• Medientyp: E-Artikel
  • Titel: Plasma protein analysis of patients with different B‐cell lymphomas using high‐content antibody microarrays
  • Beteiligte: Schröder, Christoph; Srinivasan, Harish; Sill, Martin; Linseisen, Jakob; Fellenberg, Kurt; Becker, Nikolaus; Nieters, Alexandra; Hoheisel, Jörg D.
  • Erschienen: Wiley, 2013
  • Erschienen in: PROTEOMICS – Clinical Applications
  • Sprache: Englisch
  • DOI: 10.1002/prca.201300048
  • ISSN: 1862-8346; 1862-8354
  • Schlagwörter: Clinical Biochemistry
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: <jats:sec><jats:title>Purpose</jats:title><jats:p>In this study, plasma samples from a multicentric case‐control study on lymphoma were analyzed for the identification of proteins useful for diagnosis.</jats:p></jats:sec><jats:sec><jats:title>Experimental design</jats:title><jats:p>The protein content in the plasma of 100 patients suffering from the three most common B‐cell lymphomas and 100 control samples was studied with antibody microarrays composed of 810 antibodies that target cancer‐associated proteins. Sample pools were screened for an identification of marker proteins. Then, the samples were analyzed individually to validate the usability of these markers.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>More than 200 proteins with disease‐associated abundance changes were found. The evaluation on individual patients confirmed some molecules as robust informative markers while others were inadequate for this purpose. In addition, the analysis revealed distinct subgroups for each of the three investigated B‐cell lymphoma subtypes. With this information, we delineated a classifier that discriminates the different lymphoma entities.</jats:p></jats:sec><jats:sec><jats:title>Conclusions and clinical relevance</jats:title><jats:p>Variations in plasma protein abundance permit discrimination between different patient groups. After validation on a larger study cohort, the findings could have diagnostic as well as differential diagnostic potential. Beside this, methodological aspects were critically evaluated, such as the value of sample pooling for the identification of biomarkers that are useful for a diagnosis on individual patients.</jats:p></jats:sec>