Identification of Tumor Mutation Burden and Immune Infiltrates in Hepatocellular Carcinoma Based on Multi-Omics Analysis

Abstract Background: We aimed to explore the tumor mutational burden (TMB) and immune infiltration in HCC and investigate new biomarkers for immunotherapy.Methods: Transcriptome and gene mutation data were downloaded from the GDC portal, including 374 HCC samples and 50 matched samples. Furthermore, we divided the samples into high and low TMB groups, and analyzed the differential genes between them with GO, KEGG, and GSEA. Cibersort was used to assess the immune cell infiltration in the samples. Finally, univariate and multivariate Cox regression analyses were performed to identify differential genes related to TMB and immune infiltration, and a risk prediction model was constructed.Results: We found 10 frequently mutated genes, including TP53, TTN, CTNNB1, MUC16, ALB, PCLO, MUC, APOB, RYR2, and ABCA. Pathway analysis indicated that these TMB-related differential genes were mainly enriched in PI3K-AKT. Cibersort analysis showed that memory B cells (P=0.02), CD8+ T cells (P=0.09), CD4+ memory activated T cells (P=0.07), and neutrophils (P=0.06) demonstrated a difference in immune infiltration between high and low TMB groups. On multivariate analysis, GABRA3 (P=0.05), CECR7 (P<0.001), TRIM16 (P=0.003), and IL7R (P=0.04) were associated with TMB and immune infiltration. The risk prediction model had an area under the curve (AUC) of 0.69, suggesting that patients with low risk had better survival outcomes.Conclusions: Our study demonstrated for the first time that CECR7, GABRA3, IL7R, and TRIM16L mutations were associated with TMB and promoted antitumor immunity in HCC.