International Journal of Molecular Sciences (Feb 2018)

Mass Spectrometry-Based Proteomic Profiling of Thrombotic Material Obtained by Endovascular Thrombectomy in Patients with Ischemic Stroke

  • Roberto Muñoz,
  • Enrique Santamaría,
  • Idoya Rubio,
  • Karina Ausín,
  • Aiora Ostolaza,
  • Alberto Labarga,
  • Miren Roldán,
  • Beatriz Zandio,
  • Sergio Mayor,
  • Rebeca Bermejo,
  • Mónica Mendigaña,
  • María Herrera,
  • Nuria Aymerich,
  • Jorge Olier,
  • Jaime Gállego,
  • Maite Mendioroz,
  • Joaquín Fernández-Irigoyen

DOI
https://doi.org/10.3390/ijms19020498
Journal volume & issue
Vol. 19, no. 2
p. 498

Abstract

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Thrombotic material retrieved from acute ischemic stroke (AIS) patients represents a valuable source of biological information. In this study, we have developed a clinical proteomics workflow to characterize the protein cargo of thrombi derived from AIS patients. To analyze the thrombus proteome in a large-scale format, we developed a workflow that combines the isolation of thrombus by endovascular thrombectomy and peptide chromatographic fractionation coupled to mass-spectrometry. Using this workflow, we have characterized a specific proteomic expression profile derived from four AIS patients included in this study. Around 1600 protein species were unambiguously identified in the analyzed material. Functional bioinformatics analyses were performed, emphasizing a clustering of proteins with immunological functions as well as cardiopathy-related proteins with blood-cell dependent functions and peripheral vascular processes. In addition, we established a reference proteomic fingerprint of 341 proteins commonly detected in all patients. Protein interactome network of this subproteome revealed protein clusters involved in the interaction of fibronectin with 14-3-3 proteins, TGFβ signaling, and TCP complex network. Taken together, our data contributes to the repertoire of the human thrombus proteome, serving as a reference library to increase our knowledge about the molecular basis of thrombus derived from AIS patients, paving the way toward the establishment of a quantitative approach necessary to detect and characterize potential novel biomarkers in the stroke field.

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