of claim 4, 11, 13, or 21, wherein said IHC analysis comprises determining whether 30% or more of said sample are +2 or greater in staining intensity.
US12/579,241 2006-05-18 2009-10-14 Gene and gene expressed protein targets depicting biomarker patterns and signature sets by tumor type Abandoned US20100113299A1 (en)

Priority Applications (36)

Application Number Priority Date Filing Date Title
US12/579,241 US20100113299A1 (en) 2008-10-14 2009-10-14 Gene and gene expressed protein targets depicting biomarker patterns and signature sets by tumor type
US13/188,350 US20120015843A1 (en) 2006-05-18 2011-07-21 Gene and gene expressed protein targets depicting biomarker patterns and signature sets by tumor type
US13/942,539 US20140018254A1 (en) 2008-09-16 2013-07-15 Theranostic and diagnostic methods using sparc and hsp90
US14/070,357 US20140057986A1 (en) 2008-10-14 2013-11-01 Gene and gene expressed protein targets depicting biomarker patterns and signature sets by tumor type
US14/170,370 US20140149136A1 (en) 2006-05-18 2014-01-31 Gene and gene expressed protein targets depicting biomarker patterns and signature sets by tumor type
US14/170,450 US20140149137A1 (en) 2006-05-18 2014-01-31 Gene and gene expressed protein targets depicting biomarker patterns and signature sets by tumor type
US14/175,728 US9053224B2 (en) 2006-05-18 2014-02-07 Molecular profiling of tumors
US14/175,800 US9064045B2 (en) 2006-05-18 2014-02-07 Molecular profiling of tumors
US14/175,781 US9092392B2 (en) 2006-05-18 2014-02-07 Molecular profiling of tumors
US14/187,015 US9292660B2 (en) 2006-05-18 2014-02-21 Molecular profiling of tumors
US14/187,008 US9058418B2 (en) 2006-05-18 2014-02-21 Molecular profiling of tumors
US14/187,020 US20140244182A1 (en) 2006-05-18 2014-02-21 Molecular profiling of tumors
US14/187,028 US20140244183A1 (en) 2006-05-18 2014-02-21 Molecular profiling of tumors
US14/249,261 US9322067B2 (en) 2006-05-18 2014-04-09 Molecular profiling of tumors
US14/551,345 US20150080268A1 (en) 2008-10-14 2014-11-24 Molecular profiling of tumors
US14/832,860 US20150361508A1 (en) 2008-10-14 2015-08-21 Molecular profiling of tumors
US14/832,873 US20160054325A1 (en) 2006-05-18 2015-08-21 Molecular profiling of tumors
US15/093,634 US20160224742A1 (en) 2006-05-18 2016-04-07 Molecular profiling of tumors
US15/093,668 US20160224726A1 (en) 2006-05-18 2016-04-07 Molecular profiling of tumors
US15/093,653 US20160224725A1 (en) 2006-05-18 2016-04-07 Molecular profiling of tumors
US15/094,434 US20160224727A1 (en) 2006-05-18 2016-04-08 Molecular profiling of tumors
US15/094,520 US20160224747A1 (en) 2006-05-18 2016-04-08 Molecular profiling of tumors
US15/094,457 US20160224728A1 (en) 2006-05-18 2016-04-08 Molecular profiling of tumors
US15/094,470 US20160224729A1 (en) 2006-05-18 2016-04-08 Molecular profiling of tumors
US15/094,507 US20160224746A1 (en) 2006-05-18 2016-04-08 Molecular profiling of tumors
US15/094,486 US20160224745A1 (en) 2006-05-18 2016-04-08 Molecular profiling of tumors
US15/099,466 US20160232286A1 (en) 2006-05-18 2016-04-14 Molecular profiling of tumors
US15/099,512 US20160232287A1 (en) 2006-05-18 2016-04-14 Molecular profiling of tumors
US15/099,422 US20160232283A1 (en) 2006-05-18 2016-04-14 Molecular profiling of tumors
US15/099,517 US20160232288A1 (en) 2006-05-18 2016-04-14 Molecular profiling of tumors
US15/099,442 US20160232284A1 (en) 2006-05-18 2016-04-14 Molecular profiling of tumors
US15/099,454 US20160232285A1 (en) 2006-05-18 2016-04-14 Molecular profiling of tumors
US15/099,530 US20160232289A1 (en) 2006-05-18 2016-04-14 Molecular profiling of tumors
US15/494,018 US20170228522A1 (en) 2006-05-18 2017-04-21 Molecular profiling of tumors
US16/560,999 US20200003796A1 (en) 2006-05-18 2019-09-04 Molecular profiling of tumors
US17/835,862 US20230123908A1 (en) 2006-05-18 2022-06-08 Molecular profiling of tumors

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US10533508P 2008-10-14 2008-10-14
US10692108P 2008-10-20 2008-10-20
US12/579,241 US20100113299A1 (en) 2008-10-14 2009-10-14 Gene and gene expressed protein targets depicting biomarker patterns and signature sets by tumor type

Related Parent Applications (4)

Application Number Title Priority Date Filing Date
US11/750,721 Continuation-In-Part US8700335B2 (en) 2006-05-18 2007-05-18 System and method for determining individualized medical intervention for a disease state
US13/117,687 Continuation-In-Part US20130072389A1 (en) 2008-09-16 2011-05-27 Theranostic and diagnostic methods using sparc and hsp90
US14/473,871 Continuation-In-Part US9383365B2 (en) 2006-05-18 2014-08-29 System and method for determining individualized medical intervention for a disease state
US14/473,881 Continuation-In-Part US9372193B2 (en) 2006-05-18 2014-08-29 System and method for determining individualized medical intervention for a disease state

