Evidence map›Paper›PMID 40727465›Full record

ArticleJournal of inflammation research2025

ISLR as a Cuproptosis-Related Predictor and Therapeutic Target in Heart Failure: A Multi-Omics and Bioinformatics Approach.

Kai Huang, Sufan Ding, Xiangyang Xu, Chuyi Wang, Lin Han

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Article in Journal of inflammation research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Kai Huang *Department of Cardiovascular Surgery, Changhai Hospital, Second Military Medical University, Shanghai, People's Republic of China.ORCID 0000-0002-9320-0997
Sufan Ding *Department of Cardiovascular Surgery, Changhai Hospital, Second Military Medical University, Shanghai, People's Republic of China.
Xiangyang XuDepartment of Cardiovascular Surgery, Changhai Hospital, Second Military Medical University, Shanghai, People's Republic of China.
Chuyi WangDepartment of Cardiovascular Surgery, Changhai Hospital, Second Military Medical University, Shanghai, People's Republic of China.ORCID 0009-0009-1842-1034
Lin HanDepartment of Cardiovascular Surgery, Changhai Hospital, Second Military Medical University, Shanghai, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

cuproptosisheart failureimmune infiltrationmachine learningmolecular docking

Identifiers

PMID40727465
PMCPMC12301148

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.