Evidence map›Paper›PMID 42424301›Full record

ArticlePloS one2026

An integrated multi-omics study of key mediators and therapeutic targets for doxorubicin-induced atrial fibrillation.

Zhenli Li, Sihan Liu, Jing He, Tenghui Wang, Jingtao Ma

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Article in PloS one, 2026. 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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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Zhenli LiDepartment of Cardiology, The Fourth Hospital of Hebei Medical University (the Tumor Hospital of Hebei Province), Shijiazhuang, Hebei, People's Republic of China.ORCID https://orcid.org/0009-0003-5420-5538
Sihan LiuThe Fourth Hospital of Hebei Medical University (the Tumor Hospital of Hebei Province), Shijiazhuang, Hebei, People's Republic of China.
Jing HeDepartment of Cardiology, Peking University International Hospital, No.1 Life Park Road, Zhongguancun Life Science Park, Changping District, Beijing, People's Republic of China.
Tenghui WangSchool of Basic Medicine, Hebei Medical University, Shijiazhuang, Hebei, People's Republic of China.
Jingtao MaDepartment of Cardiology, The Fourth Hospital of Hebei Medical University (the Tumor Hospital of Hebei Province), Shijiazhuang, Hebei, People's Republic of China.ORCID https://orcid.org/0009-0007-5866-217X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDoxorubicin (DOX), a widely used chemotherapeutic agent for cancer patients, is associated with a significant risk of inducing atrial fibrillation (AF), a serious cardiac complication that impairs patient prognosis. However, the specific molecular and cellular mechanisms linking DOX cardiotoxicity to AF pathogenesis remain poorly understood.

methodsFollowing processing pharmacovigilance analysis of DOX-related AF events, we employed an integrative multi-omics strategy. Differentially expressed genes (DEGs) were first identified from the atrial transcriptomic dataset. Network toxicology was used to predict DOX targets, which were intersected with AF-related genes and DEGs to identify candidate targets. Functional analyses and protein-protein interaction network analysis was applied to pinpoint hub genes. Their predictive performance was validated in independent datasets. Gene set enrichment analysis (GSEA) and immune infiltration profiling (CIBERSORT) were conducted to elucidate biological functions and immune context. Molecular docking simulations validated direct interactions between DOX and selected proteins. Finally, single-cell RNA sequencing (scRNA-seq) analysis resolved the cell-type-specific expression patterns of key targets.

resultsFunctional analyses implicated the candidate genes in critical pathways. 5 hub genes were further selected from candidate genes using the MCC algorithm. Among 5 hub genes, we identified and validated the combination of CCR2, PDE5A, and CXCR2 showed high predictive accuracy for AF (mean AUC = 0.87), with identifying and validating CCR2 and PDE5A significantly and differentially expressed. GSEA linked CCR2 and PDE5A showed different pathways. Immune infiltration analysis revealed significant alterations in macrophages, monocytes, and T cell subsets in AF tissues. Molecular docking confirmed stable, high-affinity binding between DOX and both CCR2 and PDE5A (binding energy < -7 kcal/mol). Crucially, scRNA-seq analysis demonstrated that CCR2 and PDE5A were differentially expressed in atrial macrophages and fibroblasts respectively.

conclusionThis study suggests that CCR2 and PDE5A may serve as central mediators and potential therapeutic targets for DOX-induced AF, though these findings require experimental validation.

Indexed as

Antibiotics, AntineoplasticAtrial FibrillationDoxorubicinGene Expression ProfilingGene Regulatory NetworksHumansMolecular Docking SimulationMultiomicsProtein Interaction MapsReceptors, CCR2TranscriptomeAntibiotics, AntineoplasticDoxorubicinReceptors, CCR2

Identifiers

PMID42424301
PMCPMC13349181

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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.