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BioMed Research International
Volume 2013 (2013), Article ID 976816, 11 pages
Research Article

The Human Cell Surfaceome of Breast Tumors

1Ludwig Institute for Cancer Research, São Paulo 01308-050, SP, Brazil
2Center for Applied Toxinology, Butantan Institute, São Paulo 05503-900, SP, Brazil
3Centro de Oncologia Molecular Hospital Sírio-Libanês, São Paulo 01308-050, SP, Brazil
4Instituto de Bioinformática e Biotecnologia, Natal 59064-560, RN, Brazil
5Fluidigm Inc., South San Francisco 94080, CA, USA
6Hospital AC Camargo, São Paulo 01509, SP, Brazil
7Ludwig Institute for Cancer Research, New York 10017, NY, USA
8Brain Institute, Federal University of Rio Grande do Norte, Natal 59064-560, RN, Brazil

Received 21 March 2013; Accepted 22 July 2013

Academic Editor: Lubna Nasir

Copyright © 2013 Júlia Pinheiro Chagas da Cunha et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Introduction. Cell surface proteins are ideal targets for cancer therapy and diagnosis. We have identified a set of more than 3700 genes that code for transmembrane proteins believed to be at human cell surface. Methods. We used a high-throuput qPCR system for the analysis of 573 cell surface protein-coding genes in 12 primary breast tumors, 8 breast cell lines, and 21 normal human tissues including breast. To better understand the role of these genes in breast tumors, we used a series of bioinformatics strategies to integrates different type, of the datasets, such as KEGG, protein-protein interaction databases, ONCOMINE, and data from, literature. Results. We found that at least 77 genes are overexpressed in breast primary tumors while at least 2 of them have also a restricted expression pattern in normal tissues. We found common signaling pathways that may be regulated in breast tumors through the overexpression of these cell surface protein-coding genes. Furthermore, a comparison was made between the genes found in this report and other genes associated with features clinically relevant for breast tumorigenesis. Conclusions. The expression profiling generated in this study, together with an integrative bioinformatics analysis, allowed us to identify putative targets for breast tumors.