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pmid:39141927

Defining the Soluble and Extracellular Vesicle Protein Compartments of Plasma Using In-Depth Mass Spectrometry-Based Proteomics.

Nidhi Sharma · Silvia Angori · AnnSofi Sandberg · Georgios Mermelekas · Janne Lehtiö · Oscar P B Wiklander · André Görgens · Samir El Andaloussi · Hanna Eriksson · Maria Pernemalm

Journal of proteome research · 2024 doi:10.1021/acs.jproteome.4c00490

Paper

complete

Experiment

partial

Data

partial

Analysis

partial

Execution

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Defining the Soluble and Extracellular Vesicle Protein Compartments of Plasma Using In-Depth Mass Spectrometry-Based Proteomics.
doi
10.1021/acs.jproteome.4c00490
pmid
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Nidhi Sharma
[1]
Silvia Angori
[2]
AnnSofi Sandberg
[3]
Georgios Mermelekas
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Janne Lehtiö
[5]
Oscar P B Wiklander
[6]
André Görgens
[7]
Samir El Andaloussi
[8]
Hanna Eriksson
[9]
Maria Pernemalm
journal
Journal of proteome research
year
2024
abstract
Plasma-derived extracellular vesicles (pEVs) are a potential source of diseased biomarker proteins. However, characterizing the pEV proteome is challenging due to its relatively low abundance and difficulties in enrichment. This study presents a streamlined workflow to identify EV proteins from cancer patient plasma using minimal sample input. Starting with 400 μL of plasma, we generated a comprehensive pEV proteome using size exclusion chromatography (SEC) combined with HiRIEF prefractionation-based mass spectrometry (MS). First, we compared the performance of HiRIEF and long gradient MS workflows using control pEVs, quantifying 2076 proteins with HiRIEF. In a proof-of-concept study, we applied SEC-HiRIEF-MS to a small cohort (12) of metastatic lung adenocarcinoma (LUAD) and malignant melanoma (MM) patients. We also analyzed plasma samples from the same patients to study the relationship between plasma and pEV proteomes. We identified and quantified 1583 proteins in cancer pEVs and 1468 proteins in plasma across all samples. While there was substantial overlap, the pEV proteome included several unique EV markers and cancer-related proteins. Differential analysis revealed 30 DEPs in LUAD vs the MM group, highlighting the potential of pEVs as biomarkers. This work demonstrates the utility of a prefractionation-based MS for comprehensive pEV proteomics and EV biomarker discovery. Data are available via ProteomeXchange with the identifiers PXD039338 and PXD038528.
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