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Size-exclusion chromatography combined with DIA-MS enables deep proteome profiling of extracellular vesicles from melanoma plasma and serum.
Lattmann, Evelyn; Räss, Luca; Tognetti, Marco; Gómez, Julia M Martínez; Lapaire, Valérie; Bruderer, Roland; Reiter, Lukas; Feng, Yuehan; Steinmetz, Lars M; Levesque, Mitchell P.
Afiliação
  • Lattmann E; Department of Dermatology, University Hospital Zurich, University of Zurich, Schlieren, Switzerland.
  • Räss L; Biognosys AG, Schlieren, Switzerland.
  • Tognetti M; Biognosys AG, Schlieren, Switzerland.
  • Gómez JMM; Department of Dermatology, University Hospital Zurich, University of Zurich, Schlieren, Switzerland.
  • Lapaire V; Department of Dermatology, University Hospital Zurich, University of Zurich, Schlieren, Switzerland.
  • Bruderer R; Biognosys AG, Schlieren, Switzerland.
  • Reiter L; Biognosys AG, Schlieren, Switzerland.
  • Feng Y; Biognosys AG, Schlieren, Switzerland.
  • Steinmetz LM; Stanford Genome Technology Center, Stanford University, Palo Alto, CA, USA. Lars.Steinmetz@stanford.edu.
  • Levesque MP; Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA. Lars.Steinmetz@stanford.edu.
Cell Mol Life Sci ; 81(1): 90, 2024 Feb 14.
Article em En | MEDLINE | ID: mdl-38353833
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.
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Vesículas Extracelulares / Melanoma Tipo de estudo: Guideline Limite: Humans Idioma: En Revista: Cell Mol Life Sci Assunto da revista: BIOLOGIA MOLECULAR Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Suíça

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Vesículas Extracelulares / Melanoma Tipo de estudo: Guideline Limite: Humans Idioma: En Revista: Cell Mol Life Sci Assunto da revista: BIOLOGIA MOLECULAR Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Suíça