Ebpay生命医药出版社

Ebpay生命

102912

论文已发表

提 交 论 文


注册即可获取Ebpay生命的最新动态

注 册



IF 收录期刊



  • 3.4 Breast Cancer (Dove Med Press)
  • 3.2 Clin Epidemiol
  • 2.6 Cancer Manag Res
  • 2.9 Infect Drug Resist
  • 3.7 Clin Interv Aging
  • 5.1 Drug Des Dev Ther
  • 3.1 Int J Chronic Obstr
  • 6.6 Int J Nanomed
  • 2.6 Int J Women's Health
  • 2.9 Neuropsych Dis Treat
  • 2.8 OncoTargets Ther
  • 2.0 Patient Prefer Adher
  • 2.2 Ther Clin Risk Manag
  • 2.5 J Pain Res
  • 3.0 Diabet Metab Synd Ob
  • 3.2 Psychol Res Behav Ma
  • 3.4 Nat Sci Sleep
  • 1.8 Pharmgenomics Pers Med
  • 2.0 Risk Manag Healthc Policy
  • 4.1 J Inflamm Res
  • 2.0 Int J Gen Med
  • 3.4 J Hepatocell Carcinoma
  • 3.0 J Asthma Allergy
  • 2.2 Clin Cosmet Investig Dermatol
  • 2.4 J Multidiscip Healthc



更多详情 >>





已发表论文

一种整合免疫和糖酵解通路的新型预后特征,用于提高肝细胞癌的预后和免疫治疗预测能力

 

Authors Zhang Z, Zhao H, Wang P, Geng X, Yin M, Liu Y, Zhang S, Liang Y, Ji J, Zheng G

Received 5 December 2024

Accepted for publication 10 April 2025

Published 18 April 2025 Volume 2025:12 Pages 805—823

DOI http://doi.org/10.2147/JHC.S510460

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 3

Editor who approved publication: Dr David Gerber

Zeyu Zhang,1 Hongxi Zhao,1 Pengyu Wang,2 Xueyan Geng,1 Maopeng Yin,1 Yingjie Liu,1 Shoucai Zhang,1 Yongyuan Liang,1 Jian Ji,1 Guixi Zheng1,3 

1Department of Clinical Laboratory, Qilu Hospital of Shandong University, Jinan, Shandong, 250012, People’s Republic of China; 2Faculty of Science, University of Alberta, Edmonton, Alberta, T6G 2E9, Canada; 3Shandong Engineering Research Center of Biomarker and Artificial Intelligence Application, Jinan, Shandong, 250012, People’s Republic of China

Correspondence: Guixi Zheng, Email zhengg@sdu.edu.cn

Background: This study aimed to establish an immune-glycolysis-related prognostic signature (IGRPS) to predict hepatocellular carcinoma (HCC) outcomes. Additionally, it explored the role of this signature in the tumor immune microenvironment (TIME), glycolytic pathways, and immunotherapy.
Methods: We analyzed RNA-seq, single-cell sequencing, and immune- and glycolysis-related gene datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Using weighted gene co-expression network analysis (WGCNA), F-test, and Cox regression, we identified key survival-related immune and glycolytic genes (SRIGRGs) and developed an IGRPS through multivariate Cox regression. The IGRPS’s predictive performance was validated in training and validation cohorts using Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curves, and a prognostic nomogram. Its correlation with TIME and its ability to predict immunotherapy outcomes were also assessed. In vitro experiments were conducted to analyze the expression and function of IGRPS genes in HCC.
Results: Thirteen SRIGRGs were identified for constructing the IGRPS. Patients with low-risk scores had significantly longer survival times. The area under the curve (AUC) for ROC curves was over 0.73 for training and 0.7 for validation cohorts, with C-indices of 0.721 and 0.79, respectively. IGRPS was confirmed as an independent prognostic indicator. Patients in the low-risk group showed better responses to combined anti-CTLA4 and anti-PD-1 therapies. In vitro experiments indicated that PRKAG1 and B3GAT3 were upregulated, enhancing glycolysis and promoting HCC cell proliferation and migration.
Conclusion: The IGRPS, based on immune- and glycolysis-related genes, effectively predicted prognosis and immunotherapy responses in HCC patients.

Keywords: HCC, glycolysis, tumor immune microenvironment, prognostic, immunotherapy

Download Article[PDF]