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@ARTICLE{RiosdelosRiosResendiz:302882,
      author       = {J. Rios de los Rios Resendiz$^*$ and F. Herrmann-Sim$^*$
                      and L. Wilkesmann$^*$ and D. Helm$^*$ and M. Schneider$^*$
                      and G. Campione$^*$ and K. Plügge$^*$ and G. Greiner$^*$
                      and L. Lazaro Garcia$^*$ and J. Berker$^*$ and K.
                      Richter$^*$ and L. Zielske$^*$ and W.-K. Hofmann and K.
                      Clemm von Hohenberg$^*$},
      title        = {{A} translational protocol optimizes the isolation of
                      plasma-derived extracellular vesicle proteomics.},
      journal      = {Scientific reports},
      volume       = {15},
      number       = {1},
      issn         = {2045-2322},
      address      = {[London]},
      publisher    = {Springer Nature},
      reportid     = {DKFZ-2025-01422},
      pages        = {24292},
      year         = {2025},
      note         = {#EA:B470#LA:B470#},
      abstract     = {In translational research and clinical routine, liquid
                      biopsy is a promising tool to direct individually targeted
                      treatments. Among the components of liquid biopsy,
                      extracellular vesicles (EVs) carry manyfold molecular cargo
                      and are increasingly being studied for biomarker
                      identification. In order to identify potential confounding
                      factors and determine optimal conditions when studying
                      blood-derived EV proteins, the impact of pre-analytical
                      variables needs to be assessed. Here we establish an EV
                      enrichment for proteomic analysis workflow in a real-world
                      clinical setting in which we evaluate variables from blood
                      collection through protein preparation and storage for mass
                      spectrometry (MS). We assess hemolysis, particle
                      concentration and size, protein quantity, protein markers
                      and comprehensive proteomic analysis using mass spectrometry
                      to assess the influence of different pre-analytical
                      variables like blood collection tubes, transportation of
                      blood samples and delayed processing. Under these
                      conditions, density gradient and size exclusion
                      chromatography using Sepharose CL-4B show good EV
                      enrichment. For MS, lysis with increased protease inhibitors
                      shows high protein yields while TCA protein precipitation
                      results in high numbers of identified proteins. In summary,
                      we develop here an optimized protocol for the analysis of
                      plasma EV-derived proteomics, evaluating pre-analytical
                      variables relevant for implementation in a clinical
                      setting.},
      keywords     = {Extracellular Vesicles: metabolism / Extracellular
                      Vesicles: chemistry / Humans / Proteomics: methods / Mass
                      Spectrometry / Blood Proteins / Translational Research,
                      Biomedical: methods / Biomarkers: blood / Proteome / Liquid
                      Biopsy: methods / Extracellular vesicles (Other) / Liquid
                      biopsy (Other) / Plasma (Other) / Pre-analytics (Other) /
                      Proteomics (Other) / Translation (Other) / Blood Proteins
                      (NLM Chemicals) / Biomarkers (NLM Chemicals) / Proteome (NLM
                      Chemicals)},
      cin          = {B470 / W120 / W230},
      ddc          = {600},
      cid          = {I:(DE-He78)B470-20160331 / I:(DE-He78)W120-20160331 /
                      I:(DE-He78)W230-20160331},
      pnm          = {312 - Funktionelle und strukturelle Genomforschung
                      (POF4-312)},
      pid          = {G:(DE-HGF)POF4-312},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:40624148},
      pmc          = {pmc:PMC12234866},
      doi          = {10.1038/s41598-025-08366-8},
      url          = {https://inrepo02.dkfz.de/record/302882},
}