Genomics · 2025
Unveiling the role of integrated stress response in pterygium: EGLN3, HSPA8, and NDRG1 as novel biomarkers and therapeutic targets.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Xiang Jun, Cheng Jingyi, Fan Yidan, Wu Jiawen, Lyu Zhaoyuan, Gu Jiayu, Xu Jianjiang, Lyu Ning
Аннотация
PURPOSE: Pterygium was a common progressive ocular disease with unclear pathogenesis. The aim of this study was to identify biomarkers associated with the integrated stress response (ISR) in pterygia and explore the underlying molecular mechanisms.
METHODS: Differentially expressed genes (DEGs) were identified using transcriptome sequencing. ISR-related genes (IRGs) and DEGs were integrated to identify candidate genes, and biomarkers were identified by machine learning. A nomogram was generated using these biomarkers. Enrichment analysis, immune infiltration analysis, correlation analysis, construction of transcription-factor (TF)-mRNA-miRNA regulatory networks, drug prediction, and molecular docking were performed to assess the functional mechanisms underlying these biomarkers.
RESULTS: EGLN3, HSPA8, and NDRG1 were identified as ISR-related biomarkers. EGLN3, HSPA8, and NDRG1 were associated with oxidative phosphorylation, cellular response to hypoxia, and decreased oxygen levels according to enrichment analysis. EGLN3 and NDRG1 were significantly and negatively correlated with immune cells, including immature B cells, but not HSPA8. ARNTL-EGLN3-hsa-miR-520a-3p, ARNTL-HSPA8-hsa-miR-520a-3p, and SNAPC4-NDRG1-hsa-miR-518a-5p played regulatory roles in pterygium development. Drug prediction and molecular docking analyses suggested Metribolone and Valproic Acid as potential therapeutic targets for pterygium. According to qRT-PCR, the expressions of EGLN3, HSPA8, and NDRG1 significantly differed between control and pterygium tissues.
CONCLUSIONS: EGLN3, HSPA8, and NDRG1 were identified as biomarkers associated with ISR in pterygium. The regulatory networks composed of differed expressions of ISR-related genes, miRNA-mRNA-TF regulatory axes, and immune response played crucial roles in the development of pterygium.
METHODS: Differentially expressed genes (DEGs) were identified using transcriptome sequencing. ISR-related genes (IRGs) and DEGs were integrated to identify candidate genes, and biomarkers were identified by machine learning. A nomogram was generated using these biomarkers. Enrichment analysis, immune infiltration analysis, correlation analysis, construction of transcription-factor (TF)-mRNA-miRNA regulatory networks, drug prediction, and molecular docking were performed to assess the functional mechanisms underlying these biomarkers.
RESULTS: EGLN3, HSPA8, and NDRG1 were identified as ISR-related biomarkers. EGLN3, HSPA8, and NDRG1 were associated with oxidative phosphorylation, cellular response to hypoxia, and decreased oxygen levels according to enrichment analysis. EGLN3 and NDRG1 were significantly and negatively correlated with immune cells, including immature B cells, but not HSPA8. ARNTL-EGLN3-hsa-miR-520a-3p, ARNTL-HSPA8-hsa-miR-520a-3p, and SNAPC4-NDRG1-hsa-miR-518a-5p played regulatory roles in pterygium development. Drug prediction and molecular docking analyses suggested Metribolone and Valproic Acid as potential therapeutic targets for pterygium. According to qRT-PCR, the expressions of EGLN3, HSPA8, and NDRG1 significantly differed between control and pterygium tissues.
CONCLUSIONS: EGLN3, HSPA8, and NDRG1 were identified as biomarkers associated with ISR in pterygium. The regulatory networks composed of differed expressions of ISR-related genes, miRNA-mRNA-TF regulatory axes, and immune response played crucial roles in the development of pterygium.