Large-scale analysis reveals a novel risk score to predict overall survival in hepatocellular carcinoma.

ABSTRACT:

Background

Hepatocellular carcinoma (HCC) is a major cause of cancer mortality and an increasing incidence worldwide; however, there are very few effective diagnostic approaches and prognostic biomarkers.

Materials and methods

One hundred forty-nine pairs of HCC samples from Gene Expression Omnibus (GEO) were obtained to screen differentially expressed genes (DEGs) between HCC and normal samples. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, Gene ontology enrichment analyses, and protein-protein interaction network were used. Cox proportional hazards regression analysis was used to identify significant prognostic DEGs, with which a gene expression signature prognostic prediction model was identified in The Cancer Genome Atlas (TCGA) project discovery cohort. Th

SUBMITTER: Zheng Y 

PROVIDER: S-EPMC6252784 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature