Identification of Hepatocellular Carcinoma prognostic markers based on 10-immune gene signature

Kaifei Zhao 1, Lin Xu 1, Feng Li 1, Jin Ao 1, Guojun Jiang 1, Rongshu Shi 1, Fang Chen 2, Qing Luo 2

Affiliations

PMID: 32789471
DOI: 10.1042/BSR20200894

Abstract

Background: Due to the heterogeneity of Hepatocellular Carcinoma (HCC), hepatocelluarin-associated differentially expressed genes were analyzed by bioinformatics methods to screen the molecular markers for HCC prognosis and potential molecular targets for immunotherapy.

Methods: RNA-seq data and clinical follow-up data of HCC were downloaded from The Cancer Genome Atlas (TCGA) database. Multivariate Cox analysis and Lasso regression were used to identify robust immunity-related genes. Finally, a risk prognosis model of immune gene pairs was established and verified by clinical features, test set and Gene Expression Omnibus (GEO) external validation set.

Results: A total of 536 immune-related gene (IRGs) were significantly associated with the prognosis of patients with HCC. 10 robust IRGs were finally obtained and a prognostic risk prediction model was constructed by feature selection of Lasso. The risk score of each sample is calculated based on the risk model and is divided into high risk group (Risk-H) and low risk group (Risk-L). Risk models enable risk stratification of samples in training sets, test sets, external validation sets, staging, and subtypes. The area under the curve (AUC) in the training set and the test set were all greater than 0.67, and there were significant overall survival (OS) differences between the Risk-H and Risk-L samples. Compared with the published four models, the traditional clinical features of Grade, Stage and Gender, the model performed better on the risk prediction of HCC prognosis.

Conclusion: This study constructed 10-gene signature as a novel prognostic marker for predicting survival in patients with HCC.

Keywords: 10-gene signature; Hepatocellular Carcinoma; TCGA; bioinformatics; immune related genes.