Related Child Applications (2)

Application Number Title Priority Date Filing Date
US13/188,350 Continuation US20120015843A1 (en) 2006-05-18 2011-07-21 Gene and gene expressed protein targets depicting biomarker patterns and signature sets by tumor type
US14/175,800 Continuation US9064045B2 (en) 2006-05-18 2014-02-07 Molecular profiling of tumors

Publications (1)

Publication Number Publication Date
US20100113299A1 true US20100113299A1 (en) 2010-05-06

Family

ID=42107198

Family Applications (5)

Application Number Title Priority Date Filing Date
US12/579,241 Abandoned US20100113299A1 (en) 2006-05-18 2009-10-14 Gene and gene expressed protein targets depicting biomarker patterns and signature sets by tumor type
US13/188,350 Abandoned US20120015843A1 (en) 2006-05-18 2011-07-21 Gene and gene expressed protein targets depicting biomarker patterns and signature sets by tumor type
US14/070,357 Abandoned US20140057986A1 (en) 2008-10-14 2013-11-01 Gene and gene expressed protein targets depicting biomarker patterns and signature sets by tumor type
US14/170,370 Abandoned US20140149136A1 (en) 2006-05-18 2014-01-31 Gene and gene expressed protein targets depicting biomarker patterns and signature sets by tumor type
US14/170,450 Abandoned US20140149137A1 (en) 2006-05-18 2014-01-31 Gene and gene expressed protein targets depicting biomarker patterns and signature sets by tumor type

Family Applications After (4)

Application Number Title Priority Date Filing Date
US13/188,350 Abandoned US20120015843A1 (en) 2006-05-18 2011-07-21 Gene and gene expressed protein targets depicting biomarker patterns and signature sets by tumor type
US14/070,357 Abandoned US20140057986A1 (en) 2008-10-14 2013-11-01 Gene and gene expressed protein targets depicting biomarker patterns and signature sets by tumor type
US14/170,370 Abandoned US20140149136A1 (en) 2006-05-18 2014-01-31 Gene and gene expressed protein targets depicting biomarker patterns and signature sets by tumor type
US14/170,450 Abandoned US20140149137A1 (en) 2006-05-18 2014-01-31 Gene and gene expressed protein targets depicting biomarker patterns and signature sets by tumor type

Country Status (6)

Country Link
US (5) US20100113299A1 (en)
EP (2) EP2347009A4 (en)
CN (2) CN106153918A (en)
CA (1) CA2739675C (en)
IL (1) IL212349A0 (en)
WO (1) WO2010045318A2 (en)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080014146A1 (en) * 2006-05-18 2008-01-17 Von Hoff Daniel D System and method for determining individualized medical intervention for a disease state
US20100304989A1 (en) * 2009-02-11 2010-12-02 Von Hoff Daniel D Molecular profiling of tumors
US20130254547A1 (en) * 2012-03-23 2013-09-26 International Business Machines Corporation Encrypted transmission to and storage of surprisal data
US10331626B2 (en) 2012-05-18 2019-06-25 International Business Machines Corporation Minimization of surprisal data through application of hierarchy filter pattern
US10636512B2 (en) 2017-07-14 2020-04-28 Cofactor Genomics, Inc. Immuno-oncology applications using next generation sequencing

