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<p>Endometriosis is a common gynecological disorder in which inflammatory and immune responses play a crucial role in its development and progression. This study aimed to identify potential inflammation-related biomarkers for the diagnosis and therapeutic monitoring of endometriosis. Differentially expressed genes (DEGs) between endometriosis and control groups were identified using the limma R package. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed with the clusterProfiler R package to explore functional categories and biological processes associated with the DEGs. Immune cell proportions were estimated using CIBERSORT and xCell, followed by correlation analysis between gene expression and immune cell ratios. Data were obtained from the GEO datasets GSE104948 and GSE116626. Under the criteria |fold-change (FC)| &gt; 1 and p-value &lt; 0.05, a total of 357 DEGs were identified, including 136 down-regulated and 221 up-regulated genes. GO analysis revealed enriched biological processes, such as regulation of cell-cell adhesion mediated by cadherin, cell-cell adhesion mediated by cadherin, and response to interleukin-6. Functional enrichment included extracellular matrix structural constituents and protein-binding activities. KEGG analysis highlighted pathways related to protein digestion and absorption. Three inflammation-related genes, PGI2 synthase (PTGIS), E26 transformation-specific homologous factor (EHF), and collagen type X alpha 1 (COL10A1), were identified as potential biomarkers for endometriosis. In 12Z endometriotic epithelial cells, PTGIS knockdown reduced viability, enhanced apoptosis, and impaired migration and invasion, whereas PTGIS overexpression had the opposite effects. Collectively, this study suggests that PTGIS, EHF, and COL10A1 may serve as valuable predictors for the progression of endometriosis.</p>

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Identifying Predictive Biomarkers and Immune Infiltration Features in Endometriosis

  • 期刊论文

  • 发表日期：

    2026年3月23日

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  • Xiaoli Chen,
  • Lianqin Cheng,
  • Mei Cheng,
  • Boyao Xia,
  • Si Gao,
  • Xueyao Peng,
  • Huimin Zhang,
  • Lijun Ye

摘要

Endometriosis is a common gynecological disorder in which inflammatory and immune responses play a crucial role in its development and progression. This study aimed to identify potential inflammation-related biomarkers for the diagnosis and therapeutic monitoring of endometriosis. Differentially expressed genes (DEGs) between endometriosis and control groups were identified using the limma R package. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed with the clusterProfiler R package to explore functional categories and biological processes associated with the DEGs. Immune cell proportions were estimated using CIBERSORT and xCell, followed by correlation analysis between gene expression and immune cell ratios. Data were obtained from the GEO datasets GSE104948 and GSE116626. Under the criteria |fold-change (FC)| > 1 and p-value < 0.05, a total of 357 DEGs were identified, including 136 down-regulated and 221 up-regulated genes. GO analysis revealed enriched biological processes, such as regulation of cell-cell adhesion mediated by cadherin, cell-cell adhesion mediated by cadherin, and response to interleukin-6. Functional enrichment included extracellular matrix structural constituents and protein-binding activities. KEGG analysis highlighted pathways related to protein digestion and absorption. Three inflammation-related genes, PGI2 synthase (PTGIS), E26 transformation-specific homologous factor (EHF), and collagen type X alpha 1 (COL10A1), were identified as potential biomarkers for endometriosis. In 12Z endometriotic epithelial cells, PTGIS knockdown reduced viability, enhanced apoptosis, and impaired migration and invasion, whereas PTGIS overexpression had the opposite effects. Collectively, this study suggests that PTGIS, EHF, and COL10A1 may serve as valuable predictors for the progression of endometriosis.