bioRxivBiochemistryPreprint
Membrane Sensing Peptides -Enhanced SiMoA Platform for the Detection of HER2 on Extracellular Vesicles in Metastatic Breast Cancer Patients
Arianna BonizziiD, Paola GagniiD, Francesca PiccottiiD, Marta TruffiiD, Sara AlbasiniiD, Serena MazzucchelliiD, Lorena SignatiiD, Tiziana TriulziiD, Elda TagliabueiD, Alessandro GoriiD, Giorgia EspositoiD, Francesca GorgoglioneiD, Ilaria TaglioliniiD, Fabio CorsiiD, Carlo MorassoiD
Abstract
Extracellular vesicles (EVs) offer a promising avenue for non-invasive, real-time monitoring of metastatic breast cancer (mBC), but clinical application as a liquid biopsy is hindered by their heterogeneity and low abundance. Here we present a Single Molecule Array (SiMoA) platform enhanced by membrane sensing peptides (MSP) for the highly sensitive detection of HER2 on EV membranes (EVs-HER2) and general EVs population (CD9+) directly from plasma samples of mBC patients. The MSP-based SiMoA assay demonstrated superior sensitivity and specificity compared to conventional antibody-based assays, allowing the detection of lower amounts of EVs and discriminating EVs derived from breast cancer patient-derived organoids (BC-PDO) from healthy control-derived organoids (HC-PDO). Concerning the analysis of EVs in plasma samples (n=49 mBC patients, n=30 healthy controls), we observed significantly lower CD9+ EVs levels in mBC patients relative to healthy controls, a trend consistently confirmed across assays. Notably, EVs-HER2 levels were significantly enriched in HER2-positive patients and correlated with clinical HER2 status assessed by immunohistochemistry. Besides, lower CD9+ EVs levels were associated with poorer clinical outcomes, highlighting the potential prognostic utility of EV quantification. Our findings underscore the potential of MSP-enhanced SiMoA platforms for accurate, minimally invasive monitoring of EVs-HER2 in mBC and for monitoring CD9+ EVs levels to assess disease progression.
- organism: human
- assay: proteomics
- research focus: cell type annotation
- research focus: differential expression
- research focus: protein structure prediction
- approach: experimental assay
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