Trans-omics biomarker model improves prognostic prediction accuracy for early-stage lung adenocarcinoma.

ABSTRACT: Limited studies have focused on developing prognostic models with trans-omics biomarkers for early-stage lung adenocarcinoma (LUAD). We performed integrative analysis of clinical information, DNA methylation, and gene expression data using 825 early-stage LUAD patients from 5 cohorts. Ranger algorithm was used to screen prognosis-associated biomarkers, which were confirmed with a validation phase. Clinical and biomarker information was fused using an iCluster plus algorithm, which significantly distinguished patients into high- and low-mortality risk groups (P_discovery = 0.01 and P_validation = 2.71×10^-3). Further, potential functional DNA methylation-gene expression-overall survival pathways were evaluated by causal mediation analysis. The eff

SUBMITTER: Dong X 

PROVIDER: S-EPMC6738411 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature