Evidence map›Paper›PMID 42143165›Full record

ArticleScientific reports2026

Exploring dysregulation of cuproptosis-related genes molecular clusters and candidate biomarkers in pterygium.

Ji Yang, Bo-Yu Liang, Chen-Yan Fang, Jia-Jie Li, Peng Zhang, Ping Xiang, Li-Wei Zhang, Hai Liu

Abstract read
In one paragraph

Article in Scientific reports, 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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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Ji Yang *Department of Ophthalmology, The Eye Disease Clinical Medical Research Center of Yunnan Province, Second People's Hospital of Yunnan, The Affiliated Hospital of Yunnan University, The Eye Disease Clinical Medical Center of Yunnan Province, Province, Kunming, China.
Bo-Yu Liang *Department of Ophthalmology, The Eye Disease Clinical Medical Research Center of Yunnan Province, Second People's Hospital of Yunnan, The Affiliated Hospital of Yunnan University, The Eye Disease Clinical Medical Center of Yunnan Province, Province, Kunming, China.
Chen-Yan Fang *Department of Ophthalmology, The Eye Disease Clinical Medical Research Center of Yunnan Province, Second People's Hospital of Yunnan, The Affiliated Hospital of Yunnan University, The Eye Disease Clinical Medical Center of Yunnan Province, Province, Kunming, China.
Jia-Jie LiDepartment of Ophthalmology, The Eye Disease Clinical Medical Research Center of Yunnan Province, Second People's Hospital of Yunnan, The Affiliated Hospital of Yunnan University, The Eye Disease Clinical Medical Center of Yunnan Province, Province, Kunming, China.
Peng ZhangDepartment of Ophthalmology, The Eye Disease Clinical Medical Research Center of Yunnan Province, Second People's Hospital of Yunnan, The Affiliated Hospital of Yunnan University, The Eye Disease Clinical Medical Center of Yunnan Province, Province, Kunming, China.
Ping XiangYunnan Province Innovative Research Team of Environmental Pollution, Food Safety, and Human Health, Institute of Environmental Remediation and Human Health, School of Ecology and Environment, Southwest Forestry University, Kunming, China.
Li-Wei ZhangDepartment of Ophthalmology, The Eye Disease Clinical Medical Research Center of Yunnan Province, Second People's Hospital of Yunnan, The Affiliated Hospital of Yunnan University, The Eye Disease Clinical Medical Center of Yunnan Province, Province, Kunming, China. drzhangliwei@163.com.
Hai LiuDepartment of Ophthalmology, The Eye Disease Clinical Medical Research Center of Yunnan Province, Second People's Hospital of Yunnan, The Affiliated Hospital of Yunnan University, The Eye Disease Clinical Medical Center of Yunnan Province, Province, Kunming, China. herryhai@ynu.edu.cn.

Funding

China Scholarship Council 202208535051Key Project of the Provincial Clinical Center of Yunnan Province 2024YNLCYXZX0343National clinical key specialty ophthalmology open foundation ZKF2024041National clinical key specialty ophthalmology open foundation ZKF2024042National Natural Science Foundation of China 82460201National Natural Science Foundation of China 82560205Tianjin Natural Science Foundation 24JCQNJC02050Yunnan University Medical Research Foundation YDYXJJ2024-0003
6 · The paper itself

Abstract

Pterygium is a common ocular surface disorder, with its prevalence strongly correlated to ultraviolet (UV) exposure in geographic regions. Epidemiological investigations reveal significant demographic variations, with higher incidences observed in areas with intense UV radiation and within specific populations, notably rural individuals. Despite surgical interventions being the standard treatment, recurrent cases underline the necessity for understanding the underlying biological mechanisms contributing to pterygium pathogenesis. Recent advancements in cellular death mechanisms point to cuproptosis, a copper-dependent programmed cell death pathway, as a potential regulatory factor in ocular diseases, including pterygium. This study aims to systematically investigate the immunological significance of cuproptosis-related genes (CuRGs) in pterygium's pathogenesis using an integrative bioinformatics framework. We performed transcriptomic profiling on pterygium tissues and employed machine learning algorithms to identify pivotal biomarkers for pterygium risk stratification. Comprehensive immune profiling and functional enrichment analyses were conducted to elucidate the interplay between identified CuRGs and the immune microenvironment in pterygium. Our analysis highlighted 19 CuRGs, with eight genes displaying significant dysregulation in pterygium tissues (p < 0.05). We established robust associations between CuRG expression and prominent immune cell infiltrates, notably regulatory T cells and macrophages. Furthermore, three core biomarkers (SERTAD1, JMJD1C, CSRNP1) were identified through machine learning and validated by QPCR, with the support vector machine model demonstrating exceptional predictive performance (AUC = 0.84). Empirical validation corroborated significant downregulation of selected biomarkers in pterygium tissue samples compared to normal conjunctiva. Our findings underscore the vital role of CuRGs in modulating pterygium development through immune and metabolic interactions, establishing their potential as novel therapeutic targets. Nevertheless, our study has limitations, as these findings are hypothesis-generating and require validation in larger patient cohorts.

Indexed as

CuproptosisPterygiumBiomarkersComputational BiologyFemaleGene Expression ProfilingGene Expression RegulationHumansMachine LearningMaleTranscriptomeBiomarkersCuproptosis-related genesImmune characteristicMachine learningPrediction modelPterygium

Identifiers

PMID42143165
PMCPMC13373229

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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.