In silico development and validation of a novel six-gene-derived signature in hepatocellular carcinoma.

IF 1.7 4区 医学 Q4 ONCOLOGY
Translational cancer research Pub Date : 2025-05-30 Epub Date: 2025-05-27 DOI:10.21037/tcr-2024-2621
Jin He, Binbin Li, Huize Liu, Weijian Chu, Chunhui Rao
{"title":"In silico development and validation of a novel six-gene-derived signature in hepatocellular carcinoma.","authors":"Jin He, Binbin Li, Huize Liu, Weijian Chu, Chunhui Rao","doi":"10.21037/tcr-2024-2621","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Pyruvate metabolism presents a novel, therapeutically targetable metabolic vulnerability in hepatocellular carcinoma (HCC). In this study, we sought to identify HCC molecular subtypes and develop prognostic signatures based on pyruvate metabolism-related genes (PMRGs) to inform personalized therapeutic approaches.</p><p><strong>Methods: </strong>Transcriptional profiles and clinical data of HCC patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. Consensus clustering was employed for molecular classification, while a least absolute shrinkage and selection operator (LASSO) Cox regression model was constructed for risk score calculation. The relationship between the risk score and HCC prognosis, immune landscape, gene expression, and drug sensitivity was analyzed.</p><p><strong>Results: </strong>Twenty PMRGs were identified as significantly associated with HCC prognosis. Consensus clustering of these genes revealed two distinct molecular subtypes that stratified patients into groups with favorable and unfavorable outcomes. A novel six-gene signature, comprising <i>ACACA</i>, <i>ACAT1</i>, <i>CYP1</i>, <i>DLAT</i>, <i>LDHA</i>, and <i>ME1</i>, was developed for HCC prognostication. The receiver operating characteristic (ROC) curve demonstrated robust survival prediction in all cohorts, allowing the stratification of patients into high- and low-risk groups with markedly different overall survival (OS). The signature-derived nomogram displayed appreciable clinical net benefit. Enrichment analysis revealed activation of PMRGs and enrichment of diverse metabolic processes and signaling pathways in the high-risk group. Moreover, the prognostic signature showed significant correlations with immune landscapes and therapeutic responses, enabling prediction of immunotherapy responsiveness.</p><p><strong>Conclusions: </strong>Collectively, a unique PMRG-based signature effectively predicts prognosis in HCC patients and provides valuable insights into chemotherapy and immunotherapy strategies for these individuals.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 5","pages":"2940-2955"},"PeriodicalIF":1.7000,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12169999/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Translational cancer research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.21037/tcr-2024-2621","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/5/27 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Background: Pyruvate metabolism presents a novel, therapeutically targetable metabolic vulnerability in hepatocellular carcinoma (HCC). In this study, we sought to identify HCC molecular subtypes and develop prognostic signatures based on pyruvate metabolism-related genes (PMRGs) to inform personalized therapeutic approaches.

Methods: Transcriptional profiles and clinical data of HCC patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. Consensus clustering was employed for molecular classification, while a least absolute shrinkage and selection operator (LASSO) Cox regression model was constructed for risk score calculation. The relationship between the risk score and HCC prognosis, immune landscape, gene expression, and drug sensitivity was analyzed.

Results: Twenty PMRGs were identified as significantly associated with HCC prognosis. Consensus clustering of these genes revealed two distinct molecular subtypes that stratified patients into groups with favorable and unfavorable outcomes. A novel six-gene signature, comprising ACACA, ACAT1, CYP1, DLAT, LDHA, and ME1, was developed for HCC prognostication. The receiver operating characteristic (ROC) curve demonstrated robust survival prediction in all cohorts, allowing the stratification of patients into high- and low-risk groups with markedly different overall survival (OS). The signature-derived nomogram displayed appreciable clinical net benefit. Enrichment analysis revealed activation of PMRGs and enrichment of diverse metabolic processes and signaling pathways in the high-risk group. Moreover, the prognostic signature showed significant correlations with immune landscapes and therapeutic responses, enabling prediction of immunotherapy responsiveness.

Conclusions: Collectively, a unique PMRG-based signature effectively predicts prognosis in HCC patients and provides valuable insights into chemotherapy and immunotherapy strategies for these individuals.

肝细胞癌中一种新型六基因衍生标记的计算机开发和验证。
背景:丙酮酸代谢在肝细胞癌(HCC)中呈现出一种新的、可治疗的代谢易损性。在这项研究中,我们试图确定HCC分子亚型,并基于丙酮酸代谢相关基因(PMRGs)开发预后特征,为个性化治疗方法提供信息。方法:从Cancer Genome Atlas (TCGA)和Gene Expression Omnibus (GEO)数据库中获取HCC患者的转录谱和临床资料。采用共识聚类进行分子分类,构建最小绝对收缩和选择算子(LASSO) Cox回归模型进行风险评分计算。分析风险评分与HCC预后、免疫景观、基因表达、药物敏感性的关系。结果:20个PMRGs与HCC预后显著相关。这些基因的一致聚类揭示了两种不同的分子亚型,将患者分层成有利和不利的结果组。一种新的六基因标记,包括ACACA, ACAT1, CYP1, DLAT, LDHA和ME1,用于HCC预后。受试者工作特征(ROC)曲线在所有队列中显示了稳健的生存预测,允许将患者分层为总生存(OS)显着不同的高危组和低危组。签名衍生的nomogram显示了明显的临床净收益。富集分析显示,在高危人群中,PMRGs激活,多种代谢过程和信号通路富集。此外,预后特征显示与免疫景观和治疗反应显著相关,从而能够预测免疫治疗反应性。结论:总的来说,基于pmrg的独特特征有效地预测了HCC患者的预后,并为这些个体的化疗和免疫治疗策略提供了有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
2.10
自引率
0.00%
发文量
252
期刊介绍: Translational Cancer Research (Transl Cancer Res TCR; Print ISSN: 2218-676X; Online ISSN 2219-6803; http://tcr.amegroups.com/) is an Open Access, peer-reviewed journal, indexed in Science Citation Index Expanded (SCIE). TCR publishes laboratory studies of novel therapeutic interventions as well as clinical trials which evaluate new treatment paradigms for cancer; results of novel research investigations which bridge the laboratory and clinical settings including risk assessment, cellular and molecular characterization, prevention, detection, diagnosis and treatment of human cancers with the overall goal of improving the clinical care of cancer patients. The focus of TCR is original, peer-reviewed, science-based research that successfully advances clinical medicine toward the goal of improving patients'' quality of life. The editors and an international advisory group of scientists and clinician-scientists as well as other experts will hold TCR articles to the high-quality standards. We accept Original Articles as well as Review Articles, Editorials and Brief Articles.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信