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Plasma Proteome Profiling with Monoclonal Antibody Libraries: A Pilot Biomarker Analysis for Nanomedicine-Induced Complement Activation

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Advances in Nanoparticles 2013年第2期2卷 133-144页

作者： János Szebeni Zsóka Weiszhár Zoltán Rozsnyay Todd Martinsky János Kádas József Lázár László Takács István Kurucz Arrayit Corporation Sunnyvale USA biosystems international kft. Debrecen Hungary Nanomedicine Research and Education Center Semmelweis University Budapest Hungary Seroscience Ltd. Budapest Hungary

Complement (C) activation-related hypersensitivity reactions (HSRs) represent an unsolved adverse immune effect of many i.v. administered “nanomedicines”, such as liposomal doxorubicin (Doxil/Caelyx). Because these pseudoallergic reactions can be severe or even lethal, it is an important clinical objective to find biomarkers for proneness for C activation by reactogenic nanoparticles that will allow the prediction of in vivo reactions by in vitro assays. With this goal in mind we identified a normal human blood donor who consistently showed high sensitivity to Caelyx-induced C activation in vitro, whose plasma (Caelyx sensitive plasma, CSP) was subjected to proteome profiling with a library of human plasma proteome specific mAbs. The chip (PlasmaScan-380TM) contained 380 non redundant (with respect to epitopes) mAbs. The analysis revealed 8 proteins that were differentially represented in CSP in comparison with Caelyx-insensitive control plasma. These proteins were identified by mass spectrometry and Western blot analyses to represent factor H (decreased in CSP), factor H related protein, serum amyloid P component, fibronectin, complement component C4, Apo B100, prothrombin and alpha-2-HS glycoprotein (all increased in CSP). Some of these protein changes are consistent with proneness for increased C activation, suggesting the potential use of this method in the search for biomarkers for liposome-induced or other types of nanomedicine-induced HSRs.

关键词： Hypersensitivity Reactions Complement Factor H Serum Amyloid P Proteome Profiling Biomarkers

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