An integrated approach to biomarker discovery reveals gene signatures highly predictive of cancer progression.

ABSTRACT: Current cancer biomarkers present variability in their predictive power and demonstrate limited clinical efficacy, possibly due to the lack of functional relevance of biomarker genes to cancer progression. To address this challenge, a biomarker discovery pipeline was developed to integrate gene expression profiles from The Cancer Genome Atlas and essential survival gene datasets from The Cancer Dependency Map, the latter of which catalogs genes driving cancer progression. By applying this pipeline to lung adenocarcinoma, lung squamous cell carcinoma, and glioblastoma, genes highly associated with cancer progression were identified and designated as progression gene signatures (PGSs). Analysis of area under the receiver operating characteristics curve revealed that PGSs predicted patient su

SUBMITTER: Sheng KL 

PROVIDER: S-EPMC7718261 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature