Identification of a disulfidptosis-related genes signature for diagnostic and immune infiltration characteristics in endometriosis.

Endometriosis (EMs) is the prevalent gynecological disease with the typical features of intricate pathogenesis and immune-related factors. Currently, there is no effective therapeutic intervention for EMs. Disulfidptosis, the cell death pattern discovered recently, may show close relationships to immunity and EMs. In this study, bioinformatics analysis was used to investigate the role of disulfide breakdown related genes (DRGs) in EMs. The EMs gene expression matrix was subjected to differential analysis for identifying overlap between differentially expressed genes (DEGs) in EMs and genes associated with disulfide poisoning. Immunoinfiltration analysis was performed. In addition, the association of hub genes with immune cells was examined. Multiple machine learning methods were employed to identify hub genes, construction of predictive models, and validation using external datasets and clinical samples. Totally 15 overlapping genes were identified. Immune-correlation analysis showed that NK cells played a vital role, and these 15 genes were closely related to NK cells. PDLIM1 was further determined as the hub gene through machine learning techniques. Clinical samples and external datasets were adopted for validating the performance in diagnosis. According to the above findings, we built the predictive model, and calculated the AUCs obtained from three external validation datasets to demonstrate the model accuracy. RT-qPCR and IHC analyses were applied to confirm the results. Colony formation was used to verify the effect of PDLIM1 on the proliferation of primary EMs cells. A strong correlation between disulfidptosis and EMs was identified in this study, highlighting its close correlation with the immune microenvironment. Moreover, our results shed new lights on exploring biomarkers and potential therapeutic targets for EMs.