Differential Protein Expression of mild to severe forms of Endometriosis in South Indian Ethnic patients

Introduction: Endometriosis is a prevalent, benign, estrogen-dependent, chronic gynecological disorder associated with pelvic pain and infertility. Despite its prevalence and impact on reproductive health, the underlying molecular mechanisms and differential protein expression patterns associated with different disease severity levels remain poorly understood. Key components such as extracellular matrix (ECM) components (laminins, fibronectins), adhesion molecules, cytokines, and growth factors have been shown to contribute to the pathogenesis of Endometriosis. However, the precise nature of these molecular networks and Signalling pathways remain incompletely understood, necessitating further investigation. In our study, we employed proteome profiling techniques to analyze endometrial tissue samples from women with severe forms of endometriosis, comparing them with samples from normal controls. Objective: It is to identify alterations and dysregulations in specific proteins and pathways associated with endometriosis. We utilized high-resolution two-dimensional gel electrophoresis (2-DE) and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) for protein expression analysis and identification during the mid-secretory phase. Findings: We identified thirty differentially expressed proteins, including ZC3H13, Tax1bp1, ANKRD36, ZNF658B, MALRD1, and PRRC2A. Notably, a strong association was observed among genes encoding three metabolic enzymes. Enrichment analysis revealed numerous pathways related to endometriosis-related morbidity in KEGG, WiKi, and Reactome databases, underscoring the significant role of these proteins. Conclusion: This study employed proteome profiling techniques to analyze endometrial tissue samples from women with severe forms of endometriosis, comparing them with samples from normal controls. The research identified thirty differentially expressed proteins, including ZC3H13, Tax1bp1, ANKRD36, ZNF658B, MALRD1, and PRRC2A. Notably, a strong association was observed among genes encoding three metabolic enzymes. Enrichment analysis revealed numerous pathways related to endometriosis-related morbidity, emphasizing the significant role of these proteins. This research enables the development of accurate diagnostic tools and personalized treatments by identifying specific proteins and pathways associated with endometriosis. The identified proteins also have the potential to serve as biomarkers for disease progression, aiding in monitoring and assessing treatment efficacy.