Abstract
BACKGROUND: Endometriosis (EM) is a disease related to reproductive dysfunction. The mechanism of epigenetic factors (EF) in EM still needs to be studied. Emerging evidence suggests that EF plays a role in the development of EM. However, the specific molecular pathways through which they exert their effects remain incompletely understood, necessitating further in-depth research. This study aimed to explore the mechanisms underlying EF in EM. METHODS: In the study, the differentially expressed genes (DEGs) between EM and control were obtained by analyzing transcriptome data from public databases. Candidate genes were obtained by taking the intersection of DEGs and EF-related genes (EF-RGs), which were further screened using machine learning algorithms, receiver operating characteristic analysis, and expression levels in the EM and control samples to obtain biomarkers. The potential mechanisms of biomarkers in EF were further analyzed by constructing a nomogram model, gene set enrichment analysis (GSEA), immune infiltration analysis, expression profiling in tissues and cells, molecular regulatory networks, and drug prediction. The expression of these biomarkers was validated using in vitro experiments. RESULTS: Histone deacetylase 9 (HDAC9), YY1-associated factor 2 (YAF2), and cell division cycle 6 (CDC6) were identified as EF-associated biomarkers in EM. These biomarkers had excellent diagnostic ability for EM. HDAC9, CDC6, and YAF2 were respectively significantly enriched in focal adhesion and oxidative phosphorylation pathways. Four types of differentially distributed immune cells were identified between EM and control samples using immune infiltration analysis. The expression of these biomarkers in different tissues varied with age and menstrual cycle. The expression levels of biomarkers were higher in endothelial cells. Ten miRNAs and 24 lncRNAs that targeted these biomarkers were screened, and there were 12 transcription factors (TFs) in which all the biomarkers acted together. All biomarkers worked together for drugs, including bisphenol A, benzo(a)pyrene, and cisplatin. The results of in vitro experiments were consistent with those of the bioinformatics analysis. CONCLUSION: This study identified three biomarkers (HDAC9, CDC6, and YAF2) and the potential therapeutic drugs for EM. These results provide new insights into the mechanisms underlying EM development.