Identification and Validation of Potential Immune-Related Genes for Endometriosis.

OBJECTIVE

This study aimed to identify and validate potential immune-related genes in endometriosis (Ems) through comprehensive bioinformatics analysis and immunohistochemistry (IHC) verification.

DESIGN

Using data from the GEO database, single-cell RNA sequencing (scRNA) data and traditional bulk RNA sequencing data were analyzed to identify differentially expressed genes related to the immune system. Immunological analysis confirmed alterations in immune cells associated with Ems. Machine learning techniques were employed to identify characteristic immune genes of eutopic and ectopic endometria, which were then validated through IHC experiments.

MAIN OUTCOME MEASURES: Immunological analysis revealed distinct variations in the enrichment of macrophages and NK cells in Ems. Functional enrichment analysis revealed a decrease in NK cell toxicity in both ectopic and eutopic endometria, activation of M2 macrophages in the ectopic endometrium supporting the survival of ectopic endothelial cells, and the presence of lipid antigens and signaling between immune cells facilitating the development of Ems. Machine learning algorithms revealed that TGFBR1 is a characteristic immune gene associated with the eutopic endometrium and that GIMAP4 is associated with the ectopic endometrium; this conclusion was also confirmed by IHC.

RESULTS

Macrophage and NK cell enrichment was significantly increased in endometria from patients with Ems. TGFBR1 is a characteristic immune gene associated with the eutopic endometrium, whereas GIMAP4 is associated with the ectopic endometrium.

CONCLUSION

These findings provide new insights for the clinical diagnosis and selection of immune-related targets for Ems.