Li Jing, Su Peng, Li Ting, Hao Yang, Wang Tianjun, Fu Lei, Liu Xin
Wisdom Lake Academy of Pharmacy, Xi'an Jiaotong-Liverpool University, Suzhou, China.
Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.
J Cell Biochem. 2024 Aug;125(8):e30620. doi: 10.1002/jcb.30620. Epub 2024 Jun 25.
Hepatocellular carcinoma (HCC) poses a significant challenge with dismal survival rates, necessitating a deeper understanding of its molecular mechanisms and the development of improved therapies. Metabolic reprogramming, particularly heightened glycolysis, plays a crucial role in HCC progression. Glycolysis-associated genes (GAGs) emerge as key players in HCC pathogenesis, influencing the tumor microenvironment and immune responses. This study aims to investigate the intricate interplay between GAGs and the immune landscape within HCC, offering valuable insights into potential prognostic markers and therapeutic targets to enhance treatment strategies and patient outcomes. Through the exploration of GAGs, we have identified two distinct molecular glycolytic subtypes in HCC patients, each exhibiting significant differences in both the immune microenvironment and prognosis. A risk model comprising five key GAGs was formulated and subsequently evaluated for their predictive accuracy. Our findings underscore the diverse tumor microenvironment and immune responses associated with the varying glycolytic subtypes observed in HCC. The identified key GAGs hold promise as prognostic indicators for evaluating HCC risk levels, predicting patient outcomes, and guiding clinical treatment decisions, particularly in the context of anticipating responses to immunotherapy drugs.
肝细胞癌(HCC)带来了严峻挑战,其生存率令人沮丧,因此有必要更深入地了解其分子机制并开发改进的治疗方法。代谢重编程,尤其是糖酵解增强,在HCC进展中起着关键作用。糖酵解相关基因(GAGs)成为HCC发病机制中的关键因素,影响肿瘤微环境和免疫反应。本研究旨在探究HCC中GAGs与免疫格局之间的复杂相互作用,为潜在的预后标志物和治疗靶点提供有价值的见解,以加强治疗策略并改善患者预后。通过对GAGs的探索,我们在HCC患者中识别出两种不同的分子糖酵解亚型,每种亚型在免疫微环境和预后方面均表现出显著差异。构建了一个包含五个关键GAGs的风险模型,并随后评估了其预测准确性。我们的研究结果强调了与HCC中观察到的不同糖酵解亚型相关的多样肿瘤微环境和免疫反应。所识别的关键GAGs有望作为评估HCC风险水平、预测患者预后以及指导临床治疗决策的预后指标,特别是在预测对免疫治疗药物反应的背景下。