Evidence map›Paper›PMID 38353833›Full record

ArticleCellular and molecular life sciences : CMLS2024

Size-exclusion chromatography combined with DIA-MS enables deep proteome profiling of extracellular vesicles from melanoma plasma and serum.

Evelyn Lattmann, Luca Räss, Marco Tognetti, Julia M Martínez Gómez, Valérie Lapaire, Roland Bruderer, Lukas Reiter, Yuehan Feng, Lars M Steinmetz, Mitchell P Levesque

Open access · goldAbstract read
In one paragraph

Article in Cellular and molecular life sciences : CMLS, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
3.7field-weighted citation impact, top 6% 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

11 citing papers in PubMed, 16 citations in OpenAlex.

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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.

Evelyn LattmannDepartment of Dermatology, University Hospital Zurich, University of Zurich, Schlieren, Switzerland.
Luca RässBiognosys AG, Schlieren, Switzerland.
Marco TognettiBiognosys AG, Schlieren, Switzerland.
Julia M Martínez GómezDepartment of Dermatology, University Hospital Zurich, University of Zurich, Schlieren, Switzerland.
Valérie LapaireDepartment of Dermatology, University Hospital Zurich, University of Zurich, Schlieren, Switzerland.
Roland BrudererBiognosys AG, Schlieren, Switzerland.
Lukas ReiterBiognosys AG, Schlieren, Switzerland.
Yuehan FengBiognosys AG, Schlieren, Switzerland.
Lars M SteinmetzStanford Genome Technology Center, Stanford University, Palo Alto, CA, USA. Lars.Steinmetz@stanford.edu.ORCID http://orcid.org/0000-0002-3962-2865
Mitchell P LevesqueDepartment of Dermatology, University Hospital Zurich, University of Zurich, Schlieren, Switzerland. Mitchell.Levesque@usz.ch.ORCID http://orcid.org/0000-0001-5902-9420
Biognosys (Switzerland) · CHUniversity of Zurich · CHStanford Medicine · US

Funding

Universität Zürich University Research Priority Project
6 · The paper itself

Abstract

Extracellular vesicles (EVs) are important players in melanoma progression, but their use as clinical biomarkers has been limited by the difficulty of profiling blood-derived EV proteins with high depth of coverage, the requirement for large input amounts, and complex protocols. Here, we provide a streamlined and reproducible experimental workflow to identify plasma- and serum- derived EV proteins of healthy donors and melanoma patients using minimal amounts of sample input. SEC-DIA-MS couples size-exclusion chromatography to EV concentration and deep-proteomic profiling using data-independent acquisition. From as little as 200 µL of plasma per patient in a cohort of three healthy donors and six melanoma patients, we identified and quantified 2896 EV-associated proteins, achieving a 3.5-fold increase in depth compared to previously published melanoma studies. To compare the EV-proteome to unenriched blood, we employed an automated workflow to deplete the 14 most abundant proteins from plasma and serum and thereby approximately doubled protein group identifications versus native blood. The EV proteome diverged from corresponding unenriched plasma and serum, and unlike the latter, separated healthy donor and melanoma patient samples. Furthermore, known melanoma markers, such as MCAM, TNC, and TGFBI, were upregulated in melanoma EVs but not in depleted melanoma plasma, highlighting the specific information contained in EVs. Overall, EVs were significantly enriched in intact membrane proteins and proteins related to SNARE protein interactions and T-cell biology. Taken together, we demonstrated the increased sensitivity of an EV-based proteomic workflow that can be easily applied to larger melanoma cohorts and other indications.

Indexed as

Extracellular VesiclesMelanomaChromatography, GelHumansProteomeProteomicsProteomeExosomeExtracellular vesicleMass spectrometryMelanomaProteomicsSize-exclusion chromatography

Identifiers

PMID38353833
PMCPMC10867102
OpenAlexW4391817018

What OpenQuestion holds

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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.