Hepatocellular carcinoma (HCC) is one of the most common malignancies across nations. Although the outcome of HCC has been improved significantly with the advances in comprehensive treatment, patients remain suffered from recurrence as well as metastasis. Therefore, it is urgent to identify reliable biomarkers for predicting the recurrence of HCC, by which the treating strategy can be made to restrain tumor progress. Increasing evidence has shown the association between immune signature and prognosis of HCC. Thus, we aimed to discover an immune-related gene signature that can estimate the recurrence rates of HCC. We collected gene expression profiles and clinical information of patients from GEO and TCGA dataset. Furthermore, we conducted a lasso regression analysis and established a recurrence-related model consisting of 36 immune-related gene pairs (IRGPs) with 54 genes. We validated the IRGPs in the validation cohort and observed that the immune-related signature robustly stratified patients with HCC into high- and low-risk groups in terms of recurrence (P < 0.001). Multivariant Cox regression analysis showed the relationship between the model and recurrence outcomes (Hazard Ratio: 3.81 95% Confidence Interval: 2.90-5.00). Gene Ontology and KEGG enrichment analyses revealed that those genes were enriched in important signaling pathways. In summary, we developed a robust model based on the signature of immune-related genes for forecasting the recurrence outcome of patients with HCC, which holds the potential to assist clinical practice.
Keywords: Hepatocellular carcinoma; immune gene; recurrence; survival.
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