CA2389220A1 - Methods for profiling and classifying tissue using a database that includes indices representative of a tissue population - Google Patents

Methods for profiling and classifying tissue using a database that includes indices representative of a tissue population Download PDF

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Publication number
CA2389220A1
CA2389220A1 CA002389220A CA2389220A CA2389220A1 CA 2389220 A1 CA2389220 A1 CA 2389220A1 CA 002389220 A CA002389220 A CA 002389220A CA 2389220 A CA2389220 A CA 2389220A CA 2389220 A1 CA2389220 A1 CA 2389220A1
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Prior art keywords
tissue
type
tissue specimens
specimens
normal
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CA002389220A
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French (fr)
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CA2389220C (en
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Peter C. Johnson
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Ventana Medical Systems Inc
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Individual
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6803—General methods of protein analysis not limited to specific proteins or families of proteins
    • 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
    • G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S128/00—Surgery
    • Y10S128/92—Computer assisted medical diagnostics
    • Y10S128/923—Computer assisted medical diagnostics by comparison of patient data to other data
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00—Data processing: database and file management or data structures
    • Y10S707/99931—Database or file accessing
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00—Data processing: database and file management or data structures
    • Y10S707/99931—Database or file accessing
    • Y10S707/99933—Query processing, i.e. searching
    • Y10S707/99936—Pattern matching access
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00—Data processing: database and file management or data structures
    • Y10S707/99931—Database or file accessing
    • Y10S707/99937—Sorting
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00—Data processing: database and file management or data structures
    • Y10S707/99941—Database schema or data structure
    • Y10S707/99943—Generating database or data structure, e.g. via user interface
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00—Data processing: database and file management or data structures
    • Y10S707/99941—Database schema or data structure
    • Y10S707/99944—Object-oriented database structure
    • Y10S707/99945—Object-oriented database structure processing

Abstract

A sample of normal tissue specimens obtained from a subset of a population o f subjects with shared characteristics is profiled in order to generate a plurality of structural indices that correspond to statistically significant representations of characteristics of tissue associated with the population. The structural indices include cell density, matrix density, blood vessel density and layer thickness. Alternatively, the sample of normal tissue specimens obtained from the subset of the population of subjects with shared characteristics can also be profiled in order to generate a plurality of cel l function and/or mechanical indices that correspond to statistically significant representations of characteristics of tissue associated with the population. Structural, mechanical and/or cell function indices for a plurality of tissue populations are determined, and then stored in a databas e. The database information is then used to classify tissue specimens (e.g., human tissue specimens, animal tissue specimens, plant tissue specimens, foo d tissue specimens, or manufactured tissue specimens) provided by a user. In particular, a user measures parameters (e.g., structural, mechanical and/or cell function indices) associated with the user's tissue specimens and then compares this information to corresponding parameters for normal tissue in t he database in order to classify the user's tissue specimens as either normal o r abnormal.

Claims (39)

1. ~A method for classifying user-supplied tissue specimens, comprising the steps of:
(A) accessing tissue information representative of a plurality of tissue types in a database, wherein for each tissue type the database includes a plurality of structural indices generated from a sample of normal tissue specimens obtained from a subset of a population of subjects with shared characteristics, wherein the structural indices correspond to statistically significant representations of characteristics of tissue associated with the population, and wherein the plurality of structural indices include cell density, matrix density, blood vessel density and layer thickness;
(B) measuring parameters associated with the user-supplied tissue specimens; and (C) classifying each of the user-supplied tissue specimens by comparing the measured parameters associated with the user-supplied tissue specimens with the tissue information stored in the database.
2. ~The method of claim 1, wherein the user-supplied tissue specimens correspond to manufactured tissue specimens that do not appear normal in total but contain elements that appear or function normally.
3. The method of claim 1, wherein the plurality of structural indices generated in step (A) further include relative cell location, relative matrix location, and relative blood vessel location.
4. The method of claim 3, wherein for each tissue type the database further includes a plurality of cell function indices determined from a plurality of cell function assays performed on a sample of normal tissue specimens obtained from a subset of the population of subjects with shared characteristics, wherein the cell function indices correspond to statistically significant representations of characteristics of tissue associated with the population.
5. The method of claim 4, wherein the cell function indices include location, type and amount of DNA in the normal tissue specimens from the subset.
6. The method of claim 4, wherein the cell function indices include location, type and amount of mRNA in the normal tissue specimens from the subset.
7. The method of claim 4, wherein the cell function indices include location, type and amount of cellular proteins in the normal tissue specimens from the subset.
8. The method of claim 4, wherein the cell function indices include location, type and amount of cellular lipids in the normal tissue specimens from the subset.
9. The method of claim 4, wherein the cell function indices include location, type and amount of cellular ion distributions in the normal tissue specimens from the subset.
10. The method of claim 4, wherein for each tissue type the database further includes a plurality of mechanical indices generated from a sample of normal tissue specimens obtained from a subset of a population of subjects with shared characteristics, wherein the mechanical indices correspond to statistically significant representations of characteristics of tissue associated with the population.
11. The method of claim 10, wherein the mechanical indices include a modulus of elasticity associated with the normal tissue specimens.
12. The method of claim 10, wherein the mechanical indices include a mechanical strength associated with the normal tissue specimens.
13. The method of claim 3, wherein the plurality of tissue types include at least one living tissue type.
14. The method of claim 13, wherein the plurality of tissue types includes at least one human tissue type.
15. The method of claim 13, wherein the plurality of tissue types includes at least one animal tissue type.
16. The method of claim 13, wherein the plurality of tissue types includes at least one plant tissue type.
17. The method of claim 3, wherein the plurality of tissue types include at least one non-living tissue type.
18. The method of claim 3, wherein the plurality of tissue types include at least one food tissue type.
19. The method of claim 3, wherein the plurality of tissue types include at least one abnormal tissue type.
20. The method of claim 19, wherein step (C) comprises:

