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Int J Clin Exp Pathol 2011;4(5):454-467

Original Article
Toponostics of invasive ductal breast carcinoma: combination of spatial protein
expression imaging and quantitative proteome signature analysis

Claudia Röwer, Björn Ziems, Anngret Radtke, Oliver Schmitt, Toralf Reimer, Cornelia Koy, Hans-Jürgen Thiesen, Bernd Gerber, Michael O.

Proteome Center Rostock, University of Rostock, Rostock, Germany. Institute of Immunology, University of Rostock, Rostock, Germany.
IndyMed GmbH, Rostock, Germany. Partnerschaft der Fachärzte für Pathologie, Südstadt Clinical Center, Rostock, Germany. Department of
Anatomy, University of Rostock, Rostock, Germany. Department of Obstetrics and Gynecology, University of Rostock, Rostock, Germany

Received May 31, 2011; accepted June, 2011; Epub June, 2011, published June, 2011

Abstract: Due to enormous advances in quantitative proteomics and in immunohisto¬chemistry (pathology), the two research areas have now
reached the state to be successfully interwoven in order to tackle challenges in toponostics and to open tumor-targeted systems pathology
approaches. In this study the differential expressions of candidate proteins nucleophosmin, NDKA/B, osteoinducive factor (mimecan), and
pyruvate kinase M2 from a quantitative proteome signature for invasive ductal breast cancer were determined by immunohistochemistry on 53
tissue slices from formalin-fixed and paraffin-embedded tumor and control tissue samples from ten patients and fourteen controls. In addition,
87 images from the Human Protein Atlas representing seven tumor and nine normal breast tissue samples were investigated by
computer-assisted semi-quantitative density measurements on nucleophosmin, nucleoside diphosphate kinase A/B (NDKA/B), osteoinducive
factor (mimecan), pyruvate kinase M2, glyceraldehyde-3-phosphate dehydro¬genase (GAP-DH), and mimecan (osteoinductive factor). Both IHC
data sets match well to each other and support the quantitative proteome analysis data. Determining spatial distribution of signature protein
expressions by protein imaging on morphologically intact tissue samples at the sub-cellular level and, hence, keeping all topological
information, presents an added value to quantitative proteome data. Such comprehensive data sets are needed for both, pathway analyses and
for "next generation clinical diagnostics" approaches. (IJCEP1105007)

Keywords: Breast carcinoma, proteome analysis, proteomics, protein expression signature, mass spectrometry, immunohistochemistry,
tissue microarrays, image analysis, toponomics, toponostics

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Address all correspondence to:
Prof. Dr. Michael O. Glocker
Proteome Center Rostock
Department for Proteome Research
Institute of Immunology
Medical Faculty and
Natural Science Faculty
University of Rostock
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