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Tumor metabolism has always been the focus of cancer research. SLC16A1, as a key factor in catalysis of monocarboxylate transport across the plasma membrane, has been found to be associated with the occurrence and metastasis of a variety of cancers, but its prognostic significance and mechanism in different tumors are still unclear. Based on the gene expression matrix and clinical information of human cancer tissues acquired from TCGA and GTEX databases, the differential expression of SLC16A1 in different tumors and normal tissues was analyzed. To confirm the association between its expression, the mutation of MMRS gene, and the expression level of DNMTs. Univariate Cox regression was applied to analyze the association between SLC16A1 expression and patient prognosis. The effect of SLC16A1 expression on patient survival was examined by Kaplan Meier analysis. GSEA was used to identify related signaling pathways. The expression of SLC16A1 was differentially expressed in most tumors, especially in the urinary tract where it is commonly highly expressed, and differential expression of SLC16A1 in different clinical stages. SLC16A1 expression was significantly positively correlated with MMRS gene mutation and DNMTS expression. Moreover, high SLC16A1 expression was associated with poorer overall survival (OS) and progression-free survival (PFS) in urological cancers. In particular, the results of the enrichment analysis showed that SLC16A1 was associated with processes such as cell adhesion and many signaling pathways affecting cell cycle were significantly enriched in the group with high-expressed SLC16A1. SLC16A1 expression was upregulated in urological cancer. SLC16A1 may promote tumor development by regulating the epigenetic process of urological cancer and demonstrated a great potential as a prognostic biomarker of urological cancer patients. Copyright © 2021 Zhang, Song, Wang, Guo, Xu and Shen.

Citation

Ling Zhang, Zheng-Shuai Song, Zhi-Shun Wang, Yong-Lian Guo, Chang-Geng Xu, Hao Shen. High Expression of SLC16A1 as a Biomarker to Predict Poor Prognosis of Urological Cancers. Frontiers in oncology. 2021;11:706883


PMID: 34631536

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