Identification of a Prognostic Model Based on 2-Gene Signature and Analysis of Corresponding Tumor Microenvironment in Alcohol-Related Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the most prevalent malignant tumors with the poor prognosis. Nowadays, alcohol is becoming a leading risk factor of HCC in many countries. In our study, we obtained the DEGs in alcohol-related HCC through two databases (TCGA and GEO). Subsequently, we performed enrichment analyses (GO and KEGG), constructed the PPI network and screened the 53 hub genes by Cytoscape. Two genes (BUB1B and CENPF) from hub genes was screened by LASSO and Cox regression analyses to construct the prognostic model. Then, we found that the high risk group had the worse prognosis and verified the clinical value of the risk score in alcohol-related HCC. Finally, we analyzed the tumor microenvironment between high and low risk groups through CIBERSORT and ESTIMATE. In summary, we constructed the two-gene prognostic model that could predict the poor prognosis in patients with alcohol-related HCC.