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ABSTRACT: Background
Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths worldwide and has a poor prognosis. Thus, there is a need for an effective biomarker to improve and predict the prognosis of HCC.Methods
RNA sequencing data, simple nucleotide variation data, and clinical data of HCC patients from The Cancer Genome Atlas (TCGA) to identify mutant genes, simple nucleotide variation data, and clinical data of HCC patients from the International Cancer Genome Consortium (ICGC) to validate the prognostic value of mutant genes were the data sources of the present study. To identify the overall survival (OS)-related mutant genes, a Kaplan-Meier (KM) analysis was conducted. We carried out univariate Cox and multivariate Cox regression analyses to identi
SUBMITTER: Song Z
PROVIDER: S-EPMC10630911 | biostudies-literature | 2023
REPOSITORIES: biostudies-literature