器官移植2025，Vol.16Issue(5)：738-746,9.DOI:10.12464/j.issn.1674-7445.2025134
基于机器学习和实验验证筛选肾移植缺血-再灌注损伤中程序性细胞死亡的核心基因
Identification of core genes in programmed cell death during ischemia-reperfusion injury in kidney transplantation based on machine learning and experimental validation
摘要
Abstract
Objective To identify key patterns of programmed cell death(PCD)and core genes during ischemia-reperfusion injury(IRI)in kidney transplantation.Methods Kidney transplant datasets were obtained from gene expression database,and PCD-related differentially expressed genes were screened.The non-negative matrix factorization algorithm was used to classify patients and analyze subtype-specific biological functions and key PCD patterns.Machine learning models combined with univariate Cox regression and Kaplan-Meier survival analysis were employed to identify core PCD genes during IRI in kidney transplantation and explore their correlation with key PCD patterns.A rat kidney transplant model was used to assess IRI severity through hematoxylin-eosin staining,serum creatinine(Scr),blood urea nitrogen(BUN),and Western blotting for key gene protein expression.Results Fourteen PCD-related genes were identified.Patients were classified into metabolic(subtype 1)and inflammatory(subtype 2)subtypes.Subtype 2 activated four key PCD patterns:pyroptosis,necroptosis,apoptosis and immunogenic cell death.The optimal model(XGBoost-CV:10 fold+Lasso-CV:10 fold)and survival analysis identified MCL1,BAG3,and RHOB as core PCD genes during IRI in kidney transplantation,which were broadly correlated with key PCD patterns.Experimental results showed that compared to the sham group,rats in the model group had more severe tubular injury,higher Scr and BUN levels,and increased BAG3,RHOB and MCL1 protein expression(all P<0.001).Conclusions These four PCD patterns are crucial in the pathogenesis of IRI in kidney transplantation.MCL1,BAG3 and RHOB may serve as potential biomarkers and therapeutic targets for IRI in kidney transplantation.关键词
肾移植/缺血-再灌注损伤/机器学习/程序性细胞死亡/炎症反应/细胞焦亡/细胞凋亡/免疫原性细胞死亡Key words
Kidney transplantation/Ischemia-reperfusion injury/Machine learning/Programmed cell death/Inflammatory response/Pyroptosis/Apoptosis/Immunogenic cell death分类
医药卫生引用本文复制引用
何贵柠,朱丽容,杨洁,何真,李明虎,李海滨,文宁,孙煦勇..基于机器学习和实验验证筛选肾移植缺血-再灌注损伤中程序性细胞死亡的核心基因[J].器官移植,2025,16(5):738-746,9.基金项目
广西重点研发计划项目(桂科AB24010059) （桂科AB24010059）
广西医疗卫生适宜技术开发与推广应用项目(S2023078) （S2023078）
