Identification of an E2F Target‐Related Gene Signature to Improve the Prognosis Prediction for Patients with Hepatocellular Carcinoma
Abstract Liver cancer is one of the most common malignant tumors in the world, of which hepatocellular carcinoma (HCC) is the most common histological subtype. Although thousands of biomarkers related to HCC survival and prognosis have been found through database mining, the predictive effects of single-gene biomarkers are not specific enough. Therefore, we aimed to construct a pathway-related signature that could effectively forecast HCC prognosis. We obtained gene expression data and clinical patient information from The Cancer Genome Atlas database (TCGA). Univariate and multivariate Cox regression analyses were used to identify genes enriched in the E2F target gene pathway by Gene Set Enrichment Analysis. In the training set, NBN, PHF5A, CDCA8, AK2, and EXOSC8 were significantly associated with overall survival. They were validated in the test and entire groups, confirmed by Gene Expression Omnibus (GEO), and compared with two known prognostic signatures for HCC. Overall, we demonstrated a novel five-mRNA prognostic signature based on E2F targets that successfully predicted the survival of HCC patients, is independent of clinicopathological data, and displayed superior prediction performance in HCC prognosis. Our study elucidates the cell cycle mechanism in identifying patients with poor HCC prognosis. The application of our five-mRNA prognostic signature may improve risk stratification in HCC patients and existing methods for survival prediction.