Families Citing this family (33)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
NZ556673A (en) 2005-02-03 2010-03-26 Gen Hospital Corp Method for treating gefitinib and/or erlotinib resistant cancer with an EGFR inhibitor
BRPI0618042A2 (en) 2005-11-04 2011-08-16 Wyeth Corp uses of a rapamycin and herceptin, product, pharmaceutical package, and, pharmaceutical composition
US8338109B2 (en) 2006-11-02 2012-12-25 Mayo Foundation For Medical Education And Research Predicting cancer outcome
US8022216B2 (en) 2007-10-17 2011-09-20 Wyeth Llc Maleate salts of (E)-N-{4-[3-chloro-4-(2-pyridinylmethoxy)anilino]-3-cyano-7-ethoxy-6-quinolinyl}-4-(dimethylamino)-2-butenamide and crystalline forms thereof
WO2009143603A1 (en) 2008-05-28 2009-12-03 Genomedx Biosciences, Inc. Systems and methods for expression-based discrimination of distinct clinical disease states in prostate cancer
US10407731B2 (en) 2008-05-30 2019-09-10 Mayo Foundation For Medical Education And Research Biomarker panels for predicting prostate cancer outcomes
ES2692769T3 (en) 2008-06-17 2018-12-05 Wyeth Llc Antineoplastic combinations containing HKI-272 and vinorelbine
SG10201702382RA (en) 2008-08-04 2017-05-30 Wyeth Llc Antineoplastic combinations of 4-anilino-3-cyanoquinolines and capecitabine
WO2010028288A2 (en) 2008-09-05 2010-03-11 Aueon, Inc. Methods for stratifying and annotating cancer drug treatment options
US9495515B1 (en) 2009-12-09 2016-11-15 Veracyte, Inc. Algorithms for disease diagnostics
US10236078B2 (en) 2008-11-17 2019-03-19 Veracyte, Inc. Methods for processing or analyzing a sample of thyroid tissue
US9074258B2 (en) 2009-03-04 2015-07-07 Genomedx Biosciences Inc. Compositions and methods for classifying thyroid nodule disease
SG174382A1 (en) 2009-04-06 2011-11-28 Wyeth Llc Treatment regimen utilizing neratinib for breast cancer
WO2010129934A2 (en) 2009-05-07 2010-11-11 Veracyte, Inc. Methods and compositions for diagnosis of thyroid conditions
US10446272B2 (en) 2009-12-09 2019-10-15 Veracyte, Inc. Methods and compositions for classification of samples
WO2011087926A1 (en) * 2010-01-13 2011-07-21 Wyeth Llc A CUT-POINT IN PTEN PROTEIN EXPRESSION THAT ACCURATELY IDENTIFIES TUMORS AND IS PREDICTIVE OF DRUG RESPONSE TO A PAN-ErbB INHIBITOR
AU2011305445B2 (en) 2010-09-24 2017-03-16 The Board Of Trustees Of The Leland Stanford Junior University Direct capture, amplification and sequencing of target DNA using immobilized primers
CN102094084B (en) * 2010-11-24 2012-09-19 中山大学附属第三医院 Fluorescent quantitative PCR (Polymerase Chain Reaction) method and kit for detecting EphA2 gene expression level and application thereof
AU2012352153B2 (en) 2011-12-13 2018-07-26 Veracyte, Inc. Cancer diagnostics using non-coding transcripts
EP2885640B1 (en) 2012-08-16 2018-07-18 Genomedx Biosciences, Inc. Prostate cancer prognostics using biomarkers
US10942184B2 (en) 2012-10-23 2021-03-09 Caris Science, Inc. Aptamers and uses thereof
CN114606309A (en) 2014-11-05 2022-06-10 威拉赛特公司 Diagnostic system and method using machine learning and high-dimensional transcription data
CA2991045A1 (en) 2015-06-29 2017-01-05 Caris Science, Inc. Therapeutic oligonucleotides binding c1q
US10941176B2 (en) 2015-07-28 2021-03-09 Caris Science, Inc. Therapeutic oligonucleotides
CA3018066A1 (en) 2016-03-18 2017-09-21 Caris Science, Inc. Oligonucleotide probes and uses thereof
AU2017271579B2 (en) 2016-05-25 2023-10-19 Caris Science, Inc. Oligonucleotide probes and uses thereof
EP3504348B1 (en) 2016-08-24 2022-12-14 Decipher Biosciences, Inc. Use of genomic signatures to predict responsiveness of patients with prostate cancer to post-operative radiation therapy
CA3050984A1 (en) 2017-01-20 2018-07-26 Decipher Biosciences, Inc. Molecular subtyping, prognosis, and treatment of bladder cancer
EP3593140A4 (en) 2017-03-09 2021-01-06 Decipher Biosciences, Inc. Subtyping prostate cancer to predict response to hormone therapy
WO2018205035A1 (en) 2017-05-12 2018-11-15 Genomedx Biosciences, Inc Genetic signatures to predict prostate cancer metastasis and identify tumor agressiveness
US11217329B1 (en) 2017-06-23 2022-01-04 Veracyte, Inc. Methods and systems for determining biological sample integrity
AU2019389175A1 (en) 2018-11-30 2021-06-10 Caris Mpi, Inc. Next-generation molecular profiling
EP4069865A4 (en) 2019-12-02 2023-12-20 Caris MPI, Inc. Pan-cancer platinum response predictor

Citations (72)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5610281A (en) * 1994-05-03 1997-03-11 Brigham & Women's Hospital, Inc. Antibodies for modulating heterotypic E-cadherin interactions with human T lymphocytes
US5693473A (en) * 1994-08-12 1997-12-02 Myriad Genetics, Inc. Linked breast and ovarian cancer susceptibility gene
US5710001A (en) * 1994-08-12 1998-01-20 Myriad Genetics, Inc. 17q-linked breast and ovarian cancer susceptibility gene
US5747282A (en) * 1994-08-12 1998-05-05 Myraid Genetics, Inc. 17Q-linked breast and ovarian cancer susceptibility gene
US5753441A (en) * 1994-08-12 1998-05-19 Myriad Genetics, Inc. 170-linked breast and ovarian cancer susceptibility gene
US5837492A (en) * 1995-12-18 1998-11-17 Myriad Genetics, Inc. Chromosome 13-linked breast cancer susceptibility gene
US5895748A (en) * 1996-11-27 1999-04-20 Johnson; Keith R. Panel of antibodies for detecting cadherins and catenins in tissues and method of using the panel of antibodies
US6013431A (en) * 1990-02-16 2000-01-11 Molecular Tool, Inc. Method for determining specific nucleotide variations by primer extension in the presence of mixture of labeled nucleotides and terminators
US6033857A (en) * 1995-12-18 2000-03-07 Myriad Genetics, Inc. Chromosome 13-linked breast cancer susceptibility gene
US6150514A (en) * 1997-04-09 2000-11-21 University Of Utah Research Foundation 14 Kilobase deletion in the promoter region of BRCA1 in a breast cancer family
US20020095260A1 (en) * 2000-11-28 2002-07-18 Surromed, Inc. Methods for efficiently mining broad data sets for biological markers
US20030091994A1 (en) * 1999-04-28 2003-05-15 Robert B. Jenkins Methods and probe sets for determining prostate cancer prognosis
US20040058352A1 (en) * 2000-09-01 2004-03-25 Ulrike Stein Method of establishing resistance profiles of tissues and cell lines
US20040152112A1 (en) * 2002-11-13 2004-08-05 Thomas Jefferson University Compositions and methods for cancer diagnosis and therapy
US20040191817A1 (en) * 2003-02-20 2004-09-30 Randy Scott Use of intronic RNA to measure gene expression
US6812023B1 (en) * 2000-04-27 2004-11-02 Anosys, Inc. Methods of producing membrane vesicles
US20040265813A1 (en) * 2001-07-05 2004-12-30 Teiji Takechi Dna arrays for measuring sensitivity to anticancer agent
US20050084913A1 (en) * 2003-04-22 2005-04-21 Maxygen, Inc. Novel tumor-associated antigens
US20050186584A1 (en) * 2001-12-21 2005-08-25 Catalyst Biomedica Limited Genes
US20050221398A1 (en) * 2004-01-16 2005-10-06 Ipsogen, Sas, A Corporation Of France Protein expression profiling and breast cancer prognosis
US20050260646A1 (en) * 2004-04-09 2005-11-24 Genomic Health Inc. Gene expression markers for predicting response to chemotherapy
US20060019256A1 (en) * 2003-06-09 2006-01-26 The Regents Of The University Of Michigan Compositions and methods for treating and diagnosing cancer
US20060134664A1 (en) * 2004-11-03 2006-06-22 Scherzer Clemens R Identification of dysregulated genes in patients with neurological diseases
US20060147959A1 (en) * 2004-03-31 2006-07-06 The General Hospital Corporation Method to determine responsiveness of cancer to epidermal growth factor receptor targeting treatments
US7081340B2 (en) * 2002-03-13 2006-07-25 Genomic Health, Inc. Gene expression profiling in biopsied tumor tissues
US20060275844A1 (en) * 2005-04-19 2006-12-07 Linke Steven P Diagnostic markers of breast cancer treatment and progression and methods of use thereof
US7154219B2 (en) * 2002-03-05 2006-12-26 Sanyo Electric Co., Ltd. Organic electroluminescence display with adjacent blocks of luminescent layer
US20070009966A1 (en) * 2005-04-27 2007-01-11 Pommer Ansgar J Method for identification of somatic stem cells
US20070020657A1 (en) * 2005-05-20 2007-01-25 Grebe Stefan K Methods for detecting circulating tumor cells
US20070050146A1 (en) * 2004-05-14 2007-03-01 Itzhak Bentwich Micrornas and uses thereof
US20070099209A1 (en) * 2005-06-13 2007-05-03 The Regents Of The University Of Michigan Compositions and methods for treating and diagnosing cancer
US20070117133A1 (en) * 2004-05-14 2007-05-24 Abraxis Bioscience, Inc. Sparc and methods of use thereof
US20070134687A1 (en) * 2005-09-12 2007-06-14 Aurelium Biopharma Inc. Focused microarray and methods of diagnosing cancer
US20070172857A1 (en) * 2005-12-28 2007-07-26 Sysmex Corporation Primer and method for detecting lymph node metastasis
US7250497B2 (en) * 2002-06-07 2007-07-31 Myriad Genetics, Inc. Large deletions in human BRCA1 gene and use thereof
US20070243552A1 (en) * 2003-04-11 2007-10-18 Williams Inna R Novel approach to molecular diagnosis of human papillomavirus-related diseases
US20070292412A1 (en) * 2006-05-09 2007-12-20 Oy Jurilab Ltd Novel genes and markers in type 2 diabetes and obesity
US20080004233A1 (en) * 2006-06-27 2008-01-03 University Of South Florida Delta-Tocotrienol Treatment and Prevention of Pancreatic Cancer
US7319007B2 (en) * 2003-06-12 2008-01-15 Pomeranian Academy Of Medicine Determining a predisposition to cancer
US20080014598A1 (en) * 2006-07-13 2008-01-17 Cell Signaling Technology, Inc. Phospho-specific antibodies to pi3k regulatory subunit and uses thereof
US20080038271A1 (en) * 2006-06-05 2008-02-14 Amler Lukas C Extending survival of cancer patients with elevated levels of EGF or TGF-alpha
US20080064049A1 (en) * 2005-10-31 2008-03-13 The Regents Of The University Of Michigan Compositions and methods for treating and diagnosing cancer
US20080090233A1 (en) * 2004-05-27 2008-04-17 The Regents Of The University Of Colorado Methods for Prediction of Clinical Outcome to Epidermal Growth Factor Receptor Inhibitors by Cancer Patients
US20080096768A1 (en) * 2000-03-31 2008-04-24 University Of Southern California Epigenetic sequences for esophageal adenocarcinoma
US20080213280A1 (en) * 2003-04-09 2008-09-04 Genentech, Inc. Therapy of autoimmune disease in a patient with an inadequate response to a tnf-alpha inhibitor
US20080220418A1 (en) * 2004-09-30 2008-09-11 Matthias Ballhause Method For Providing Dna Fragments Derived From An Archived Sample
US20080226645A1 (en) * 2007-01-10 2008-09-18 Wyeth Methods and compositions for assessment and treatment of asthma
US7442507B2 (en) * 2005-01-24 2008-10-28 New York University School Of Medicine Methods for detecting circulating mutant BRAF DNA
US20080268449A1 (en) * 2007-02-26 2008-10-30 John Wayne Cancer Institute Utility of b-raf dna mutation in diagnosis and treatment of cancer
US20080312199A1 (en) * 2006-12-15 2008-12-18 Glinsky Gennadi V Treatments of therapy resistant diseases and drug combinations for treating the same
US20080318230A1 (en) * 2003-05-30 2008-12-25 David Agus Gene expression markers for response to egfr inhibitor drugs
US20090061454A1 (en) * 2006-03-09 2009-03-05 Brody Jerome S Diagnostic and prognostic methods for lung disorders using gene expression profiles from nose epithelial cells
US20090061422A1 (en) * 2005-04-19 2009-03-05 Linke Steven P Diagnostic markers of breast cancer treatment and progression and methods of use thereof
US20090092983A1 (en) * 2003-08-28 2009-04-09 Daniel Birnbaum Identification of an erbb2 gene expression signature in breast cancers
US20090098538A1 (en) * 2006-03-31 2009-04-16 Glinsky Gennadi V Prognostic and diagnostic method for disease therapy
US7526387B2 (en) * 2003-07-10 2009-04-28 Genomic Health, Inc. Expression profile algorithm and test for cancer prognosis
US20090118175A1 (en) * 2005-05-06 2009-05-07 Macina Roberto A Compositions and Methods for Detection, Prognosis and Treatment of Breast Cancer
US20090130125A1 (en) * 2002-08-12 2009-05-21 Igeneong Krebs-Immuntherapie Forschungs- Und Entwicklungs-Ag Combination of tumor-associated surface protein antigens and tumor-associated sugars in the treatment and diagnosis of cancer
US20090155798A1 (en) * 2007-11-30 2009-06-18 Applied Genomics, Inc. Tle3 as a marker for chemotherapy
US20090170715A1 (en) * 2006-03-31 2009-07-02 Glinsky Gennadi V Prognostic and diagnostic method for cancer therapy
US7560226B2 (en) * 1998-12-23 2009-07-14 Medsaic Pty Limited Assay to detect a binding partner
US20090181406A1 (en) * 2002-08-01 2009-07-16 Rudiger Ridder Kits for detecting cervical dysplasia
US20090215642A1 (en) * 2005-12-09 2009-08-27 Knudson Alfred G Methods and Compositions for Assessing Alterations in Gene Expression Patterns in Clinically Normal Tissues Obtained from Heterozygous Carriers of Mutant Genes Associated with Cancer and Methods of Use Thereof
US20090226902A1 (en) * 2005-10-12 2009-09-10 Hemmo Arjan Drexhage Method to Diagnose or Screen for Inflammatory Diseases
US20090233279A1 (en) * 2005-03-16 2009-09-17 Sidney Kimmel Cancer Center Methods and Compositions for Predicting Death from Cancer and Prostate Cancer Survival Using Gene Expression Signatures
US7593913B2 (en) * 2006-01-11 2009-09-22 Siemens Medical Solutions Usa, Inc. Systems and method for integrative medical decision support
US20090258436A1 (en) * 2006-07-13 2009-10-15 Peter Hornbeck Reagents for the Detection of Protein Phosphorylation in Signaling Pathways
US20090280493A1 (en) * 2006-09-08 2009-11-12 Siemens Healthcare Diagnostics Inc. Methods and Compositions for the Prediction of Response to Trastuzumab Containing Chemotherapy Regimen in Malignant Neoplasia
US20090311702A1 (en) * 2008-05-12 2009-12-17 Steve Shak Tests to predict responsiveness of cancer patients to chemotherapy treatment options
US20100055724A1 (en) * 2007-01-26 2010-03-04 University Of Louisville Research Foundation, Inc. Methods of detecting autoantibodies for diagnosing and characterizing disorders
US20100069298A1 (en) * 2008-09-16 2010-03-18 Robert Penny Methods for Detecting Overexpression of SPARC and Therapeutic and Diagnostic Methods Relating to Same
US20100092524A1 (en) * 2007-01-26 2010-04-15 University Of Louisville Research Foundation, Inc. Modification of exosomal components for use as a vaccine

Family Cites Families (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2000024940A1 (en) * 1998-10-28 2000-05-04 Vysis, Inc. Cellular arrays and methods of detecting and using genetic disorder markers
US8613907B2 (en) * 2000-10-12 2013-12-24 University Of Rochester Compositions that inhibit proliferation of cancer cells
US7529685B2 (en) * 2001-08-28 2009-05-05 Md Datacor, Inc. System, method, and apparatus for storing, retrieving, and integrating clinical, diagnostic, genomic, and therapeutic data
WO2004089073A2 (en) * 2003-04-03 2004-10-21 Genpath Pharmaceuticals, Incorporated Inducible breast cancer model
WO2004112575A2 (en) * 2003-06-20 2004-12-29 Amgen Inc. Gene amplification and overexpression in cancer
BRPI0509580A (en) * 2004-03-30 2007-11-27 Pfizer Prod Inc signal transduction inhibitor combinations
WO2007038792A2 (en) * 2005-09-28 2007-04-05 H. Lee Moffitt Cancer Center Individualized cancer treatments
AU2007253740A1 (en) * 2006-05-18 2007-11-29 Molecular Profiling Institute, Inc. System and method for determining individualized medical intervention for a disease state
JP5759104B2 (en) * 2006-08-11 2015-08-05 コーニンクレッカ フィリップス エヌ ヴェ System and method for associating nucleic acid profiles and proteomic profiles with health care procedures and guidelines in a decision support system
EP1892303A1 (en) * 2006-08-22 2008-02-27 Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. Methods for identifying therapeutical targets in tumors and for determining and targeting angiogenesis and hemostasis related to adenocarcinomas of the lung
SG175680A1 (en) * 2006-10-27 2011-11-28 Decode Genetics Ehf Cancer susceptibility variants on chr8q24.21
WO2008079269A2 (en) * 2006-12-19 2008-07-03 Genego, Inc. Novel methods for functional analysis of high-throughput experimental data and gene groups identified therfrom

Patent Citations (85)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6013431A (en) * 1990-02-16 2000-01-11 Molecular Tool, Inc. Method for determining specific nucleotide variations by primer extension in the presence of mixture of labeled nucleotides and terminators
US5610281A (en) * 1994-05-03 1997-03-11 Brigham & Women's Hospital, Inc. Antibodies for modulating heterotypic E-cadherin interactions with human T lymphocytes
US6300080B1 (en) * 1994-05-03 2001-10-09 Brigham And Women's Hospital, Inc. Methods and compositions for modulating heterotypic E-cadherin interactions with T lymphocytes
US20010018189A1 (en) * 1994-05-03 2001-08-30 Brenner Michael B. Methods and compositions for modulating heterotypic E-cadherin interactions with T lymphocytes
US6406870B2 (en) * 1994-05-03 2002-06-18 The Brigham And Women's Hospital, Inc. Methods and compositions for modulating heterotypic E-cadherin interactions with T lymphocytes
US20020192724A1 (en) * 1994-05-03 2002-12-19 Brenner Michael B. Methods and compositions for modulating heterotypic E-cadherin interactions with T lymphocytes
US7029676B2 (en) * 1994-05-03 2006-04-18 The Brigham And Women's Hospital, Inc. Methods and compositions for modulating heterotypic E-cadherin interactions with T lymphocytes
US5747282A (en) * 1994-08-12 1998-05-05 Myraid Genetics, Inc. 17Q-linked breast and ovarian cancer susceptibility gene
US5753441A (en) * 1994-08-12 1998-05-19 Myriad Genetics, Inc. 170-linked breast and ovarian cancer susceptibility gene
US5710001A (en) * 1994-08-12 1998-01-20 Myriad Genetics, Inc. 17q-linked breast and ovarian cancer susceptibility gene
US5693473A (en) * 1994-08-12 1997-12-02 Myriad Genetics, Inc. Linked breast and ovarian cancer susceptibility gene
US5837492A (en) * 1995-12-18 1998-11-17 Myriad Genetics, Inc. Chromosome 13-linked breast cancer susceptibility gene
US6033857A (en) * 1995-12-18 2000-03-07 Myriad Genetics, Inc. Chromosome 13-linked breast cancer susceptibility gene
US6124104A (en) * 1995-12-18 2000-09-26 Myriad Genectics, Inc. Chromosome 13-linked breast cancer susceptibility gene
US5997866A (en) * 1996-11-27 1999-12-07 Johnson; Keith R. Panel of antibodies for detecting cadherins, catenins and plaque proteins in tissues and method of using the panel
US5895748A (en) * 1996-11-27 1999-04-20 Johnson; Keith R. Panel of antibodies for detecting cadherins and catenins in tissues and method of using the panel of antibodies
US6150514A (en) * 1997-04-09 2000-11-21 University Of Utah Research Foundation 14 Kilobase deletion in the promoter region of BRCA1 in a breast cancer family
US7560226B2 (en) * 1998-12-23 2009-07-14 Medsaic Pty Limited Assay to detect a binding partner
US20030091994A1 (en) * 1999-04-28 2003-05-15 Robert B. Jenkins Methods and probe sets for determining prostate cancer prognosis
US20080096768A1 (en) * 2000-03-31 2008-04-24 University Of Southern California Epigenetic sequences for esophageal adenocarcinoma
US6812023B1 (en) * 2000-04-27 2004-11-02 Anosys, Inc. Methods of producing membrane vesicles
US20040058352A1 (en) * 2000-09-01 2004-03-25 Ulrike Stein Method of establishing resistance profiles of tissues and cell lines
US20020095260A1 (en) * 2000-11-28 2002-07-18 Surromed, Inc. Methods for efficiently mining broad data sets for biological markers
US20040265813A1 (en) * 2001-07-05 2004-12-30 Teiji Takechi Dna arrays for measuring sensitivity to anticancer agent
US20050186584A1 (en) * 2001-12-21 2005-08-25 Catalyst Biomedica Limited Genes
US7154219B2 (en) * 2002-03-05 2006-12-26 Sanyo Electric Co., Ltd. Organic electroluminescence display with adjacent blocks of luminescent layer
US7081340B2 (en) * 2002-03-13 2006-07-25 Genomic Health, Inc. Gene expression profiling in biopsied tumor tissues
US20070141589A1 (en) * 2002-03-13 2007-06-21 Baker Joffre B Gene expression profiling in biopsied tumor tissues
US20070065845A1 (en) * 2002-03-13 2007-03-22 Baker Joffre B Gene expression profiling in biopsied tumor tissues
US7250497B2 (en) * 2002-06-07 2007-07-31 Myriad Genetics, Inc. Large deletions in human BRCA1 gene and use thereof
US20080318224A1 (en) * 2002-06-07 2008-12-25 Myriad Genetics, Incorporated Large deletions in human brca1 gene and use thereof
US20080318223A1 (en) * 2002-06-07 2008-12-25 Myriad Genetics, Incorporated Large deletions in human brca1 gene and use thereof
US20090181406A1 (en) * 2002-08-01 2009-07-16 Rudiger Ridder Kits for detecting cervical dysplasia
US20090130125A1 (en) * 2002-08-12 2009-05-21 Igeneong Krebs-Immuntherapie Forschungs- Und Entwicklungs-Ag Combination of tumor-associated surface protein antigens and tumor-associated sugars in the treatment and diagnosis of cancer
US20040152112A1 (en) * 2002-11-13 2004-08-05 Thomas Jefferson University Compositions and methods for cancer diagnosis and therapy
US20040191817A1 (en) * 2003-02-20 2004-09-30 Randy Scott Use of intronic RNA to measure gene expression
US20080213280A1 (en) * 2003-04-09 2008-09-04 Genentech, Inc. Therapy of autoimmune disease in a patient with an inadequate response to a tnf-alpha inhibitor
US20070243552A1 (en) * 2003-04-11 2007-10-18 Williams Inna R Novel approach to molecular diagnosis of human papillomavirus-related diseases
US20050084913A1 (en) * 2003-04-22 2005-04-21 Maxygen, Inc. Novel tumor-associated antigens
US20080318230A1 (en) * 2003-05-30 2008-12-25 David Agus Gene expression markers for response to egfr inhibitor drugs
US20060019256A1 (en) * 2003-06-09 2006-01-26 The Regents Of The University Of Michigan Compositions and methods for treating and diagnosing cancer
US7319007B2 (en) * 2003-06-12 2008-01-15 Pomeranian Academy Of Medicine Determining a predisposition to cancer
US20090197255A1 (en) * 2003-06-12 2009-08-06 Pomeranian Academy Of Medicine Determining a predisposition to cancer
US7526387B2 (en) * 2003-07-10 2009-04-28 Genomic Health, Inc. Expression profile algorithm and test for cancer prognosis
