Zhang Li-Wei, Yang Ji, Jiang Hua-Wei, Yang Xiu-Qiang, Chen Ya-Nan, Ying Wei-Dang, Deng Ying-Liang, Zhang Min-Hui, Liu Hai, Zhang Hong-Lei
Department of Ophthalmology, The Affiliated Hospital of Yunnan University, Second People's Hospital of Yunnan Province, The Eye Hospital of Yunnan Province, The Eye Disease Clinical Medical Research Center of Yunnan Province, The Eye Disease Clinical Medical Center of Yunnan Province, Kunming, China.
Department of Ophthalmology, Wuhan Children's Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Front Mol Biosci. 2024 Dec 11;11:1524517. doi: 10.3389/fmolb.2024.1524517. eCollection 2024.
Pterygium is a complex ocular surface disease characterized by the abnormal proliferation and growth of conjunctival and fibrovascular tissues at the corneal-scleral margin. Understanding the underlying molecular mechanisms of pterygium is crucial for developing effective diagnostic and therapeutic strategies.
To elucidate the molecular mechanisms of pterygium, we conducted a differential gene expression analysis between pterygium and normal conjunctival tissues using high-throughput RNA sequencing. We identified differentially expressed genes (DEGs) with statistical significance (adjust < 0.05, |logFC| > 1). Enrichment analyses were performed to assess the biological processes and signaling pathways associated with these DEGs. Additionally, we utilized weighted correlation network analysis (WGCNA) to select module genes and applied Random Forest (RF) and Support Vector Machine (SVM) algorithms to identify pivotal feature genes influencing pterygium progression. The diagnostic potential of these genes was validated using external datasets (GSE2513 and GSE51995). Immune cell infiltration analysis was conducted using CIBERSORT to compare immune cell populations between pterygium and normal conjunctival tissues. Quantitative PCR (qPCR) was used to confirm the expression levels of the identified feature genes. Furthermore, we identified key miRNAs and candidate drugs targeting these feature genes.
A total of 718 DEGs were identified in pterygium tissues compared to normal conjunctival tissues, with 254 genes showing upregulated expression and 464 genes exhibiting downregulated expression. Enrichment analyses revealed that these DEGs were significantly associated with inflammatory processes and key signaling pathways, notably leukocyte migration and IL-17 signaling. Using WGCNA, RF, and SVM, we identified KRT10 and NGEF as pivotal feature genes influencing pterygium progression. The diagnostic potential of these genes was validated using external datasets. Immune cell infiltration analysis demonstrated significant differences in immune cell populations between pterygium and normal conjunctival tissues, with an increased presence of M1 macrophages and resting dendritic cells in pterygium samples. qPCR analysis confirmed the elevated expression of KRT10 and NGEF in pterygium tissues.
Our findings emphasize the importance of gene expression profiling in unraveling the pathogenesis of pterygium. The identification of pivotal feature gene KRT10 and NGEF provide valuable insights into the molecular mechanisms underlying pterygium progression.
翼状胬肉是一种复杂的眼表疾病，其特征是角膜巩膜缘处结膜和纤维血管组织异常增殖和生长。了解翼状胬肉的潜在分子机制对于制定有效的诊断和治疗策略至关重要。
为阐明翼状胬肉的分子机制，我们使用高通量RNA测序对翼状胬肉组织和正常结膜组织进行了差异基因表达分析。我们鉴定出具有统计学意义的差异表达基因（DEGs）（调整后P<0.05，|logFC|>1）。进行富集分析以评估与这些DEGs相关的生物学过程和信号通路。此外，我们利用加权基因共表达网络分析（WGCNA）选择模块基因，并应用随机森林（RF）和支持向量机（SVM）算法来识别影响翼状胬肉进展的关键特征基因。使用外部数据集（GSE2513和GSE51995）验证了这些基因的诊断潜力。使用CIBERSORT进行免疫细胞浸润分析，以比较翼状胬肉组织和正常结膜组织中的免疫细胞群体。定量PCR（qPCR）用于确认所鉴定特征基因的表达水平。此外，我们鉴定了靶向这些特征基因的关键miRNA和候选药物。
与正常结膜组织相比，在翼状胬肉组织中总共鉴定出718个DEGs，其中254个基因表达上调，464个基因表达下调。富集分析表明，这些DEGs与炎症过程和关键信号通路显著相关，特别是白细胞迁移和IL-17信号通路。使用WGCNA、RF和SVM，我们鉴定出KRT10和NGEF是影响翼状胬肉进展的关键特征基因。使用外部数据集验证了这些基因的诊断潜力。免疫细胞浸润分析表明，翼状胬肉组织和正常结膜组织中的免疫细胞群体存在显著差异，翼状胬肉样本中M1巨噬细胞和静息树突状细胞的存在增加。qPCR分析证实了翼状胬肉组织中KRT10和NGEF的表达升高。
我们的研究结果强调了基因表达谱在揭示翼状胬肉发病机制中的重要性。关键特征基因KRT10和NGEF的鉴定为翼状胬肉进展的分子机制提供了有价值的见解。
