A robust twelve-gene signature for prognosis prediction of hepatocellular carcinoma.

ABSTRACT:

Background

The prognosis of hepatocellular carcinoma (HCC) patients remains poor. Identifying prognostic markers to stratify HCC patients might help to improve their outcomes.

Methods

Six gene expression profiles (GSE121248, GSE84402, GSE65372, GSE51401, GSE45267 and GSE14520) were obtained for differentially expressed genes (DEGs) analysis between HCC tissues and non-tumor tissues. To identify the prognostic genes and establish risk score model, univariable Cox regression survival analysis and Lasso-penalized Cox regression analysis were performed based on the integrated DEGs by robust rank aggregation method. Then Kaplan-Meier and time-dependent receiver operating characteristic (ROC) curves were generated to validate the prognostic performance of risk score in training da

SUBMITTER: Ouyang G 

PROVIDER: S-EPMC7268417 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature