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Combinatorial Chemistry & High Throughput Screening

Author(s): Zhijian Wang, Xuenuo Chen and Zheng Jiang*

DOI: 10.2174/1386207325666220126104358

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SLC17A2 Expression Correlates with Prognosis and Immune Infiltrates in Hepatocellular Carcinoma

Page: [2001 - 2015] Pages: 15

  • * (Excluding Mailing and Handling)

Abstract

Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors with a dismal prognosis, according to updated statistics. The solute carrier family 17 member 2 (SLC17A2) has not been studied in liver cancer. Therefore, we evaluated the role of SLC17A2 in HCC by bioinformatics analysis.

Objective: The objective of the study was to explore the value of SLC17A2 in the prognosis and diagnosis of hepatocellular carcinoma.

Methods: The expression level of SLC17A2 in HCC and the clinicopathological data were analyzed based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and validated by immunohistochemical staining. In addition, the Kaplan–Meier plotter database and receiver operating characteristic (ROC) curve analysis were used to explore the prognostic and diagnostic significance. Some online databases were used to analyze the relationship between immune cell infiltration and analyze the relationship between immune cell infiltration and SLC17A2 in HCC.

Results: Multivariate Cox regression analysis showed that SLC17A2 expression was low in HCC (P < 0.05) and closely related to the clinical stage of HCC. In addition, SLC17A2 had a certain diagnostic value in HCC according to ROC curve analysis. Further biological analyses showed that SLC17A2 can regulate fatty acid metabolism, amino acid metabolism and cytochrome P450- related metabolism. Notably, we found that SLC17A2 expression was closely correlated with the infiltration of most immune cells in HCC.

Conclusion: SLC17A2 expression is low in HCC and correlates with immune infiltration, so it may serve as an independent prognostic factor for HCC.

Keywords: SLC17A2, hepatocellular carcinoma (HCC), independent prognostic factor, bioinformatics, immunohistochemical staining, immune cell infiltration.

Graphical Abstract

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