Raoul Charles Coombes

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Imperial College London
Country flagUnited Kingdom

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Recent Grants

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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

-

SPAIN
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Zoltan Takats

-

UNITED KINGDOM
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Iain Macpherson

Professor of Breast Oncology

-

UNITED KINGDOM
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Alastair D. Lamb

-

UNITED KINGDOM
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Jeremy Kirk Nicholson

Imperial College London Faculty of Medicine

UNITED KINGDOM
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Philip Badman

Imperial College London

UNITED KINGDOM
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Carlo Palmieri

University of Liverpool

UNITED KINGDOM
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Mark Rehkämper

Imperial College London

UNITED KINGDOM
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Zahi I Mitri

Oregon Health & Science University

UNITED STATES
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Dónal Landers

The University of Manchester

UNITED KINGDOM
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Florent Mouliere

Group Leader / Assistant Professor

VU medisch centrum

NETHERLANDS
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