Jing Li, Peng Su, Ting Li, Yang Hao, Tianjun Wang, Lei Fu, Xin Liu
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引用次数: 0
Abstract
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.
期刊介绍:
The Journal of Cellular Biochemistry publishes descriptions of original research in which complex cellular, pathogenic, clinical, or animal model systems are studied by biochemical, molecular, genetic, epigenetic or quantitative ultrastructural approaches. Submission of papers reporting genomic, proteomic, bioinformatics and systems biology approaches to identify and characterize parameters of biological control in a cellular context are encouraged. The areas covered include, but are not restricted to, conditions, agents, regulatory networks, or differentiation states that influence structure, cell cycle & growth control, structure-function relationships.