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

International Journal of Clinical and Experimental Pathology

Claudia Röwer¹ 

关键词: Breast carcinoma;    proteome analysis;    proteomics;    protein expression signature;    mass spectrometry;    immunohistochemistry;    tissue microarrays;    image analysis;    toponomics;    toponostics;   

DOI  :  

学科分类：生理学与病理学

来源: e-Century Publishing Corporation

【 摘 要 】

Due to enormous advances in quantitative proteomics and in immunohistochemistry (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, nucleoside diphosphate kinase A/B (NDKA/B), osteoinducive factor (mimecan), and pyru-vate 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.

【 授权许可】

CC BY-NC