BACKGROUND: The purpose of this study was to investigate the potential correlation between Cuproptosis, a newly recognized form of programmed cell death, and heart failure (HF), using an integrative multi-omics analysis. METHODS: All the datasets were downloaded from GEO database. Cuproptosis-related genes (CRGs) were acquired from FerrDb V2 database. Differentially expressed CRGs were obtained in heart failure dataset (GSE57338). Cuproptosis subtypes were identified from HF samples in GSE57338 based on CRGs. CIBERSORT and GSVA analysis were used to explore the immune and pathway characteristics among Cuproptosis subtypes. WGCNA was used to determined the genes related to Cuproptosis subtypes and HF phenotype. The Cuproptosis-related predictive gene in heart failure were defined by machine learning and subjected to external validation. CTD database and molecular docking were applied to seek for the chemicals binding to the selected gene. RESULTS: In the study, it was found that a total of 21 CRGs exhibited dysregulated expression in individuals with heart failure (HF). Furthermore, two distinct subtypes of Cuproptosis were identified. One hundred and three genes (related to Cuproptosis subtypes and HF phenotype) were put into machine learning algorithms and 6 predictive genes were filtered (HMOX2, MTSS1L, ISLR, GRB14, ARRDC3, and MEIS1). Notably, ISLR was found to be upregulated in both dilated cardiomyopathy and ischemic cardiomyopathy. Additionally, the efficacy of Pirinixic acid in providing heart protection against HF induced by pressure overload was demonstrated. CONCLUSION: We identified six cuproptosis-related biomarkers (HMOX2, MTSS1L, ISLR, GRB14, ARRDC3, and MEIS1) in HF. Notably, ISLR was upregulated in HF. The PPARα agonist Pirinixic acid demonstrated therapeutic potential by downregulating ISLR expression, thereby attenuating pressure overload-induced cardiac dysfunction.
ISLR as a Cuproptosis-Related Predictor and Therapeutic Target in Heart Failure: A Multi-Omics and Bioinformatics Approach.
ISLR 作为心力衰竭中与铜凋亡相关的预测因子和治疗靶点:多组学和生物信息学方法
阅读:7
作者:Huang Kai, Ding Sufan, Xu Xiangyang, Wang Chuyi, Han Lin
| 期刊: | Journal of Inflammation Research | 影响因子: | 4.100 |
| 时间: | 2025 | 起止号: | 2025 Jul 22; 18:9699-9716 |
| doi: | 10.2147/JIR.S490041 | 研究方向: | 心血管 |
| 疾病类型: | 心力衰竭 | ||
特别声明
1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。
2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。
3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。
4、投稿及合作请联系:info@biocloudy.com。
