Lei Yang , Kien Pham , Yibo Xi , Shaoning Jiang , Keith D. Robertson , Chen Liu
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引用次数: 0
Abstract
Hepatocellular carcinoma (HCC) is the most common primary liver cancer, with high incidence and mortality worldwide. Despite diagnostic and therapeutic advancements, HCC remains poorly responsive to treatment, with a poor prognosis. Understanding the molecular mechanisms driving HCC is crucial for developing effective therapies. Emerging evidence indicates that dysregulated fatty acid metabolism contributes to HCC. Acyl-CoA medium-chain synthetase 5 (ACSM5), involved in fatty acid metabolism, is down-regulated in HCC; however, its role is not well understood. This study was used to analyze ACSM5 expression in HCC patient samples and cell lines. The newly established ACSM5-overexpressing HCC cell lines, Huh7-ACSM5 and Hepa1-6–ACSM5, were used to investigate the effects and regulatory mechanisms of ACSM5. The results showed that ACSM5 was significantly down-regulated in HCC tumor tissues compared with non-tumor tissues. ACSM5 expression was regulated by DNA methylation, with a DNA methyltransferase 1 (DNMT1) inhibitor effectively increasing ACSM5 expression and reducing promoter region methylation. Overexpression of ACSM5 in Huh7 cells reduced fatty acid accumulation, decreased cell proliferation, migration, and invasion in vitro, and inhibited tumor growth in mouse xenografts. Furthermore, ACSM5 overexpression also decreased STAT3 phosphorylation, subsequently affecting downstream cytokine TGFB and FGF12 mRNA levels. These findings suggest that ACSM5 down-regulation contributes to HCC progression, providing insights into its oncogenic role and highlighting its potential as a biomarker and therapeutic target for HCC.
期刊介绍:
The American Journal of Pathology, official journal of the American Society for Investigative Pathology, published by Elsevier, Inc., seeks high-quality original research reports, reviews, and commentaries related to the molecular and cellular basis of disease. The editors will consider basic, translational, and clinical investigations that directly address mechanisms of pathogenesis or provide a foundation for future mechanistic inquiries. Examples of such foundational investigations include data mining, identification of biomarkers, molecular pathology, and discovery research. Foundational studies that incorporate deep learning and artificial intelligence are also welcome. High priority is given to studies of human disease and relevant experimental models using molecular, cellular, and organismal approaches.