Background
Hepatocellular carcinoma (HCC) is a malignant tumor with a poor prognosis. The progression of numerous malignancies has been linked to abnormal vesicle-mediated transport-related gene (VMTRG) expression. The prognostic importance of VMTRGs in HCC is uncertain nonetheless.
Conclusions
Based on VMTRGs, we have developed a signature that assists in accurate prognosis prediction and formulating personalized treatment strategies for HCC patients.
Methods
Utilizing HCC data from TCGA and ICGC, we employed univariate cox analysis, unsupervised clustering, and lasso analysis to construct molecular subtypes and prognostic signature of HCC based on the prognostic-associated VMTRGs expression levels. Subsequently, we validated the expression levels of the signature genes. We investigated the probable pathways using gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA). Six methods were utilized to compare immune cell infiltration between two risk groups. Moreover, the "pRRophetic" algorithm was utilized to test the drug sensitivity of both groups.
Results
We identified two distinct subtypes with divergent biological behaviors and immune functionality through unsupervised clustering. Subtype C1 demonstrated a poorer prognosis. A prognostic signature incorporating two VMTRGs (KIF2C and RAC1) was formulated. Immunohistochemistry and qRT-PCR analyses unveiled a significant upregulation of these pivotal genes within HCC tissues. The prognosis was worse for the high-risk group, which also had a higher clinicopathological grade, higher levels of tumor mutation burden (TMB), a higher immunological infiltration of CD8 + T cells, a higher expression of immune checkpoints, and enhanced immunotherapy efficacy. These two risk groups also have varied chemotherapy drug sensitivities. Conclusions: Based on VMTRGs, we have developed a signature that assists in accurate prognosis prediction and formulating personalized treatment strategies for HCC patients.