Gene expression analysis in endometriosis: Immunopathology insights, transcription factors and therapeutic targets - Geng, Rong; Huang, Xiaobin; Li, Linxi; Guo, Xin; Wang, Qingru; Zheng, Yuhua; Guo, Xiaoling (Frontiers in Immunology, 2022)
Endometriosis is recognized as an estrogen-dependent inflammation disorder, estimated to affect about 8-15% of women of childbearing age. Pelvic pain and infertility are the two major clinical symptoms. Currently, the etiology and pathogenesis of endometriosis are not clear. In our research, we made use of extensive bioinformatics approaches to explore the potential mechanism for endometriosis. Through GSVA and GSEA analysis, we found immune and metabolic pathways enriched in endometriosis. Compared with non-endometriosis, women with endometriosis suffer from immune disorders, whose immune infiltrating cells, immune response gene sets, and immune response pathways. Then, we screened twenty-seven transcription factors (TFs) from differentially expressed genes. Most of the twenty-seven TFs were also shown to correlate with immune abnormalities. By the Lasso model, we screened five TFs (KLF2 AEBP1, DLX6, HOXB6 and RORB). The prediction model of the ROC curve based on GSE7305 and GSE11691databases further identified four TFs (AEBP1, HOXB6, KLF2 and RORB) as the main objective. They had a high diagnostic value in endometriosis. In separate KEGG analysis of four transcription factors, four group enriched pathways were similar to specific endometriosis analysis, and lupus erythematosus (SLE) appeared multiple times. Then, four TFs created a connected module in the PPI network, and they were closely connected in the PPI network. We then employed WGCNA to redefine specific gene modules, and sixty-two genes were lastly reselected. Enrichment analyses (Go and KEGG) were performed using Metascape. Three new sets of modules were identified, and KLF2 and HOXB6 genes were again present in two of them, suggesting dominant contribution to endometriosis. Using the ceRNA network, we further sought to explore the regulatory relationship. We detected that NEAT1 and XIST might regulate the expression of four TFs through the lncRNA-miRNA-mRNA network. Finally, we determined whether those four TFs harbor meaningful therapeutic value. Based on the binding energy of the AEBP1, HOXB6, KLF2 and RORB, they all showed good affinity with goserelin and dienogest. Through our systematic evaluation, we provide a more comprehensive perspective on transcription factors and offer a basis for future studies in endometriosis.