Patent ID: 7955800
Filing Date: 2011-06-07
Classification: C12Q

Abstract:
1. A method for predicting prognosis of survival in a human patient having non-small cell lung cancer, comprising the steps of: (a) obtaining a lung cancer tissue sample from the patient; (b) determining the expression intensity of each gene in a 16-gene set in the lung cancer tissue sample, wherein said 16-gene set comprises 16 genes consisting of annexin A5 (ANXA5; SEQ ID NO: 28), lymphocyte-specific protein tyrosine kinase (LCK; SEQ ID NO: 29), mechanistic target of rapamycin (FRAP1; SEQ ID NO: 30), signal transducer and activator of transcription 1 (STAT1; SEQ ID NO: 31), neurofibromin 1 (NF1; SEQ ID NO: 32), hepatocyte growth factor (HGF; SEQ ID NO: 33), hyaluronan-mediated motility receptor (HMMR; SEQ ID NO: 34), interferon regulatory factor 4 (IRF4; SEQ ID NO: 35), zinc finger protein 264 (ZNF264; SEQ ID NO: 36), v-erb-b2 avian erythroblastic leukemia viral oncogene homolog 3 (ErbB3; SEQ ID NO: 19), signal transducer and activator of transcription 2 (STAT2; SEQ ID NO: 37), cytoplasmic polyadenylation element binding protein 4 (CPEB4; SEQ ID NO: 38), ring finger protein 4 (RNF4; SEQ ID NO: 39), dual specificity phosphatase 6 (DUSP6; SEQ ID NO: 40), monocyte to macrophage differentiation-associated (MMD; SEQ ID NO:41), and discs, large (Drosophila) homolog 2 (DLG2; SEQ ID NO: 42); (c) generating a risk score for said patient from the expression intensities of said 16 genes in the 16-gene set in the lung cancer tissue sample; and (d) predicting the prognosis of survival in the patient by comparing the risk score of the patient with a median of risk scores of a group of non-small cell lung cancer human patients, wherein the median of risk scores is generated from the expression intensities of said 16 genes in the lung cancer tissue samples of the group of non-small cell lung cancer human patients, the patient is predicted to have a poor chance of survival when the risk score of the patient is higher than the median of risk scores and the patient is predicted to have a good chance of survival when the risk score of the patient is lower than the median of risk scores.