Identification, monitoring and treatment of disease and characterization of biological condition using gene expression profiles

• US 8,718,946 B2
• Filed: 09/21/2011
• Issued: 05/06/2014
• Est. Priority Date: 11/09/2001
• Status: Expired due to Term

• Current Assignee: Life Technologies Corporation (Thermo Fisher Scientific Incorporated)
• Original Assignee: Life Technologies Corporation (Thermo Fisher Scientific Incorporated)
• Inventors: Bevilacqua, Michael, Cheronis, John, Tryon, Victor, Bankaitis-Davis, Danute
• Primary Examiner(s): ZEMAN, MARY K
• Application Number:
  US13/239,070
• Publication Number:
  US 20120077199A1
• Time in Patent Office: 958 Days
• Field of Search: 702/19
• US Class Current: 702/19
• CPC Class Codes: G01N 2800/042 Disorders of carbohydrate metabolism, e.g. diabetes, glucose metabolism
• CPC Class Codes: G01N 33/57415 of breast
• CPC Class Codes: G01N 33/6803 General methods of protein analysis not limited to specific proteins or families of proteins
• CPC Class Codes: G01N 33/6863 Cytokines, i.e. immune system proteins modifying a biological response such as cell growth proliferation or differentiation, e.g. TNF, CNF, GM-CSF, lymphotoxin, MIF or their receptors
• CPC Class Codes: G01N 33/6869 Interleukin
• CPC Class Codes: G01N 33/6893 related to diseases not provided for elsewhere
• CPC Class Codes: G16B 20/00 ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• CPC Class Codes: G16B 25/00 ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
• CPC Class Codes: G16B 25/10 Gene or protein expression profiling; Expression-ratio estimation or normalisation
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

A method provides an index that is indicative of the state of a subject, as to a biological condition, based on a sample from the subject. An embodiment of this method includes: deriving from the sample a profile data set, the profile data set including a plurality of members, each member being a quantitative measure of the amount of a distinct RNA or protein constituent in a panel of constituents selected so that measurement of the constituents enables evaluation of the biological condition; and in deriving the profile data set, achieving such measure for each constituent under measurement conditions that are substantially repeatable; and applying values from the profile data set to an index function that provides a mapping from an instance of a profile data set into a single-valued measure of biological condition, so as to produce an index pertinent to the biological condition of the subject.

Claims

1. A method of evaluating the efficacy of a therapeutic agent on an inflammatory condition, the method comprising:

a) producing a first index for a sample from a subject, the sample providing a source of RNAs comprising;

i) quantitatively measuring the amount of RNA from the sample from the subject by amplification, wherein a panel of constituents is selected so that measurement conditions of the constituents enables evaluation of said inflammatory condition and wherein the measures of all constituents in the panel form a first profile data set, wherein said amplification for each constituent is under conditions that are (1) within a degree of repeatability of better than five percent; and

(2) the efficiencies of amplification are within two percent,

ii) inserting the values from a first profile data set into an index function derived using latent class modeling, thereby providing a single-valued measure of the inflammatory condition so as to produce an index pertinent to the inflammatory condition of the subject, wherein the first profile data set is derived from quantitatively measuring the amount of RNA of all constituents in said panel from a sample of a plurality of subjects of a relevant population and which measurements form a normative baseline profile data set;

iii) inserting the values from the normative profile data set into the index function, thereby providing a single-valued measure of the inflammatory condition so as to produce an index pertinent to the inflammatory condition of the relevant population,

iv) producing an index of the subject;

v) normalizing the index of the subject with the index of the relevant population to provide the first index; and

(b) evaluating the efficacy of the agent based on a value of the first index prior to treatment and comparing to the value of the first index after treatment, wherein the first index is greater than 1 prior to treatment and the first index after treatment is less that 1 when treatment is efficacious.

2. The method of claim 1, wherein the agent is selected from the group consisting of an anti-inflammatory steroid compound, non-steroidal anti-inflammatory drug and antibiotic.

3. The method of claim 1, wherein the inflammatory condition is caused by, is a result of, or is exacerbated by, an infection.

4. The method of claim 1, wherein treatment of the inflammatory condition is based on the prediction of efficacy of the agent.

5. The method of claim 2, wherein the anti-inflammatory steroid compound is solumedrol, prednisone, or dexamethasone.

6. The method of claim 2, wherein the non-steroidal anti-inflammatory drug is ibuprofen.

7. The method of claim 2, wherein the antibiotic is polymyxin B.

8. The method of claim 2, wherein the anti-inflammatory steroid compound is solumedrol, prednisone, or dexamethasone.

9. The method of claim 1, wherein the panel of constituents comprises IL1A, 1L1B, TNFA, IFNG and IL10.

10. The method of claim 9, wherein the panel further comprises B7, TACI, PLA2G7 and C1QA.

11. The method of claim 9, wherein the panel further comprises GRO1 and GRO2.

12. The method of claim 9, wherein the panel further comprises B7, TACI, PLA2G7, C1QA, GRO1 and GRO2.