Abstract
Background/Objectives: Endometrial cancer (EC) is the second most frequent gynecological malignant tumor in postmenopausal women. Pathogenic mechanisms related to the onset and development of the disease are still unknown. To identify dysregulated proteins associated with EC we exploited a combined in vitro/in silico approach analyzing the proteome of exosomes with advanced MS techniques and annotating their results by using Chymeris1 AI tools. Methods: To this aim in this pilot study, we performed a deep proteomics analysis with high resolution MS (HRMS), advanced computational tools and western blotting for proteomics data validation. Results: That allowed us to identify 3628 proteins in serum albumin-depleted exosomes from 10 patients with EC compared to 10 healthy controls. This is the largest number of proteins identified in EC serum EVs. After quantification and statistical analysis, we identified 373 significantly (p < 0.05) dysregulated proteins involved in neutrophil and platelet degranulation pathways. A more detailed bioinformatics analysis revealed 61 dysregulated enzymes related to metabolic and catabolic pathways linked to tumor invasion. Through this analysis, we identified 49 metabolic and catabolic pathways related to tumor growth. Conclusions: Altogether, data shed light on the metabolic pathways involved in tumors. This is very important for understanding the metabolism of EC and for the development of new therapies.