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Perturbation biology nominates upstream–downstream drug combinations in RAF inhibitor resistant melanoma cells

Resistance to targeted cancer therapies is an important clinical problem. The discovery of anti-resistance drug combinations is challenging as resistance can arise by diverse escape mechanisms. To address this challenge, we improved and applied the experimental-computational perturbation biology met...

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Autores principales: Korkut, Anil, Wang, Weiqing, Demir, Emek, Aksoy, Bülent Arman, Jing, Xiaohong, Molinelli, Evan J, Babur, Özgün, Bemis, Debra L, Onur Sumer, Selcuk, Solit, David B, Pratilas, Christine A, Sander, Chris
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4539601/
https://www.ncbi.nlm.nih.gov/pubmed/26284497
http://dx.doi.org/10.7554/eLife.04640
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author Korkut, Anil
Wang, Weiqing
Demir, Emek
Aksoy, Bülent Arman
Jing, Xiaohong
Molinelli, Evan J
Babur, Özgün
Bemis, Debra L
Onur Sumer, Selcuk
Solit, David B
Pratilas, Christine A
Sander, Chris
author_facet Korkut, Anil
Wang, Weiqing
Demir, Emek
Aksoy, Bülent Arman
Jing, Xiaohong
Molinelli, Evan J
Babur, Özgün
Bemis, Debra L
Onur Sumer, Selcuk
Solit, David B
Pratilas, Christine A
Sander, Chris
author_sort Korkut, Anil
collection PubMed
description Resistance to targeted cancer therapies is an important clinical problem. The discovery of anti-resistance drug combinations is challenging as resistance can arise by diverse escape mechanisms. To address this challenge, we improved and applied the experimental-computational perturbation biology method. Using statistical inference, we build network models from high-throughput measurements of molecular and phenotypic responses to combinatorial targeted perturbations. The models are computationally executed to predict the effects of thousands of untested perturbations. In RAF-inhibitor resistant melanoma cells, we measured 143 proteomic/phenotypic entities under 89 perturbation conditions and predicted c-Myc as an effective therapeutic co-target with BRAF or MEK. Experiments using the BET bromodomain inhibitor JQ1 affecting the level of c-Myc protein and protein kinase inhibitors targeting the ERK pathway confirmed the prediction. In conclusion, we propose an anti-cancer strategy of co-targeting a specific upstream alteration and a general downstream point of vulnerability to prevent or overcome resistance to targeted drugs. DOI: http://dx.doi.org/10.7554/eLife.04640.001
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spelling pubmed-45396012015-08-25 Perturbation biology nominates upstream–downstream drug combinations in RAF inhibitor resistant melanoma cells Korkut, Anil Wang, Weiqing Demir, Emek Aksoy, Bülent Arman Jing, Xiaohong Molinelli, Evan J Babur, Özgün Bemis, Debra L Onur Sumer, Selcuk Solit, David B Pratilas, Christine A Sander, Chris eLife Cell Biology Resistance to targeted cancer therapies is an important clinical problem. The discovery of anti-resistance drug combinations is challenging as resistance can arise by diverse escape mechanisms. To address this challenge, we improved and applied the experimental-computational perturbation biology method. Using statistical inference, we build network models from high-throughput measurements of molecular and phenotypic responses to combinatorial targeted perturbations. The models are computationally executed to predict the effects of thousands of untested perturbations. In RAF-inhibitor resistant melanoma cells, we measured 143 proteomic/phenotypic entities under 89 perturbation conditions and predicted c-Myc as an effective therapeutic co-target with BRAF or MEK. Experiments using the BET bromodomain inhibitor JQ1 affecting the level of c-Myc protein and protein kinase inhibitors targeting the ERK pathway confirmed the prediction. In conclusion, we propose an anti-cancer strategy of co-targeting a specific upstream alteration and a general downstream point of vulnerability to prevent or overcome resistance to targeted drugs. DOI: http://dx.doi.org/10.7554/eLife.04640.001 eLife Sciences Publications, Ltd 2015-08-18 /pmc/articles/PMC4539601/ /pubmed/26284497 http://dx.doi.org/10.7554/eLife.04640 Text en © 2015, Korkut et al http://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Cell Biology
Korkut, Anil
Wang, Weiqing
Demir, Emek
Aksoy, Bülent Arman
Jing, Xiaohong
Molinelli, Evan J
Babur, Özgün
Bemis, Debra L
Onur Sumer, Selcuk
Solit, David B
Pratilas, Christine A
Sander, Chris
Perturbation biology nominates upstream–downstream drug combinations in RAF inhibitor resistant melanoma cells
title Perturbation biology nominates upstream–downstream drug combinations in RAF inhibitor resistant melanoma cells
title_full Perturbation biology nominates upstream–downstream drug combinations in RAF inhibitor resistant melanoma cells
title_fullStr Perturbation biology nominates upstream–downstream drug combinations in RAF inhibitor resistant melanoma cells
title_full_unstemmed Perturbation biology nominates upstream–downstream drug combinations in RAF inhibitor resistant melanoma cells
title_short Perturbation biology nominates upstream–downstream drug combinations in RAF inhibitor resistant melanoma cells
title_sort perturbation biology nominates upstream–downstream drug combinations in raf inhibitor resistant melanoma cells
topic Cell Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4539601/
https://www.ncbi.nlm.nih.gov/pubmed/26284497
http://dx.doi.org/10.7554/eLife.04640
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