Concurrent analysis of copy number variations and expression profiles to identify genes associated with tumorigenesis and survival outcome in lung adenocarcinoma

Abstract

Lung cancer has been one of the major causes of cancer-related death worldwide. To predict survival outcomes of lung cancer patients, many prognosis gene sets were identified by using gene expression microarrays. However, these gene sets were often inconsistent across independent cohorts. To identify genes with more consistency, we combined gene expression and copy number variations (CNVs). Affymetrix SNP 6.0 and u133plus2.0 microarrays were performed on 42 pairs of lung adenocarcinoma patients. The copy number varied regions (CNVR) existed in more than 30% samples were identified and 475 differentially expressed genes with concordant changes were selected for pathway analysis. Thirteen pathways were significantly enriched among the 475 CNV-associated genes, and survival analyses showed these pathways had generally consistent and significant prediction probabilities across three independent microarray studies. Therefore, integration between gene expression and copy number may help to lower false discovery rate and identify genes used to predict survival outcomes.