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

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40727465", "kind": "science-record", "revision": 3, "content_hash": "sha256:ea999bcc17798c89715acc7354181d2436970cc86d6ea3ab80244c582b31c7b4", "created_at": "2026-11-01T20:30:50Z", "updated_at": "2026-11-01T22:14:27Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "ISLR as a Cuproptosis-Related Predictor and Therapeutic Target in Heart Failure: A Multi-Omics and Bioinformatics Approach.", "doi": "10.2147/JIR.S490041", "pmid": "40727465", "authors": ["Kai Huang", "Sufan Ding", "Xiangyang Xu", "Chuyi Wang", "Lin Han"], "journal": "Journal of inflammation research", "year": 2025, "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.\nMethods: 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.\nResults: 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.\nConclusion: 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.", "claims": [{"id": "claim-method", "statement": "Student’s t-test was used to evaluate differences between two groups.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40727465", "locator": "sections[13] \"Statistical Analysis\" paragraph 2", "quote": "Student’s t-test was used to evaluate differences between two groups."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All human transcriptomic data used in this study (GSE57338, GSE120895, GSE203160, GSE161470) were obtained from the publicly accessible Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40727465", "locator": "sections[26] \"Ethical Statement\" paragraph 2", "quote": "All human transcriptomic data used in this study (GSE57338, GSE120895, GSE203160, GSE161470) were obtained from the publicly accessible Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "We identified six cuproptosis-related biomarkers (HMOX2, MTSS1L, ISLR, GRB14, ARRDC3, and MEIS1) in HF.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40727465", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "We identified six cuproptosis-related biomarkers (HMOX2, MTSS1L, ISLR, GRB14, ARRDC3, and MEIS1) in HF."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "We identified six cuproptosis-related biomarkers (HMOX2, MTSS1L, ISLR, GRB14, ARRDC3, and MEIS1) in HF.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:40727465"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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