Biomarker discovery in non-small cell lung cancer: integrating gene expression profiling, meta-analysis and tissue microarray validation

ABSTRACT: Background: Global gene expression profiling has been widely used in lung cancer research to identify clinically relevant molecular subtypes as well as to predict prognosis and therapy response. So far, the value of these multi-gene signatures in clinical practice is unclear and the biological importance of individual genes is difficult to assess as the published signatures virtually do not overlap. Methods: Here we describe a novel single institute cohort, including 196 non-small lung cancer (NSCLC) cases with clinical information and long-term follow-up, which was used as a training set to screen for single genes with prognostic impact. The top 450 gene probe sets identified using a univariate Cox regression model (significance level p<0.01) were tested in a meta-analysis including five

ORGANISM(S): Homo sapiens

SUBMITTER: Botling J 

PROVIDER: S-ECPF-GEOD-37745 | biostudies-other | 2013 Jan

REPOSITORIES: biostudies-other