title: Prognostic and predictive value of a malignancy-risk gene signature in early-stage non-small cell lung cancer.
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.
authors.affiliation: Department of Biostatistics, Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA. dung-tsa.chen@moffitt.org
authors.forename: Dung-Tsa
authors.initials: DT
authors.lastname: Chen
authors.forename: Ying-Lin
authors.initials: YL
authors.lastname: Hsu
authors.forename: William J
authors.initials: WJ
authors.lastname: Fulp
authors.forename: Domenico
authors.initials: D
authors.lastname: Coppola
authors.forename: Eric B
authors.initials: EB
authors.lastname: Haura
authors.forename: Timothy J
authors.initials: TJ
authors.lastname: Yeatman
authors.forename: W Douglas
authors.initials: WD
authors.lastname: Cress
mesh_terms: D000328:Adult; D000368:Aged; D000704:Analysis of Variance; D002289:Carcinoma, Non-Small-Cell Lung / Q000235:genetics* / Q000401:mortality / Q000473:pathology*; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D053208:Kaplan-Meier Estimate; D008175:Lung Neoplasms / Q000235:genetics* / Q000401:mortality / Q000473:pathology*; D008297:Male; D008875:Middle Aged; D060787:Neoplasm Grading; D009367:Neoplasm Staging; D011237:Predictive Value of Tests; D011379:Prognosis; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D015996:Survival Rate