Identification of a five-immune gene model as an independent prognostic factor in hepatocellular carcinoma

Abstract

Background

Hepatocellular carcinoma (HCC) is a common malignant tumor with a poor prognosis. We aimed to identify a new prognostic model of HCC based on differentially expressed (DE) immune genes.

Methods

The DE immune genes were identified based on an analysis of 374 cases of HCC and 50 adjacent non-tumor specimens from the Cancer Genome Atlas (TCGA) database. Univariate Cox analysis, Lasso regression, and multivariate Cox analysis were used to construct the model based on the training group. Survival analysis and the receiver operating characteristic (ROC) curves were used to evaluate model performance. The testing group and the entire group were subsequently used for validation of the model.

Results

A five-immune gene model consisted of HSPA4, ISG20L2, NDRG1, EGF, and IL17D was identified. Based on the model, the overall survival was significantly different between the high-risk and low-risk groups (P = 7.953e-06). The AUCs for the model at 1- and 3-year were 0.849 and 0.74, respectively. The reliability of the model was confirmed using the validation groups. The risk score was identified as an independent prognostic parameter and closely related to the content of immune cells from human HCC specimens.

Conclusion

We identified a five-immune gene model that can be used as an independent prognostic marker for HCC.