Evidence map›Paper›PMID 38443328›Full record

ArticleJournal of extracellular vesicles2024

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, Zoltan Takats

Open access · goldAbstract read
In one paragraph

Article in Journal of extracellular vesicles, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed
16.6field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

45 citing papers in PubMed, 72 citations in OpenAlex.

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  19. 80 years of extracellular vesicles: from discovery to clinical translation.Extracellular vesicles and circulating nucleic acids · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 3 countries.

Erika DoradoFaculty of Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0001-5244-092X
Maria Luisa DoriaFaculty of Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom.
Anika NagelkerkeFaculty of Engineering, Department of Bioengineering, Department of Materials, Institute of Biomedical Engineering, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-7541-588X
James S McKenzieFaculty of Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-1007-317X
Stefania Maneta-StavrakakiFaculty of Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-4621-4704
Thomas E WhittakerFaculty of Engineering, Department of Bioengineering, Department of Materials, Institute of Biomedical Engineering, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-3181-4571
Jeremy K NicholsonInstitute of Global Health Innovation, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-8123-8349
Raoul Charles CoombesFaculty of Medicine, Department of Surgery and Cancer, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-4811-1100
Molly M StevensFaculty of Engineering, Department of Bioengineering, Department of Materials, Institute of Biomedical Engineering, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-7335-266X
Zoltan TakatsFaculty of Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-0795-3467
Imperial College London · GBNIHR Imperial Biomedical Research Centre · GBInserm · FR

Funding

Cancer Research UK C52720/A27886Cancer Research UK Rosetta Grand Challenge project
6 · The paper itself

Abstract

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.

Indexed as

Breast NeoplasmsExtracellular VesiclesBiomarkersFemaleGlycerophospholipidsHumansPlasmaBiomarkersGlycerophospholipidsbreast cancerextracellular vesicleslipidomicsliquid biopsymass spectrometry

Identifiers

PMID38443328
PMCPMC10914699
OpenAlexW4392515388

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.