US20090280490A1 (en) * 2003-07-10 2009-11-12 Baker Joffre B Expression Profile Algorithm and Test for Cancer Prognosis
US20090092983A1 (en) * 2003-08-28 2009-04-09 Daniel Birnbaum Identification of an erbb2 gene expression signature in breast cancers
US20050221398A1 (en) * 2004-01-16 2005-10-06 Ipsogen, Sas, A Corporation Of France Protein expression profiling and breast cancer prognosis
US20060147959A1 (en) * 2004-03-31 2006-07-06 The General Hospital Corporation Method to determine responsiveness of cancer to epidermal growth factor receptor targeting treatments
US20050260646A1 (en) * 2004-04-09 2005-11-24 Genomic Health Inc. Gene expression markers for predicting response to chemotherapy
US20070117133A1 (en) * 2004-05-14 2007-05-24 Abraxis Bioscience, Inc. Sparc and methods of use thereof
US20070050146A1 (en) * 2004-05-14 2007-03-01 Itzhak Bentwich Micrornas and uses thereof
US20080090233A1 (en) * 2004-05-27 2008-04-17 The Regents Of The University Of Colorado Methods for Prediction of Clinical Outcome to Epidermal Growth Factor Receptor Inhibitors by Cancer Patients
US20080220418A1 (en) * 2004-09-30 2008-09-11 Matthias Ballhause Method For Providing Dna Fragments Derived From An Archived Sample
US20060134664A1 (en) * 2004-11-03 2006-06-22 Scherzer Clemens R Identification of dysregulated genes in patients with neurological diseases
US7442507B2 (en) * 2005-01-24 2008-10-28 New York University School Of Medicine Methods for detecting circulating mutant BRAF DNA
US20090233279A1 (en) * 2005-03-16 2009-09-17 Sidney Kimmel Cancer Center Methods and Compositions for Predicting Death from Cancer and Prostate Cancer Survival Using Gene Expression Signatures
US20090061422A1 (en) * 2005-04-19 2009-03-05 Linke Steven P Diagnostic markers of breast cancer treatment and progression and methods of use thereof
US20060275844A1 (en) * 2005-04-19 2006-12-07 Linke Steven P Diagnostic markers of breast cancer treatment and progression and methods of use thereof
US20070009966A1 (en) * 2005-04-27 2007-01-11 Pommer Ansgar J Method for identification of somatic stem cells
US20090118175A1 (en) * 2005-05-06 2009-05-07 Macina Roberto A Compositions and Methods for Detection, Prognosis and Treatment of Breast Cancer
US20070020657A1 (en) * 2005-05-20 2007-01-25 Grebe Stefan K Methods for detecting circulating tumor cells
US20070099209A1 (en) * 2005-06-13 2007-05-03 The Regents Of The University Of Michigan Compositions and methods for treating and diagnosing cancer
US20070134687A1 (en) * 2005-09-12 2007-06-14 Aurelium Biopharma Inc. Focused microarray and methods of diagnosing cancer
US20090226902A1 (en) * 2005-10-12 2009-09-10 Hemmo Arjan Drexhage Method to Diagnose or Screen for Inflammatory Diseases
US20080064049A1 (en) * 2005-10-31 2008-03-13 The Regents Of The University Of Michigan Compositions and methods for treating and diagnosing cancer
US20090215642A1 (en) * 2005-12-09 2009-08-27 Knudson Alfred G Methods and Compositions for Assessing Alterations in Gene Expression Patterns in Clinically Normal Tissues Obtained from Heterozygous Carriers of Mutant Genes Associated with Cancer and Methods of Use Thereof
US20070172857A1 (en) * 2005-12-28 2007-07-26 Sysmex Corporation Primer and method for detecting lymph node metastasis
US7593913B2 (en) * 2006-01-11 2009-09-22 Siemens Medical Solutions Usa, Inc. Systems and method for integrative medical decision support
US20090061454A1 (en) * 2006-03-09 2009-03-05 Brody Jerome S Diagnostic and prognostic methods for lung disorders using gene expression profiles from nose epithelial cells
US20090170715A1 (en) * 2006-03-31 2009-07-02 Glinsky Gennadi V Prognostic and diagnostic method for cancer therapy
US20090098538A1 (en) * 2006-03-31 2009-04-16 Glinsky Gennadi V Prognostic and diagnostic method for disease therapy
US20070292412A1 (en) * 2006-05-09 2007-12-20 Oy Jurilab Ltd Novel genes and markers in type 2 diabetes and obesity
US20080038271A1 (en) * 2006-06-05 2008-02-14 Amler Lukas C Extending survival of cancer patients with elevated levels of EGF or TGF-alpha
US20080004233A1 (en) * 2006-06-27 2008-01-03 University Of South Florida Delta-Tocotrienol Treatment and Prevention of Pancreatic Cancer
US20080014598A1 (en) * 2006-07-13 2008-01-17 Cell Signaling Technology, Inc. Phospho-specific antibodies to pi3k regulatory subunit and uses thereof
US20090258436A1 (en) * 2006-07-13 2009-10-15 Peter Hornbeck Reagents for the Detection of Protein Phosphorylation in Signaling Pathways
US20090280493A1 (en) * 2006-09-08 2009-11-12 Siemens Healthcare Diagnostics Inc. Methods and Compositions for the Prediction of Response to Trastuzumab Containing Chemotherapy Regimen in Malignant Neoplasia
US20080312199A1 (en) * 2006-12-15 2008-12-18 Glinsky Gennadi V Treatments of therapy resistant diseases and drug combinations for treating the same
US20080226645A1 (en) * 2007-01-10 2008-09-18 Wyeth Methods and compositions for assessment and treatment of asthma
US20100055724A1 (en) * 2007-01-26 2010-03-04 University Of Louisville Research Foundation, Inc. Methods of detecting autoantibodies for diagnosing and characterizing disorders
US20100092524A1 (en) * 2007-01-26 2010-04-15 University Of Louisville Research Foundation, Inc. Modification of exosomal components for use as a vaccine
US20080268449A1 (en) * 2007-02-26 2008-10-30 John Wayne Cancer Institute Utility of b-raf dna mutation in diagnosis and treatment of cancer
US20090155798A1 (en) * 2007-11-30 2009-06-18 Applied Genomics, Inc. Tle3 as a marker for chemotherapy
US20090311702A1 (en) * 2008-05-12 2009-12-17 Steve Shak Tests to predict responsiveness of cancer patients to chemotherapy treatment options
US20100069298A1 (en) * 2008-09-16 2010-03-18 Robert Penny Methods for Detecting Overexpression of SPARC and Therapeutic and Diagnostic Methods Relating to Same

