Investigating immune cell infiltration and gene expression features in pterygium pathogenesis

被引:0
|
作者
Ji Yang [1 ]
Ya-Nan Chen [1 ]
Chen-Yan Fang [1 ]
Yan Li [1 ]
Hong-Qin Ke [1 ]
Rui-Qin Guo [1 ]
Ping Xiang [2 ]
Yun-Ling Xiao [3 ]
Li-Wei Zhang [1 ]
Hai Liu [1 ]
机构
[1] Department of Ophthalmology, The Eye Disease Clinical Medical Research Center of Yunnan Province, Second People’s Hospital of Yunnan Province, The Affiliated Hospital of Yunnan University, The Eye Disease Clinical Medical Center of Yunnan Province, Kunming
[2] Yunnan 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
[3] Honghe County People’s Hospital, Honghe
基金
中国国家自然科学基金;
关键词
Biomarkers; Gene expression; Immune cell infiltration; Machine learning; Pterygium;
D O I
10.1038/s41598-025-98042-8
中图分类号
学科分类号
摘要
Pterygium is a prevalent ocular disease characterized by abnormal conjunctival tissue proliferation, significantly impacting patients’ quality of life. However, the underlying molecular mechanisms driving pterygium pathogenesis remain inadequately understood. This study aimed to investigate gene expression changes following pterygium excision and their association with immune cell infiltration. Clinical samples of pterygium and adjacent relaxed conjunctival tissue were collected for transcriptomic analysis using RNA sequencing combined with bioinformatics approaches. Machine learning algorithms, including LASSO, SVM-RFE, and Random Forest, were employed to identify potential diagnostic biomarkers. GO, KEGG, GSEA, and GSVA were utilized for enrichment analysis. Single-sample GSEA was employed to analyze immune infiltration. The GSE2513 and GSE51995 datasets from the GEO database, along with clinical samples, were selected for validation analysis. Differentially expressed genes (DEGs) were identified from the PRJNA1147595 and GSE2513 datasets, revealing 2437 DEGs and 172 differentially regulated genes (DRGs), respectively. There were 52 co-DEGs shared by both datasets, and four candidate biomarkers (FN1, SPRR1B, SERPINB13, EGR2) with potential diagnostic value were identified through machine learning algorithms. Single-sample GSEA demonstrated increased Th2 cell infiltration and decreased CD8 + T cell presence in pterygium tissues, suggesting a crucial role of the immune microenvironment in pterygium pathogenesis. Analysis of the GSE51995 dataset and qPCR results revealed significantly higher expression levels of FN1 and SPRR1B in pterygium tissues compared to conjunctival tissues, but SERPINB13 and EGR2 expression levels were not statistically significant. Furthermore, we identified four candidate drugs targeting the two feature genes FN1 and SPRR1B. This study provides valuable insights into the molecular characteristics and immune microenvironment of pterygium. The identification of potential biomarkers FN1 and SPRR1B highlights their significance in pterygium pathogenesis and lays a foundation for further exploration aimed at integrating these findings into clinical practice. © The Author(s) 2025.
引用
收藏
相关论文
共 50 条
  • [1] Immune infiltration in nasopharyngeal carcinoma based on gene expression
    Luo, Meng-Si
    Huang, Guan-Jiang
    Liu, Bao-Xinzi
    MEDICINE, 2019, 98 (39)
  • [2] Profiles of Immune Cell Infiltration in Carotid Artery Atherosclerosis Based on Gene Expression Data
    Wang, Long
    Gao, Beibei
    Wu, Mingyue
    Yuan, Wei
    Liang, Ping
    Huang, Jinyu
    FRONTIERS IN IMMUNOLOGY, 2021, 12
  • [3] Identification of Transcriptional Pattern Related to Immune Cell Infiltration With Gene Co-Expression Network in Papillary Thyroid Cancer
    Li, Meiye
    Zhang, Jimei
    Zhang, Zongjing
    Qian, Ying
    Qu, Wei
    Jiang, Zhaoshun
    Zhao, Baochang
    FRONTIERS IN ENDOCRINOLOGY, 2022, 13
  • [4] Exploration of the immune cell infiltration-related gene signature in the prognosis of melanoma
    Zeng, Yangyang
    Zeng, Yulan
    Yin, Hang
    Chen, Fengxia
    Wang, Qingqing
    Yu, Xiaoyan
    Zhou, Yunfeng
    AGING-US, 2021, 13 (03): : 3459 - 3482
  • [5] Integrated investigation of DNA methylation, gene expression and immune cell population revealed immune cell infiltration associated with atherosclerotic plaque formation
    Yihong Yin
    Zhaohong Xie
    Dong Chen
    Hao Guo
    Min Han
    Zhengyu Zhu
    Jianzhong Bi
    BMC Medical Genomics, 15
  • [6] Integrated investigation of DNA methylation, gene expression and immune cell population revealed immune cell infiltration associated with atherosclerotic plaque formation
    Yin, Yihong
    Xie, Zhaohong
    Chen, Dong
    Guo, Hao
    Han, Min
    Zhu, Zhengyu
    Bi, Jianzhong
    BMC MEDICAL GENOMICS, 2022, 15 (01)
  • [7] Comprehensive integration of diagnostic biomarker analysis and immune cell infiltration features in sepsis via machine learning and bioinformatics techniques
    Yang, Liuqing
    Xuan, Rui
    Xu, Dawei
    Sang, Aming
    Zhang, Jing
    Zhang, Yanfang
    Ye, Xujun
    Li, Xinyi
    FRONTIERS IN IMMUNOLOGY, 2025, 16
  • [8] Aberrant expression of genes and proteins in pterygium and their implications in the pathogenesis
    Qing-Yang Feng
    Zi-Xuan Hu
    Xi-Ling Song
    Hong-Wei Pan
    International Journal of Ophthalmology, 2017, 10 (06) : 973 - 981
  • [9] Aberrant expression of genes and proteins in pterygium and their implications in the pathogenesis
    Feng, Qing-Yang
    Hu, Zi-Xuan
    Song, Xi-Ling
    Pan, Hong-Wei
    INTERNATIONAL JOURNAL OF OPHTHALMOLOGY, 2017, 10 (06) : 973 - 981
  • [10] Viral involvement in the pathogenesis and clinical features of ophthalmic pterygium (Review)
    Chalkia, Aikaterini K.
    Spandidos, Demetrios A.
    Detorakis, Efstathios T.
    INTERNATIONAL JOURNAL OF MOLECULAR MEDICINE, 2013, 32 (03) : 539 - 543