Signaling pathway-based identification of extensive prognostic gene signatures for lung adenocarcinoma.

ABSTRACT: Tumor recurrence is the major cause of death in lung cancer treatment. To date, there is no clinically applied gene expression-based model to predict the risk for tumor recurrence in non-small cell lung cancer (NSCLC). We sought to embed crosstalk with major signaling pathways into biomarker identification. Three approaches were used to identify prognostic gene signatures from 442 lung adenocarcinoma samples. Candidate genes co-expressed with 6 or 7 major NSCLC signaling hallmarks were identified from genome-wide coexpression networks specifically associated with different prognostic groups. From these candidate genes, the first approach selected genes significantly associated with disease-specific survival using univariate Cox model. The second approach used random forests to refine the g

SUBMITTER: Wan YW 

PROVIDER: S-EPMC3274612 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature