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Ovarian cancer (OvCA) is the most lethal neoplasia among gynecologic malignancies and faces high rates of new cases particularly in South America. In special, the High Grade Serous Ovarian Carcinoma (HGSC) presents very poor prognosis with deaths caused mainly by metastasis. Among several mechanisms involved in metastasis, the Epithelial to Mesenchymal Transition (EMT) molecular reprogramming represents a model for latest stages of cancer progression. EMT promotes important cellular changes in cellular adhesion and cell-cell communication, which particularly depends on the paracrine signaling from neighbor cells. Considering the importance of cellular communication during EMT and metastasis, here we analyzed the changes in the secretome of the ovarian cancer cell line Caov-3 induced to EMT by Epidermal Growth Factor (EGF). Using a combination of GEL-LC-MS/MS and stable isotopic metabolic labelling (SILAC), we identified up-regulated candidates during EMT as a starting point to identify relevant proteins for HGSC. Based on public databases, our candidate proteins were validated and prioritized for further analysis. Importantly, several of the protein candidates were associated with cellular vesicles, which are important to the cell-cell communication and metastasis. Furthermore, the association of candidate proteins with gene expression data uncovered a subset of proteins correlated with the mesenchymal subtype of ovarian cancer. Based on this relevant molecular signature for aggressive ovarian cancer, supported by protein and gene expression data, we developed a targeted proteomic method to evaluate individual OvCA clinical samples. The quantitative information obtained for 33 peptides, representative of 18 proteins, was able to segregate HGSC from other tumor types. Our study highlighted the richness of the secretome and EMT to reveal relevant proteins for HGSC, which could be used in further studies and larger patient cohorts as a potential stratification signature for ovarian cancer tumor that could guide clinical conduct for patient treatment. Schematic experimental approach. Secretome of Caov-3 cells induced to EMT by EGF (10 ng/mL) for 96 h and respective control (not induced) were combined with the secretome of Caov-3 cells cultured in heavy SILAC medium and analyzed by LC-MS/MS. The mRNA expression levels of differentially quantified proteins were retrieved from the TCGA and only up-regulated proteins at maximum value on Mesenchymal subtype gene expression were select to be used in our final verification panel. The final MRM method covering 18 proteins was used to analyze selected tumor samples. Individual figures adapted from https://smart.servier.com/ [Display omitted] • We explored the model of inducing EMT in Caov-3 ovarian cancer cell lines using EGF. • Our quantitative proteomic approach identified proteins up-regulated in the secretome of Caov-3 cells during EMT. • Selected up-regulated proteins were mainly associated with mechanisms of vesicle-mediated transport. • Up-regulated proteins were prioritized based on gene expression signature of mesenchymal subtype of HGSC tumors. • Secretome-gene expression associated proteins were used to develop a targeted proteomics method to analyze clinical samples. • The final method was able to stratify high grade ovarian cancer patient tumor samples from other subtypes. [ABSTRACT FROM AUTHOR]