Extracellular vesicles as a promising source of lipid biomarkers for breast cancer detection in blood plasma

Author:

Dorado Erika1ORCID,Doria Maria Luisa1,Nagelkerke Anika2ORCID,McKenzie James S.1ORCID,Maneta‐Stavrakaki Stefania1ORCID,Whittaker Thomas E.2ORCID,Nicholson Jeremy K.3ORCID,Coombes Raoul Charles4ORCID,Stevens Molly M.2ORCID,Takats Zoltan156ORCID

Affiliation:

1. Faculty of Medicine, Department of Metabolism, Digestion and Reproduction Imperial College London London United Kingdom

2. Faculty of Engineering, Department of Bioengineering, Department of Materials, Institute of Biomedical Engineering Imperial College London London United Kingdom

3. Institute of Global Health Innovation Imperial College London London United Kingdom

4. Faculty of Medicine, Department of Surgery and Cancer Imperial College London London United Kingdom

5. PRISM Inserm U1192 University of Lille Lille France

6. Deparment of Immunomedicine University of Regensburg Regensburg Germany

Abstract

AbstractExtracellular vesicles (EVs), including exosomes and microvesicles, mediate intercellular communication in cancer, from development to metastasis. EV‐based liquid biopsy is a promising strategy for cancer diagnosis as EVs can be found in cancer patients’ body fluids. In this study, the lipid composition of breast cancer‐derived EVs was studied as well as the potential of blood plasma EVs for the identification of lipid biomarkers for breast cancer detection. Initially, an untargeted lipidomic analysis was carried out for a panel of cancerous and non‐cancerous mammary epithelial cells and their secreted EVs. We found that breast cancer‐derived EVs are enriched in sphingolipids and glycerophospholipids compared to their parental cells. The initial in vitro study showed that EVs and their parental cells can be correctly classified (100% accuracy) between cancerous and non‐cancerous, as well as into their respective breast cancer subtypes, based on their lipid composition. Subsequently, an untargeted lipidomic analysis was carried out for blood plasma EVs from women diagnosed with breast cancer (primary or progressive metastatic breast cancer) as well as healthy women. Correspondingly, when blood plasma EVs were analysed, breast cancer patients and healthy women were correctly classified with an overall accuracy of 93.1%, based on the EVs’ lipid composition. Similarly, the analysis of patients with primary breast cancer and healthy women showed an overall accuracy of 95% for their correct classification. Furthermore, primary and metastatic breast cancers were correctly classified with an overall accuracy of 89.5%. This reveals that the blood plasma EVs’ lipids may be a promising source of biomarkers for detection of breast cancer. Additionally, this study demonstrates the usefulness of untargeted lipidomics in the study of EV lipid composition and EV‐associated biomarker discovery studies. This is a proof‐of‐concept study and a starting point for further analysis on the identification of EV‐based biomarkers for breast cancer.

Funder

Cancer Research UK

Publisher

Wiley

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