The Clinical Relevance and Immune Correlation of SLC10 Family Genes in Liver Cancer.

Abstract

This study was aimed to reveal the clinical relevance and immune correlation of the SLC10 family genes in liver cancer. A comprehensive bioinformatics analysis was utilized to determine the gene expression, genetic alterations, DNA methylation, clinical significance, survival association and immune correlation of seven SLC10 family genes in liver cancer. The multiplexed immunohistochemical technique was applied to determine the association between SLC10A3 protein expression and immune cells, and the correlation between SLC10A3 protein and immune checkpoints (PD1 and PD-L1) in a cohort of 32 individuals with liver cancer. The expression of SLC10 family genes was different between normal liver tissues and malignant liver tissues. SLC10A5 showed the highest alteration rate (8%), followed by SLC10A3 (2.8%). Low expression of SLC10A1 was indicative of poor tumor grade and advanced tumor stage in liver cancer. Scatter plots uncovered that expression of SLC10A3 was inversely associated with SLC10A1 and SLC10A5 expression in liver cancer. The expression of SLC10A1 and SLC10A5 was strongly associated with their DNA methylation. SLC10A1 expression was a reliable genetic biomarker for the prediction of survival outcomes in liver cancer population. Expression of SLC10 family genes was remarkably linked with the abundance of most immune infiltrating cells in liver cancer, and SLC10A3 was the most significant member. The multiplexed immunohistochemical technique confirmed that there existed the significant correlations between SLC10A3 protein expression and CD4 T cells, CD20 B cells and the close association with PD-1 in the stromal area from malignant tissues. The expressions of SLC10 family genes were different between normal liver tissues and malignant liver tissues, and they were correlated with each other in liver cancer. SLC10A1 possesses the most significant correlation with survival outcomes. SLC10A3 exhibited the most significant relationship with immune cells, as revealed by bioinformatics analysis and multispectral imaging technique.