期刊
CELLULAR PHYSIOLOGY AND BIOCHEMISTRY
卷 50, 期 3, 页码 924-935出版社
Cell Physiol Biochem Press GmbH & Co
DOI: 10.1159/000494477
关键词
microRNA-124; Monocarboxylate transporter 1; Lactate metabolism; Pancreatic ductal adenocarcinoma
资金
- National Natural Science Foundation of China [81572472, 81773161]
Background/Aims: Increasing evidence shows that reprogramming of energy metabolism is a hallmark of cancer. Considering the emergence of microRNAs as crucial modulators of cancer, this study aimed to better understand the molecular mechanisms of miR-124 in regulating glycolysis in human pancreatic cancer. Methods: RT-PCR was used to investigate the expression of monocarboxylate transporters (MCTs) in pancreatic ductal adenocarcinoma (PDAC) patient samples and the PANC-1 cell line. A public database and immunochemistry were used for comprehensive analysis of MCT1 expression. The targeting of MCT1 by miR124 was predicted by software and validated for the MCT1 3'-UTR by dual-luciferase reporter analysis. Cell proliferation, apoptosis, migration, xenografting, and the intracellular pH and L-lactate levels were assessed. Hypoxia-inducible factor-a (HIF-1a) and lactate dehydrogenase A (LDH-A) expression levels were determined by RT-PCR and western blotting. Results: MCT1 expression was higher in PDAC tissue than in normal tissue. Inhibition of MCT1 affected lactate metabolism, resulting in a higher intracellular pH and less proliferation of PANC-1 cells. MCT1 was the target gene of mi R-124.1n in vitro experiments, mi R-124 inhibited the glycolytic activity of PANC-1 cells by targeting MCT1, further decreasing the tumor phenotype by increasing the intracellular pH through LDH-A and HIF-1 alpha. In in vivo experiments, overexpression of miR-124 and silencing of MCT1 significantly inhibited tumor growth. Conclusion: miR-124 inhibits the progression of PANC-1 by targeting MCT1 in the lactate metabolic pathway. Our findings provide novel evidence for further functional studies of miR-124, which might be useful for future therapeutic approaches to PDAC. (C) 2018 The Author(s)
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