Identify an innovative ferroptosis-related gene in hepatocellular carcinoma

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Abstract

Background: SLC1A5 has been demonstrated to be associated with the progression of other tumors; however, studies are lacking in hepatocellular carcinoma (HCC). Here, we identify SLC1A5, as a novel ferroptosis factor, for HCC patients. Methods: The core biomarkers were identified by univariate and multivariate Cox regression analysis, and the genes present in liver cancer were validated using the public database. Then, gene set enrichment analysis (GSEA) was performed to explore the underlying molecular mechanisms. In addition, we explore the relationship between SLC1A5 and clinical factors. Finally, we determine the effect of SLC1A5 on HCC cells using real-time PCR, cell scratch analysis, transwell analysis, and CCK8 analysis in molecular biology experiments. Results: Cox regression model shows that SLC1A5 was an independent risk factor for HCC patients. GSEA results indicated high expression of SLC1A5 related to the fatty acid metabolism pathway. Clinical correlation analysis demonstrates that alpha-fetoprotein (AFP) expression was positively correlated with SLC1A5 (p = 8e−05), and the higher tumor stage means the higher expression of SLC1A5 (p =.02). In addition, SLC1A5 expression was also positively correlated with vascular infiltration of HCC (p =.04). Furthermore, the SLC1A5 function deficiency experiment explored its underlying impact on the biological function of HCC. qPCR, also called quantitative polymerase chain reaction, confirmed that SLC1A5 was highly expressed in liver cancer when compared with normal tissues. Studies have also shown that downregulation of SLC1A5 can inhibit wound healing, invasion, and proliferation of HCC cells. Conclusion: In conclusion, ferroptosis factor SLC1A5 is a new therapeutic target for hepatocellular carcinoma.

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APA

Hu, G., Huang, X., Zhang, B., Gao, P., Wu, W., & Wang, J. (2022). Identify an innovative ferroptosis-related gene in hepatocellular carcinoma. Journal of Clinical Laboratory Analysis, 36(9). https://doi.org/10.1002/jcla.24632

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