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ORIGINAL RESEARCH article
Front. Med.
Sec. Precision Medicine
Volume 12 - 2025 | doi: 10.3389/fmed.2025.1501467
This article is part of the Research Topic Unraveling Ischemia-Reperfusion Injury: Advances in Injury Mechanisms and Treatment Targets View all 3 articles
Identification of biomarkers associated with programmed cell death in liver ischemia-reperfusion injury: insights from machine learning frameworks and molecular docking in multiple cohorts
Provisionally accepted
Jifeng Liu 1
Yeheng Jin 2 Fengchen Lv 1 Yao Yang 1
Junchen Li 1
Yunshu Zhang 1
Lei Zhong 1*
Wei Liu 1- 1 First Affiliated Hospital, Dalian Medical University, Dalian, China
- 2 China Medical University, Shenyang, Liaoning Province, China
Liver ischemia-reperfusion injury (LIRI) is a major reason for liver injury that occurs during surgical procedures such as hepatectomy and liver transplantation and is a major cause of graft dysfunction after transplantation. Programmed cell death (PCD) has been found to correlate with the degree of LIRI injury and plays an important role in the treatment of LIRI. We aim to comprehensively explore the expression patterns and mechanism of action of PCD-related genes in LIRI and to find novel molecular targets for early prevention and treatment of LIRI. We first compared the expression profiles, immune profiles, and biological function profiles of LIRI and control samples. We then identified 47 PCDrelated differentially expressed genes in LIRI and used functional enrichment analysis to understand the underlying mechanisms. By utilizing 113 machine learning methods, 11 model genes were identified. ROC curves and confusion matrix from the six cohorts illustrate the superior diagnostic value of our model. Cytoscape was utilized to further screen these 11 genes for the hub gene MYC, which is considered a hub PCD-related target in LIRI. GSEA, GSVA, immune correlation analysis, transcription factor prediction, ceRNA network analysis, and single-cell map further revealed the mechanism of action and regulatory network of MYC in LIRI. Finally, BMS-536924 and PF-431396 were found to be potential therapeutic agents for LIRI, as identified by the CMap database and molecular docking. In conclusion, this study comprehensively characterizes PCD in LIRI and identifies one core molecule, providing a new strategy for early prevention and treatment of LIRI.
Keywords: Liver ischemia-reperfusion injury, programmed cell death, molecular docking, machine learning, biomarkers
Received: 26 Sep 2024; Accepted: 20 Feb 2025.
Copyright: © 2025 Liu, Jin, Lv, Yang, Li, Zhang, Zhong and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Lei Zhong, First Affiliated Hospital, Dalian Medical University, Dalian, China
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