PROGNOSTIC AND PREDICTIVE GENE SIGNATURE FOR NON-SMALL CELL LUNG CANCER AND ADJUVANT CHEMOTHERAPY
The application provides methods of prognosing and classifying lung cancer patients into poor survival groups or good survival groups and for determining the benefit of adjuvant chemotherapy by way of a multigene signature. The application also includes kits and computer products for use in the methods of the application.
1 . A method for predicting benefit of adjuvant chemotherapy for a non-small cell lung cancer (NSCLC) patient, comprising:
determining a gene expression profile from a sample of the patient's lung tumor, the gene expression profile comprising the level of expression of from 5 to 14 genes each correlative with survival in NSCLC, and being listed in Table 3; and
classifying the gene expression profile as being predictive of a positive response to adjuvant chemotherapy or as being predictive of non-responsiveness to adjuvant chemotherapy.
2 . The method of claim 1 , wherein the gene expression profile comprises the expression level of from 5 to 13 genes that are correlative with survival in NSCLC, the genes being selected from Table 4A.
3 . The method of claim 1 , wherein the gene expression profile does not include expression level of one or both of MLANA and MYT1L.
4 . The method of claim 1 , wherein the gene expression profile further comprises the level of expression of one or more normalization genes in the sample.
5 . The method of claim 4 , wherein the normalization gene(s) include one or more of BAT1, TBP, PP1A, and GUSB.
6 . The method of claim 5 , wherein a normalization gene is GUSB.
7 . The method of claim 1 , wherein the gene expression profile is determined by quantitative RT-PCR.
8 . The method of claim 1 , wherein the sample is a frozen tumor tissue specimen, or is a formalin-fixed paraffin-embedded tumor tissue specimen.
9 . The method of claim 7 , wherein the RT-PCR amplifies at least one target sequence listed in Table 11.
10 . The method of claim 7 , wherein the quantitative PCR amplifies at least one target sequence listed in Table 9.
11 . The method of claim 7 , wherein the quantitative PCR employs at least one primer or primer set of Table 7 or Table 16.
12 . The method of claim 1 , wherein a product of amplification is detected with a probe selected from Table 16.
13 . A method for preparing a gene expression profile indicative of response to adjuvant chemotherapy for non-small cell lung cancer (NSCLC), comprising:
determining the level of expression of at least 5 genes from Table 4A in a formalin-fixed paraffin-embedded tumor tissue sample from a lung cancer patient;
wherein the expression levels are determined by quantitative RT-PCR, and wherein the gene expression profile includes the expression level of fewer than 15 genes that are correlative with survival in NSCLC.
14 - 22 . (canceled)
23 . The method of claim 1 , wherein the tumor tissue sample is from a stage I or stage II NSCLC patient.
24 . A method of prognosing or classifying a subject with non-small cell lung cancer (NSCLC) comprising the steps:
a. determining the expression of thirteen biomarkers in a test tumor tissue sample from the subject, wherein the biomarkers correspond to genes in Table 4A, and
b. comparing the expression of the thirteen biomarkers in the test sample with expression of the thirteen biomarkers in a control sample,
wherein a difference or a similarity in the expression of the thirteen biomarkers between the control and the test sample is used to prognose or classify the subject with NSCLC into a poor survival group or a good survival group.
25 . A method of predicting prognosis in a subject with non-small cell lung cancer (NSCLC) comprising the steps:
a. obtaining a subject biomarker expression profile in a tumor tissue sample of the subject;
b. obtaining a biomarker reference expression profile associated with a prognosis, wherein the subject biomarker expression profile and the biomarker reference expression profile each have thirteen values, each value representing the expression level of a biomarker, wherein each biomarker corresponds to one gene in Table 4A; and
c. selecting the biomarker reference expression profile most similar to the subject biomarker expression profile, to thereby predict a prognosis for the subject.
26 . The method of claim 25 , wherein the biomarker reference expression profile comprises a poor survival group or a good survival group.
27 - 34 . (canceled)
35 . A method of selecting a therapy for a subject with NSCLC, comprising the steps:
a. determining the expression of thirteen biomarkers in a test tumor tissue sample from the subject, wherein the thirteen biomarkers correspond to the thirteen genes in Table 4A;
b. comparing the expression of the thirteen biomarkers in the test sample with the thirteen biomarkers in a control sample;
c. classifying the subject in a poor survival group or a good survival group, wherein a difference or a similarity in the expression of the thirteen biomarkers between the control sample and the test sample is used to classify the subject into a poor survival group or a good survival group;
d. selecting adjuvant chemotherapy if the subject is classified in the poor survival group and selecting no adjuvant chemotherapy if the subject is classified in the good survival group.
36 . A composition comprising a plurality of isolated nucleic acid sequences, wherein each isolated nucleic acid sequence hybridizes to:
a. a RNA product of 13 genes listed in Table 4A; and/or
b. a nucleic acid complementary to a),
wherein the composition is used to measure the level of RNA expression of the 13 genes.
37 - 40 . (canceled)
41 . A computer implemented product for predicting a prognosis or classifying a subject with NSCLC comprising:
a. a means for receiving values corresponding to a subject expression profile in a subject sample; and
b. a database comprising a reference expression profile associated with a prognosis, wherein the subject biomarker expression profile and the biomarker reference profile each has thirteen values, each value representing the expression level of a biomarker, wherein each biomarker corresponds to one gene in Table 4A;
wherein the computer implemented product selects the biomarker reference expression profile most similar to the subject biomarker expression profile, to thereby predict a prognosis or classify the subject.
42 - 47 . (canceled)
48 . A kit comprising a primer set for amplifying a target sequence in each of from 5 to 14 genes from Table 3, and including at least 5 genes from Table 4A.
49 - 71 . (canceled)