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Background <p>Glutathione (GSH) plays a central role in multiple physiological processes, including the maintenance of intracellular redox homeostasis and the detoxification of xenobiotics. While previous studies have linked GSH metabolism to the pathogenesis and treatment of hepatocellular carcinoma (HCC), systematic analysis of the expression profiles of GSH metabolism-related genes in HCC and their consistent correlation with patient prognosis remains insufficiently addressed.</p> Methods <p>In this study, the ribonucleic acid sequencing (RNA-seq) data and clinical information data of HCC were downloaded from public databases. Following Cox regression and consensus clustering analyses, three GSH metabolism-related subtypes with differential survival probability and immune infiltration status were identified in patients with HCC. Next, <i>CDCA8</i>, <i>KIF20A</i>, <i>TRNP1</i>, and <i>ADH4</i> were chosen to establish a prognostic model.</p> Results <p>Compared with those in the low-risk group, patients with high-risk scores exhibited poor survival probability, higher immune scores, decreased benefit from immunotherapy and poor drug sensitivity.</p> Conclusions <p>In summary, this study established a prognostic risk model for HCC based on GSH metabolism-related genes, which could predict the prognosis and characterize immune infiltration status of HCC. This study may contribute to the identification of potential prognostic targets and the development of new clinical management strategies for HCC.</p>

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Prognostic modeling and immune infiltration analysis in hepatocellular carcinoma using glutathione metabolism-associated genes

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月19日

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  • Fuqiang Ma,
  • LiLi,
  • Ziyi Xu,
  • Yingda Xie,
  • Yanpin Ma,
  • Penghui Li

摘要

Background

Glutathione (GSH) plays a central role in multiple physiological processes, including the maintenance of intracellular redox homeostasis and the detoxification of xenobiotics. While previous studies have linked GSH metabolism to the pathogenesis and treatment of hepatocellular carcinoma (HCC), systematic analysis of the expression profiles of GSH metabolism-related genes in HCC and their consistent correlation with patient prognosis remains insufficiently addressed.

Methods

In this study, the ribonucleic acid sequencing (RNA-seq) data and clinical information data of HCC were downloaded from public databases. Following Cox regression and consensus clustering analyses, three GSH metabolism-related subtypes with differential survival probability and immune infiltration status were identified in patients with HCC. Next, CDCA8, KIF20A, TRNP1, and ADH4 were chosen to establish a prognostic model.

Results

Compared with those in the low-risk group, patients with high-risk scores exhibited poor survival probability, higher immune scores, decreased benefit from immunotherapy and poor drug sensitivity.

Conclusions

In summary, this study established a prognostic risk model for HCC based on GSH metabolism-related genes, which could predict the prognosis and characterize immune infiltration status of HCC. This study may contribute to the identification of potential prognostic targets and the development of new clinical management strategies for HCC.