Identification of multi-omics biomarkers and construction of the novel prognostic model for hepatocellular carcinoma.

ABSTRACT: Genome changes play a crucial role in carcinogenesis, and many biomarkers can be used as effective prognostic indicators in various tumors. Although previous studies have constructed many predictive models for hepatocellular carcinoma (HCC) based on molecular signatures, the performance is unsatisfactory. Because multi-omics data can more comprehensively reflect the biological phenomenon of disease, we hope to build a more accurate predictive model by multi-omics analysis. We use the TCGA to identify crucial biomarkers and construct prognostic models through difference analysis, univariate Cox, and LASSO/stepwise Cox analysis. The performances of predictive models were evaluated and validated through survival analysis, Harrell's concordance index (C-index), receiver operating characteristi

SUBMITTER: Liu X 

PROVIDER: S-EPMC9287549 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature