The NLRP3 activation-related signature predict the diagnosis and indicate immune characteristics in endometriosis

Abstract

Abstract Endometriosis (EMS) is a common gynecological disease leading to chronic pelvic pain and infertility in women of reproductive age, but its underlying pathogenic genes and effective treatment are still unclear. To date, abnormal expression of NLRP3 activation-related genes has been identified in EMS patients and mouse models. Therefore, this study sought to identify the key genes that could affect the diagnosis and treatment of EMS. The GSE7307 dataset was downloaded from the Gene Expression Omnibus (GEO) database, including 18 EMS samples and 23 control samples. 14 differential genes related to NLRP3 activation and EMS were obtained from the endometrial samples of GSE7307 by differential analysis. GO and KEGG analysis showed that these genes were mainly involved in the production and regulation of the cytokine IL-1β, and the NOD-like receptor signaling pathway. Random Forest (RF) and support vector machine recursive feature elimination (SVM-RFE) algorithms were used to select four diagnostic markers related to NLRP3 activation (NLRP3, IL-1β, LY96 and PDIA3) to construct the EMS diagnostic model. The four diagnostic markers were verified using western blotting and validated in the GSE7305 and GSE23339 datasets. The AUC values showed that the model had a good diagnostic performance. In addition, the infiltration of immune cells in the samples and the correlation between different immune factors and diagnostic markers were further discussed. These results suggest that four diagnostic markers may also play an important role in the immunity of EMS. Finally, 10 drugs targeting to four diagnostic markers were retrieved from the DrugBank database, of which niclosamide proved useful for treating EMS. Overall, we identified four key diagnostic genes for EMS. In addition, large-scale and multicenter prospective cohort studies are necessary to confirm whether these four genes also have valid diagnostic value in blood samples from EMS patients.