Evidence map›Paper›PMID 41743358›Full record

ArticleFrontiers in molecular biosciences2026

Identification of potential ferroptosis-related biomarkers in proliferative vitreoretinopathy based on machine learning.

Jiangying Liu, Shengxiang Zhang, Lingdan Wu, Yingchao Xue, Boyu Liu, Hongyan Song, Qihua Xu

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Article in Frontiers in molecular biosciences, 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

7 authors.

Jiangying LiuSchool of Optometry, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
Shengxiang ZhangSchool of Optometry, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
Lingdan WuSchool of Optometry, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
Yingchao XueSchool of Optometry, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
Boyu LiuDepartment of Ophthalmology, The Affiliated Eye Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
Hongyan SongSchool of Optometry, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
Qihua XuSchool of Optometry, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Proliferative vitreoretinopathy (PVR) is a blinding retinal condition often linked to retinal detachment, eye trauma, and complications following intraocular surgery. Although oxidative stress and epithelial-mesenchymal transition (EMT) are well-recognized contributors to PVR pathogenesis, whether ferroptosis-related pathways are involved in this process remains unclear. Methods: Differentially expressed genes (DEGs) were identified from the GSE28133 dataset and intersected with ferroptosis-related genes curated from FerrDb to obtain ferroptosis-related differentially expressed genes (FRDGs). Functional enrichment analyses, protein-protein interaction network construction, and machine learning approaches (LASSO regression and SVM-RFE) were applied to identify key candidate genes. Immune infiltration was analyzed using CIBERSORT. Experimental validation was performed using an Results: Functional enrichment analyses indicated that FRDGs were mainly involved in wound healing, tissue remodeling, oxidative stress responses, and ferroptosis-related pathways. TIMP1 and STAT3 were identified as ferroptosis-associated candidate genes with strong discriminative ability between PVR and control samples in the discovery dataset. Immune infiltration analysis revealed distinct immune cell profiles in PVR samples and significant correlations between TIMP1 and STAT3 expression and multiple immune cell subsets. Experimental validation confirmed upregulation of TIMP1 and STAT3 in the EMT model. In addition, Western blot analysis demonstrated significantly increased GPX4 protein expression in retinal tissues from the rabbit PVR model compared with controls. Conclusion: This study identifies TIMP1 and STAT3 as ferroptosis-associated candidate genes in proliferative vitreoretinopathy and highlights potential links among ferroptosis-related regulatory pathways, immune microenvironment alterations, and PVR pathogenesis. These findings provide a foundation for further mechanistic studies to clarify the role of ferroptosis in PVR.

Indexed as

bioinformaticsbiomarkersferroptosisimmune infiltrationmachine learningproliferative vitreoretinopathy

Identifiers

PMID41743358
PMCPMC12930359

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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.