Literature DB >> 21738817

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

Claudia Röwer1, Björn Ziems, Anngret Radtke, Oliver Schmitt, Toralf Reimer, Cornelia Koy, Hans-Jürgen Thiesen, Bernd Gerber, Michael O Glocker.   

Abstract

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.

Entities:  

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

Mesh:

Substances:

Year:  2011        PMID: 21738817      PMCID: PMC3127067     

Source DB:  PubMed          Journal:  Int J Clin Exp Pathol        ISSN: 1936-2625


  31 in total

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Review 3.  Quantification of immunohistochemistry--issues concerning methods, utility and semiquantitative assessment II.

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9.  Classification and grading of invasive breast carcinoma.

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10.  Object orientated automated image analysis: quantitative and qualitative estimation of inflammation in mouse lung.

Authors:  Coralie Apfeldorfer; Kristina Ulrich; Gareth Jones; David Goodwin; Susie Collins; Emanuel Schenck; Virgile Richard
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  4 in total

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Journal:  J Exp Clin Cancer Res       Date:  2018-03-02

2.  Analysis of the Interaction Network of Hub miRNAs-Hub Genes, Being Involved in Idiopathic Pulmonary Fibers and Its Emerging Role in Non-small Cell Lung Cancer.

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Journal:  Front Genet       Date:  2020-04-02       Impact factor: 4.599

3.  Proteomic Profiling of Retinoblastoma-Derived Exosomes Reveals Potential Biomarkers of Vitreous Seeding.

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Journal:  Cancers (Basel)       Date:  2020-06-12       Impact factor: 6.639

4.  Osteoglycin-induced VEGF Inhibition Enhances T Lymphocytes Infiltrating in Colorectal Cancer.

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  4 in total

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