Prognostic and predictive value of a malignancy-risk gene signature in early-stage non-small cell lung cancer

J Natl Cancer Inst. 2011 Dec 21;103(24):1859-70. doi: 10.1093/jnci/djr420. Epub 2011 Dec 8.

Abstract

Background: The malignancy-risk gene signature is composed of numerous proliferative genes and has been applied to predict breast cancer risk. We hypothesized that the malignancy-risk gene signature has prognostic and predictive value for early-stage non-small cell lung cancer (NSCLC) patients.

Methods: The ability of the malignancy-risk gene signature to predict overall survival (OS) of early-stage NSCLC patients was tested using a large NSCLC microarray dataset from the Director's Challenge Consortium (n = 442) and two independent NSCLC microarray datasets (n = 117 and 133, for the GSE13213 and GSE14814 datasets, respectively). An overall malignancy-risk score was generated by principal component analysis to determine the prognostic and predictive value of the signature. An interaction model was used to investigate a statistically significant interaction between adjuvant chemotherapy (ACT) and the gene signature. All statistical tests were two-sided.

Results: The malignancy-risk gene signature was statistically significantly associated with OS (P < .001) of NSCLC patients. Validation with the two independent datasets demonstrated that the malignancy-risk score had prognostic and predictive values: Of patients who did not receive ACT, those with a low malignancy-risk score had increased OS compared with a high malignancy-risk score (P = .007 and .01 for the GSE13212 and GSE14814 datasets, respectively), indicating a prognostic value; and in the GSE14814 dataset, patients receiving ACT survived longer in the high malignancy-risk score group (P = .03), and a statistically significant interaction between ACT and the signature was observed (P = .02).

Conclusions: The malignancy-risk gene signature was associated with OS and was a prognostic and predictive indicator. The malignancy-risk gene signature could be useful to improve prediction of OS and to identify those NSCLC patients who will benefit from ACT.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Adult
  • Aged
  • Analysis of Variance
  • Carcinoma, Non-Small-Cell Lung / genetics*
  • Carcinoma, Non-Small-Cell Lung / mortality
  • Carcinoma, Non-Small-Cell Lung / pathology*
  • Female
  • Gene Expression Profiling
  • Gene Expression Regulation, Neoplastic*
  • Humans
  • Kaplan-Meier Estimate
  • Lung Neoplasms / genetics*
  • Lung Neoplasms / mortality
  • Lung Neoplasms / pathology*
  • Male
  • Middle Aged
  • Neoplasm Grading
  • Neoplasm Staging
  • Predictive Value of Tests
  • Prognosis
  • Proportional Hazards Models
  • Reproducibility of Results
  • Survival Rate