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Extracellular vesicles as a promising source of lipid biomarkers for breast cancer detection in blood plasma
Journal article   Open access   Peer reviewed

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

Erika Dorado, Maria Luisa Doria, Anika Nagelkerke, James S McKenzie, Stefania Maneta-Stavrakaki, Thomas E Whittaker, Jeremy K Nicholson, Raoul Charles Coombes, Molly M Stevens and Zoltan Takats
Journal of extracellular vesicles, Vol.13(3), e12419
2024
DOI: https://doi.org/10.1002/jev2.12419
PMID: 38443328
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Published 1.96 MBDownloadView
Published (Version of Record)CC BY V4.0,  Open Access

Abstract

breast cancer extracellular vesicles lipidomics liquid biopsy mass spectrometry
Extracellular 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.

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Citation topics
1 Clinical & Life Sciences
1.196 Micro & Long Noncoding RNA
1.196.1475 Exosomes
Web Of Science research areas
Cell Biology
ESI research areas
Biology & Biochemistry
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