A computational strategy to select optimized protein targets for drug development toward the control of cancer diseases

Detalhes bibliográficos
Autor(a) principal: Carels, Nicolas
Data de Publicação: 2015
Outros Autores: Tilli, Tatiana, Tuszynski, Jack A.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da FIOCRUZ (ARCA)
Texto Completo: https://www.arca.fiocruz.br/handle/icict/23767
Resumo: Fundação Oswaldo Cruz. Centro de Desenvolvimento Tecnológico em Saúde. Rio de Janeiro, RJ, Brasil / Instituto Nacional de Ciência e Tecnologia para Inovação em Doenças Negligenciadas (INCT/IDN). Rio de Janeiro, RJ, Brasil.
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spelling Carels, NicolasTilli, TatianaTuszynski, Jack A.2017-12-23T02:11:57Z2017-12-23T02:11:57Z2015CARELS, N. et al. A Computational Strategy to Select Optimized Protein Targets for Drug Development toward the Control of Cancer Diseases. PLOS One, v. 10, n. 1, p. e0115054, 2015.1932-6203https://www.arca.fiocruz.br/handle/icict/2376710.1371/journal.pone.0115054engPLOSAlvos proteicosCâncerA computational strategy to select optimized protein targets for drug development toward the control of cancer diseasesinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleFundação Oswaldo Cruz. Centro de Desenvolvimento Tecnológico em Saúde. Rio de Janeiro, RJ, Brasil / Instituto Nacional de Ciência e Tecnologia para Inovação em Doenças Negligenciadas (INCT/IDN). Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Centro de Desenvolvimento Tecnológico em Saúde. Rio de Janeiro, RJ, Brasil / Instituto Nacional de Ciência e Tecnologia para Inovação em Doenças Negligenciadas (INCT/IDN). Rio de Janeiro, RJ, Brasil.University of Alberta. Faculty of Medicine & Dentistry. Department of Oncology. Department of Physics. Edmonton, Alberta, Canada.In this report, we describe a strategy for the optimized selection of protein targets suitable for drug development against neoplastic diseases taking the particular case of breast cancer as an example. We combined human interactome and transcriptome data from malignant and control cell lines because highly connected proteins that are up-regulated in malignant cell lines are expected to be suitable protein targets for chemotherapy with a lower rate of undesirable side effects. We normalized transcriptome data and applied a statistic treatment to objectively extract the sub-networks of down- and up-regulated genes whose proteins effectively interact. We chose the most connected ones that act as protein hubs, most being in the signaling network. We show that the protein targets effectively identified by the combination of protein connectivity and differential expression are known as suitable targets for the successful chemotherapy of breast cancer. Interestingly, we found additional proteins, not generally targeted by drug treatments, which might justify the extension of existing formulation by addition of inhibitors designed against these proteins with the consequence of improving therapeutic outcomes. The molecular alterations observed in breast cancer cell lines represent either driver events and/or driver pathways that are necessary for breast cancer development or progression. However, it is clear that signaling mechanisms of the luminal A, B and triple negative subtypes are different. Furthermore, the up- and down-regulated networks predicted subtype-specific drug targets and possible compensation circuits between up- and down-regulated genes. We believe these results may have significant clinical implications in the personalized treatment of cancer patients allowing an objective approach to the recycling of the arsenal of available drugs to the specific case of each breast cancer given their distinct qualitative and quantitative molecular traits.info:eu-repo/semantics/openAccessreponame:Repositório Institucional da FIOCRUZ (ARCA)instname:Fundação Oswaldo Cruz (FIOCRUZ)instacron:FIOCRUZLICENSElicense.txtlicense.txttext/plain; charset=utf-83101https://www.arca.fiocruz.br/bitstream/icict/23767/1/license.txt425ef259bcb460998407fbfed7c102d0MD51ORIGINALCarels_etal_2015.pdfCarels_etal_2015.pdfapplication/pdf3474910https://www.arca.fiocruz.br/bitstream/icict/23767/2/Carels_etal_2015.pdf1bfcdc7ba12b522dd957dbf93c99d456MD52journal.pone.0115054.s001.DOCjournal.pone.0115054.s001.DOCMaterial 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dc.title.pt_BR.fl_str_mv A computational strategy to select optimized protein targets for drug development toward the control of cancer diseases
title A computational strategy to select optimized protein targets for drug development toward the control of cancer diseases
spellingShingle A computational strategy to select optimized protein targets for drug development toward the control of cancer diseases
Carels, Nicolas
Alvos proteicos
Câncer
title_short A computational strategy to select optimized protein targets for drug development toward the control of cancer diseases
title_full A computational strategy to select optimized protein targets for drug development toward the control of cancer diseases
title_fullStr A computational strategy to select optimized protein targets for drug development toward the control of cancer diseases
title_full_unstemmed A computational strategy to select optimized protein targets for drug development toward the control of cancer diseases
title_sort A computational strategy to select optimized protein targets for drug development toward the control of cancer diseases
author Carels, Nicolas
author_facet Carels, Nicolas
Tilli, Tatiana
Tuszynski, Jack A.
author_role author
author2 Tilli, Tatiana
Tuszynski, Jack A.
author2_role author
author
dc.contributor.author.fl_str_mv Carels, Nicolas
Tilli, Tatiana
Tuszynski, Jack A.
dc.subject.other.pt_BR.fl_str_mv Alvos proteicos
Câncer
topic Alvos proteicos
Câncer
description Fundação Oswaldo Cruz. Centro de Desenvolvimento Tecnológico em Saúde. Rio de Janeiro, RJ, Brasil / Instituto Nacional de Ciência e Tecnologia para Inovação em Doenças Negligenciadas (INCT/IDN). Rio de Janeiro, RJ, Brasil.
publishDate 2015
dc.date.issued.fl_str_mv 2015
dc.date.accessioned.fl_str_mv 2017-12-23T02:11:57Z
dc.date.available.fl_str_mv 2017-12-23T02:11:57Z
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dc.identifier.citation.fl_str_mv CARELS, N. et al. A Computational Strategy to Select Optimized Protein Targets for Drug Development toward the Control of Cancer Diseases. PLOS One, v. 10, n. 1, p. e0115054, 2015.
dc.identifier.uri.fl_str_mv https://www.arca.fiocruz.br/handle/icict/23767
dc.identifier.issn.pt_BR.fl_str_mv 1932-6203
dc.identifier.doi.none.fl_str_mv 10.1371/journal.pone.0115054
identifier_str_mv CARELS, N. et al. A Computational Strategy to Select Optimized Protein Targets for Drug Development toward the Control of Cancer Diseases. PLOS One, v. 10, n. 1, p. e0115054, 2015.
1932-6203
10.1371/journal.pone.0115054
url https://www.arca.fiocruz.br/handle/icict/23767
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