Identification of a thirteen-gene signature predicting overall survival for hepatocellular carcinoma.

ABSTRACT:

Background

Hepatocellular carcinoma (HCC) is a malignant tumor of the digestive system characterized by mortality rate and poor prognosis. To indicate the prognosis of HCC patients, lots of genes have been screened as prognostic indicators. However, the predictive efficiency of single gene is not enough. Therefore, it is essential to identify a risk-score model based on gene signature to elevate predictive efficiency.

Methods

Lasso regression analysis followed by univariate Cox regression was employed to establish a risk-score model for HCC prognosis prediction based on The Cancer Genome Atlas (TCGA) dataset and Gene Expression Omnibus (GEO) dataset GSE14520. R package 'clusterProfiler' was used to conduct function and pathway enrichment analysis. The infiltration level of v

SUBMITTER: Zhou X 

PROVIDER: S-EPMC8065179 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature