ArticleFrontiers in immunology2024
Predicting mitophagy-related genes and unveiling liver endothelial cell heterogeneity in hepatic ischemia-reperfusion injury.
Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 15 citations in OpenAlex.
- PINK1-Parkin pathway-mediated mitophagy in sepsis: friend or foe?Molecular biology reports · 2026Review
- Article
- Single-cell and bulk transcriptomic analyses uncover immune subtypes associated with programmed cell death features in intrahepatic cholangiocarcinoma.Scientific reports · 2026Article
- Single-cell and multi-omics analysis identifies mitophagy-related biomarkers and therapeutic targets in ischemic stroke.Scientific reports · 2026Article
- Article
- Article
- Discovery of Endothelial-Monocyte Crosstalk in Ischemic-Reperfusion Injury Following Liver Transplantation Based on Integration of Single-Cell RNA and Transcriptome RNA Sequencing.Journal of cellular and molecular medicine · 2025Article
- Effect of remote ischemic postconditioning on hepatic ischemia-reperfusion injury in patients undergoing laparoscopic hepatectomy: a randomized double-blinded controlled trial.Frontiers in medicine · 2025Article
- Novel Perspectives in Hepatic Ischemia-Reperfusion Injury: The cGAS-STING Pathway.Journal of inflammation research · 2025Review
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Hepatic Ischemia-Reperfusion Injury (HIRI) is a major complication in liver transplants and surgeries, significantly affecting postoperative outcomes. The role of mitophagy, essential for removing dysfunctional mitochondria and maintaining cellular balance, remains unclear in HIRI. Methods: To unravel the role of mitophagy-related genes (MRGs) in HIRI, we assembled a comprehensive dataset comprising 44 HIRI samples alongside 44 normal control samples from the Gene Expression Omnibus (GEO) database for this analysis. Using Random Forests and Support Vector Machines - Recursive Feature Elimination (SVM-RFE), we pinpointed eight pivotal genes and developed a logistic regression model based on these findings. Further, we employed consensus cluster analysis for classifying HIRI patients according to their MRG expression profiles and conducted weighted gene co-expression network analysis (WGCNA) to identify clusters of genes that exhibit high correlation within different modules. Additionally, we conducted single-cell RNA sequencing data analysis to explore insights into the behavior of MRGs within the HIRI. Results: We identified eight key genes (FUNDC1, VDAC1, MFN2, PINK1, CSNK2A2, ULK1, UBC, MAP1LC3B) with distinct expressions between HIRI and controls, confirmed by PCR validation. Our diagnostic model, based on these genes, accurately predicted HIRI outcomes. Analysis revealed a strong positive correlation of these genes with monocytic lineage and a negative correlation with B and T cells. HIRI patients were divided into three subclusters based on MRG profiles, with WGCNA uncovering highly correlated gene modules. Single-cell analysis identified two types of endothelial cells with different MRG scores, indicating their varied roles in HIRI. Conclusions: Our study highlights the critical role of MRGs in HIRI and the heterogeneity of endothelial cells. We identified the macrophage migration inhibitory factor (MIF) and cGAS-STING (GAS) pathways as regulators of mitophagy's impact on HIRI. These findings advance our understanding of mitophagy in HIRI and set the stage for future research and therapeutic developments.
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