ABSTRACT: Addressing tumor heterogeneity in breast cancer research is crucial, given the distinct subtypes like triple-negative, luminal A/B, and HER2, requiring precise differentiation for effective treatment. This study introduces a non-invasive method by analyzing post-translationally modified proteins in plasma extracellular vesicles (EVs), which play a role in immune regulation and intercellular communication. Examining modifications like phosphorylation, acetylation, and glycosylation in EVs provides insights into breast cancer dynamics. One hundred one plasma samples from luminal A/B, triple-negative breast cancer, and healthy individuals underwent discovery and validation experiments. The study identified over 28,000 unique non-modified peptides, 5,000 phosphopeptides, 680 acetyl peptides, and 1,300 glycopeptides that were successfully characterized. Bioinformatics analyses revealed significant overexpression of 815 non-modified proteins, 3,958 phosphopeptides, 352 acetyl peptides, and 895 glycopeptides in luminal A/B or triple-negative breast cancer subtypes. Phosphorylated and glycosylated PD-L1 peptides emerged as potential markers for breast cancer, regardless of subtype. Aligning findings with literature and PAM50 gene signatures highlighted markers correlated with lower survival rates. The study also conducted 123 scheduled parallel reaction monitoring (PRM) analyses, leveraging machine learning to pinpoint a panel of specific modification sites with high accuracy in subtype differentiation. This research reveals diagnostic markers and enhances understanding of the molecular landscape, contributing to more effective and personalized breast cancer diagnostics and treatments.
