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Bioinformatics Advance Access published online on March 7, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl077
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© The Author (2006). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received January 13, 2006
Revised February 10, 2006
Accepted February 27, 2006

Discovery note

Convergence of the proteomic pattern in cancer

Ute Müller 1, Günther Ernst 2, Christian Melle 2, Reinhard Guthke 3, and Ferdinand von Eggeling 2 *

1 Core Unit Chip Application (CUCA), Institute of Human Genetics and Anthropology, Friedrich-Schiller-University, 07740 Jena, Germany; aura optik gmbh, Wildenbruchstraße 15, 07745 Jena, Germany
2 Core Unit Chip Application (CUCA), Institute of Human Genetics and Anthropology, Friedrich-Schiller-University, 07740 Jena, Germany
3 Leibniz Institute for Natural Product Research and Infection Biology - Hans Knoell Institute (HKI), 07745 Jena, Germany

* To whom correspondence should be addressed.
Ferdinand von Eggeling, E-mail: fegg{at}mti.uni-jena.de


  Abstract

Motivation: On the histological level the differentiation of normal epithelial tissues is well known and also the phenomenon of dedifferentiation which occurs the more the cells develop towards malignancy. To identify an epithelial tumor-specific proteomic profile as well as to measure the proximities between we used data from tumor tissue and adjacent normal tissue microdissected from head and neck and colon cancer samples which were analyzed using ProteinChip technology and performed a bioinformatic meta-analysis on the resulting four complex data sets.

Results: All four groups could be identified based on their proteomic signatures and the tumor tissues were found to be more similar to one another than to the normal epithelial tissue from which they progressed. This study shows at the proteomic level that changes in the histological features of tumors as compared to the tissues from which they arise are reflected in the convergence of proteomic pattern during the development to cancer.

Supplementary information: Supplementary data for this paper are available on Bioinformatics online.

UM and GE contributed equally to this to this work

Associate Editor: Jonathan Wren


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