Raoul Charles Coombes
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Recent Grants
Grant: Close
Optical Fluorescence Micro and Nanoscopy to determine and quantify functional molecular interactions and dynamics across time and length scales
Open Date: 2021-06-30
Close Date: 2022-06-29
Grant: Close
Bionanofabrication Suite
Open Date: 2018-07-31
Close Date: 2023-07-30
Grant: Close
Imperial Confidence in Concept: ICIC6
Open Date: 2018-03-01
Close Date: 2020-02-28
Grant: Close
Mi-CARE: A Microchip-based diagnostic Companion for Early Detection and Therapeutic Monitoring of Breast Cancer
Open Date: 2018-01-01
Close Date: 2020-12-31
Grant: Close
Imperial Confidence in Concept: ICiC
Open Date: 2016-03-01
Close Date: 2018-02-28
Articles (8)
Year:
2025
Year:
2025
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.
Year:
2024
Year:
2023
Year:
2023
Year:
2023
Year:
2022
Year:
2021
Collaborators (11)
Javier García-Corbacho
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Zoltan Takats
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Iain Macpherson
Professor of Breast Oncology
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Alastair D. Lamb
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Jeremy Kirk Nicholson
Imperial College London Faculty of Medicine
Philip Badman
Imperial College London
Carlo Palmieri
University of Liverpool
Mark Rehkämper
Imperial College London
Zahi I Mitri
Oregon Health & Science University
Dónal Landers
The University of Manchester
Florent Mouliere
Group Leader / Assistant Professor
VU medisch centrum
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