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080014146A1 (en) * 2006-05-18 2008-01-17 Von Hoff Daniel D System and method for determining individualized medical intervention for a disease state
US8700335B2 (en) 2006-05-18 2014-04-15 Caris Mpi, Inc. System and method for determining individualized medical intervention for a disease state
US20100304989A1 (en) * 2009-02-11 2010-12-02 Von Hoff Daniel D Molecular profiling of tumors
US8768629B2 (en) 2009-02-11 2014-07-01 Caris Mpi, Inc. Molecular profiling of tumors
US20130254547A1 (en) * 2012-03-23 2013-09-26 International Business Machines Corporation Encrypted transmission to and storage of surprisal data
US10331626B2 (en) 2012-05-18 2019-06-25 International Business Machines Corporation Minimization of surprisal data through application of hierarchy filter pattern
US10353869B2 (en) 2012-05-18 2019-07-16 International Business Machines Corporation Minimization of surprisal data through application of hierarchy filter pattern
US10636512B2 (en) 2017-07-14 2020-04-28 Cofactor Genomics, Inc. Immuno-oncology applications using next generation sequencing

Also Published As

Publication number Publication date
WO2010045318A2 (en) 2010-04-22
CA2739675A1 (en) 2010-04-22
EP2347009A2 (en) 2011-07-27
US20120015843A1 (en) 2012-01-19
CN106153918A (en) 2016-11-23
US20140149136A1 (en) 2014-05-29
US20140149137A1 (en) 2014-05-29
WO2010045318A3 (en) 2010-08-19
CA2739675C (en) 2020-12-01
US20140057986A1 (en) 2014-02-27
IL212349A0 (en) 2011-06-30
EP3075864A1 (en) 2016-10-05
EP2347009A4 (en) 2012-05-30
CN102232117A (en) 2011-11-02

Similar Documents

Publication Publication Date Title
CA2739675C (en) Gene and gene expressed protein targets depicting biomarker patterns and signature sets by tumor type
US9372193B2 (en) System and method for determining individualized medical intervention for a disease state
AU2017279695B2 (en) System and method for determining individualized medical intervention for a disease state
AU2022203286A1 (en) System and method for determining individualized medical intervention for a disease state

Legal Events

Date Code Title Description
STCB Information on status: application discontinuation

Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION