Identification of DNA repair-related genes predicting pathogenesis and prognosis for liver cancer.

ABSTRACT:

Background

Liver cancer (LC) is one of the most fatal cancers throughout the world. More efficient and sensitive gene signatures that could accurately predict survival in LC patients are vitally needed to promote a better individualized and effective treatment.

Material/methods

422 LC and adjacent normal tissues with both RNA-Seq and clinical data in TCGA were embedded in our study. Gene set enrichment analysis (GSEA) was applied to identify genes and hallmark gene sets that are more valuable for liver cancer therapy. Cox regression analysis was used to identify genes related to overall survival (OS) and build the prediction model. cBioPortal database was used to examine the alterations of the panel mRNA signature. ROC curves and Kaplan-Meier curves were used to validate the

SUBMITTER: Zhu W 

PROVIDER: S-EPMC7847017 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature