Evidence map›Paper›PMID 42057474›Full record

ArticleJournal of extracellular vesicles2026

Lipidome Analysis of Cancer Cells and Their Extracellular Vesicles Reveals Cancer-Type-Specific Lipid Signatures and Enables the Design of EV-Mimetic Liposomes.

Noélie Douanne, Yousra Benslimane, Rubén R López, Prisca Bustamante, Thupten Tsering, Yunxi Chen, Laura Kienzle, Masoud Ghasemi, Lorne Taylor, Yuning Chen and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of extracellular vesicles, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

15 authors.

Noélie DouanneCancer Research Program, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada.
Yousra BenslimaneCancer Research Program, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada.
Rubén R LópezCancer Research Program, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada.
Prisca BustamanteCancer Research Program, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada.
Thupten TseringCancer Research Program, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada.
Yunxi ChenCancer Research Program, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada.
Laura KienzleCancer Research Program, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada.
Masoud GhasemiCancer Research Program, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada.
Lorne TaylorProteomics and Molecular Analysis Platform, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada.
Yuning ChenCancer Research Program, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada.
Anaïs Toreja BoutinCancer Research Program, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada.
David JunckerDepartment of Biomedical Engineering and Victor Philippe Dahdaleh Institute of Genomic Medicine, McGill University, Montreal, Quebec, Canada.ORCID https://orcid.org/0000-0002-7313-1162
Catherine MounierLipid metabolism laboratory, Biological Sciences Department, Université du Québec à Montréal (UQAM), Montréal, Quebec, Canada.
Vahé NerguizianDepartment of Electrical Engineering, École de technologie supérieure, Montreal, Quebec, Canada.
Julia V BurnierCancer Research Program, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada.ORCID https://orcid.org/0000-0002-2184-2157

Funding

Canadian Institutes for Health Research 190179Fonds de Recherche du Québec en Santé 312831National Sciences and Engineering Research Council of Canada 177808
6 · The paper itself

Abstract

Lipid metabolism reprogramming is a hallmark of cancer, yet the global lipidome of cancer cells and their extracellular vesicles (EVs) remains poorly understood. Using mass spectrometry, we analyzed the lipid profiles of a panel of human cancer and non-cancer cell lines along with their secreted EVs. Cancer cells exhibited distinct lipid signatures, including elevated lipid raft components. Cancer-derived EVs displayed unique lipid compositions that clustered separately from cell lipid profiles, suggesting active lipid sorting during EV biogenesis. Comparative analysis of primary and metastatic cells and their EVs, highlighted phospholipid alterations during metastasis. These findings suggest that EV lipid profiles could serve as cancer biomarkers, and the data can inform synthetic EV-based nanoparticle design for drug delivery. Our study provides one of the most comprehensive characterizations of the cancer EV lipidome to date, offering novel insights into lipid metabolism in cancer progression and potential therapeutic applications.

Indexed as

Extracellular VesiclesLipid MetabolismLipidomicsLipidsLiposomesNeoplasmsBiomarkers, TumorCell Line, TumorHumansBiomarkers, TumorLipidsLiposomesbiomarkerscancercells and extracellular vesicles (EVs)colorectal cancerlipid classes/familieslipidomicsliver metastasissaturation levelstumor microenvironmentuveal melanoma

Identifiers

PMID42057474
PMCPMC13129227

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.