(C) classifying each of the user-supplied tissue specimens as either normal or abnormal by comparing measured parameters associated with the user-supplied tissue specimens with the tissue information stored in the database.
21. The method of claim 20, wherein the user-supplied tissue specimens correspond to manufactured tissue specimens that do not appear normal in total but contain elements that appear or function normally.
22. The method of claim 1, wherein the plurality of tissue types include at least one virtual tissue type.
23. A method for classifying user-supplied tissue specimens, comprising the steps of:

(A) accessing tissue information representative of a plurality of tissue types in a database, wherein for each tissue type the database includes a plurality of cell function indices determined from a plurality of cell function assays performed on a sample of normal tissue specimens obtained from a subset of a population of subjects with shared characteristics, wherein the cell function indices correspond to statistically significant representations of characteristics of tissue associated with the population;

(B) measuring parameters associated with the user-supplied tissue specimens; and (C) classifying each of the user-supplied tissue specimens by comparing the measured parameters associated with the user-supplied tissue specimens with the tissue information stored in the database.
24. The method of claim 23, wherein the user-supplied tissue specimens correspond to manufactured tissue specimens that do not appear normal in total but contain elements that appear or function normally.
25. The method of claim 23, wherein the cell function indices include location, type and amount of DNA in the normal tissue specimens from the subset.
26. The method of claim 23, wherein the cell function indices include location, type and amount of mRNA in the normal tissue specimens from the subset.
27. The method of claim 23, wherein the cell function indices include location, type and amount of cellular proteins in the normal tissue specimens from the subset.
28. The method of claim 23, wherein the cell function indices include location, type and amount of cellular lipids in the normal tissue specimens from the subset.
29. The method of claim 23, wherein the cell function indices include location, type and amount of cellular ion distributions in the normal tissue specimens from the subset.
30. The method of claim 23, wherein the plurality of tissue types include at least one living tissue type.
31. The method of claim 30, wherein the plurality of tissue types includes at least one human tissue type.
32. The method of claim 30, wherein the plurality of tissue types includes at least one animal tissue type.
33. The method of claim 30, wherein the plurality of tissue types includes at least one plant tissue type.
34. The method of claim 23, wherein the plurality of tissue types include at least one non-living tissue type.
35. The method of claim 23, wherein the plurality of tissue types include at least one food tissue type.
36. The method of claim 23, wherein the plurality of tissue types include at least one abnormal tissue type.
37. The method of claim 36, wherein step (C) comprises:

(C) classifying each of the user-supplied tissue specimens as either normal or abnormal by comparing measured parameters associated with the user-supplied tissue specimens with the tissue information stored in the database.
38. The method of claim 37, wherein the user-supplied tissue specimens correspond to manufactured tissue specimens that do not appear normal in total but contain elements that appear or function normally.
39. The method of claim 23, wherein the plurality of tissue types include at least one virtual tissue type.
CA2389220A 1999-06-23 2000-06-23 Methods for profiling and classifying tissue using a database that includes indices representative of a tissue population Expired - Lifetime CA2389220C (en)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US09/338,909 1999-06-23
US09/338,909 US6611833B1 (en) 1999-06-23 1999-06-23 Methods for profiling and classifying tissue using a database that includes indices representative of a tissue population
PCT/US2000/017391 WO2000079269A1 (en) 1999-06-23 2000-06-23 Methods for profiling and classifying tissue using a database that includes indices representative of a tissue population

Publications (2)

Publication Number Publication Date
CA2389220A1 true CA2389220A1 (en) 2000-12-28
CA2389220C CA2389220C (en) 2011-07-26

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US (2) US6611833B1 (en)
EP (1) EP1194775A4 (en)
JP (1) JP2003502669A (en)
AU (1) AU5888000A (en)
CA (1) CA2389220C (en)
WO (1) WO2000079269A1 (en)

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