Blood plasma derived extracellular vesicles (BEVs): particle purification liquid chromatography (PPLC) and proteomic analysis reveals BEVs as a potential minimally invasive tool for predicting response to breast cancer treatment

BREAST CANCER RESEARCH AND TREATMENT(2022)

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摘要
Purpose Circulating blood plasma derived extracellular vesicles (BEVs) containing proteins hold promise for their use as minimally invasive biomarkers for predicting response to cancer therapy. The main goal of this study was to establish the efficiency and utility of the particle purification liquid chromatography (PPLC) BEV isolation method and evaluate the role of BEVs in predicting breast cancer (BC) patient response to neoadjuvant chemotherapy (NAC). Methods PPLC isolation was used to separate BEVs from non-EV contaminants and characterize BEVs from 17 BC patients scheduled to receive NAC. Using LC–MS/MS, we compared the proteome of PPLC-isolated BEVs from patients ( n = 7) that achieved a pathological complete response (pCR) after NAC (responders [R]) to patients ( n = 10) who did not achieve pCR (non-responders [NR]). Luminal MCF7 and basaloid MDA-MB-231 BC cells were treated with isolated BEVs and evaluated for metabolic activity by MTT assay. Results NR had elevated BEV concentrations and negative zeta potential (ζ-potential) prior to receipt of NAC. Eight proteins were enriched in BEVs of NR. GP1BA (CD42b), PECAM-1 (CD31), CAPN1, HSPB1 (HSP27), and ANXA5 were validated using western blot. MTT assay revealed BEVs from R and NR patients increased metabolic activity of MCF7 and MDA-MB-231 BC cells and the magnitude was highest in MCF7s treated with NR BEVs. Conclusion PPLC-based EV isolation provides a preanalytical separation process for BEVs devoid of most contaminants. Our findings suggest that PPLC-isolated BEVs and the five associated proteins may be established as predictors of chemoresistance, and thus serve to identify NR to spare them the toxic effects of NAC.
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关键词
BEVs, PPLC, Breast cancer, Neoadjuvant chemotherapy, Chemoresistance, Biomarkers
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