Transient receptor potential channel-related biomarkers for prognostic assessment in hepatocellular carcinoma

Abstract

Hepatocellular carcinoma (HCC) is the most common and fatal form of liver cancer and has been associated with the transient receptor potential channel (TRPC) family. However, the exact mechanism underlying this connection remains elusive. In this study, we aimed to investigate the role of TRPCs in HCC using bioinformatics methods. We employed bioinformatics methods to screen and determine the biomarkers (cytochrome P450 family 2 subfamily C member [CYP2C9], kinesin family member 20A [KIF20A], secreted phosphoprotein 1 [SPP1], and TMF-regulated nuclear protein 1 [TRNP1]) for the risk score of HCC patients. To further verify our findings, we conducted western blotting to determine the expression levels of these biomarkers in HCC and normal samples. Functional characterization of the corresponding genes was conducted through wound healing, cell counting kit-8, and transwell invasion assays using cell lines with gene knockdown or overexpression. Notably, there were significant differences in the levels of 13 types of immune cells between the two risk groups, such as activated dendritic cells and activated CD4+ T cells. Western blotting indicated that KIF20A, SPP1, and TRNP1 were upregulated in HCC, which is consistent with the differential analysis. In the TRNP1 overexpression group, the cell migration distance, cell viability, and cell invasion ability were enhanced. In conclusion, this study identified four biomarkers, namely CYP2C9, KIF20A, SPP1, and TRNP1, and established a risk model for HCC. Our findings can pave the way for improving the diagnosis and treatment options for HCC using TRPC-related biomarkers.

Keywords

Hepatocellular carcinoma / Transient receptor potential / Differentially expressed genes / Consensus clustering analysis / Risk score

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