Background: The epithelial-mesenchymal transition (EMT) promotes cell signaling and morphology alterations, contributing to cancer progression. Exosomes, extracellular vesicles containing proteins involved in cell-cell communication, have emerged as a potential source of biomarkers for several diseases.
Methods: Our aim was to assess the proteome content of exosomes secreted after EMT-induction to identify potential biomarkers for ovarian cancer classification. EMT was induced in the ovarian cancer cell line CAOV3 by treating it with EGF (10 ng/mL) for 96 h following 24 h of serum deprivation. Subsequently, exosomes were isolated from the supernatant using selective centrifugation after decellularization, and their characteristics were determined. The proteins present in the exosomes were extracted, identified, and quantified using Label-Free-Quantification (LFQ) via Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS). To identify potential biomarkers, the obtained proteomic data was integrated with the TGGA database for mRNA expression using principal component analysis and a conditional inference tree.
Results: The exosomes derived from CAOV3 cells exhibited similar diameter and morphology, measuring approximately 150 nm, regardless of whether they were subjected to EMT stimulation or not. The proteomic analysis of proteins from CAOV3-derived exosomes revealed significant differential regulation of 157 proteins, with 100 showing upregulation and 57 downregulation upon EMT induction. Further comparison of the upregulated proteins with the TCGA transcriptomic data identified PLAU, LAMB1, COL6A1, and TGFB1 as potential biomarkers of the mesenchymal HGSOC subtype.
Conclusions: The induction of EMT, the isolation of exosomes, and the subsequent proteomic analysis highlight potential biomarkers for an aggressive ovarian cancer subtype. Further investigation into the role of these proteins is warranted to enhance our understanding of ovarian cancer outcomes.
Keywords: Epithelial-mesenchymal transition; Exosomes; Extracellular vesicles; Ovarian cancer; Secretome.
© 2023. The Author(s).