Please use this identifier to cite or link to this item: https://repositorio.ufrn.br/jspui/handle/123456789/23336
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dc.contributor.authorJúlia Pinheiro Chagas da Cunha-
dc.contributor.authorPedro Alexandre Favoretto Galante-
dc.contributor.authorJorge Estefano Santana de Souza-
dc.contributor.authorMartin Pieprzyk-
dc.contributor.authorDirceMaria Carraro-
dc.contributor.authorLloyd J. Old-
dc.contributor.authorAnamaria Aranha Camargo-
dc.contributor.authorSandro José de Souza-
dc.date.accessioned2017-06-01T12:57:32Z-
dc.date.available2017-06-01T12:57:32Z-
dc.date.issued2013-
dc.identifier.issn2314-6133-
dc.identifier.urihttps://repositorio.ufrn.br/jspui/handle/123456789/23336-
dc.languageengpt_BR
dc.rightsAcesso Abertopt_BR
dc.subjectHuman Cell Surfaceomept_BR
dc.subjectBreast Tumorspt_BR
dc.titleThe Human Cell Surfaceome of Breast Tumorspt_BR
dc.typearticlept_BR
dc.description.resumoCell 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, togetherwith an integrative bioinformatics analysis, allowed us to identify putative targets for breast tumors.pt_BR
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