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


ABSTRACT: 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.

SUBMITTER: Korkut A 

PROVIDER: S-EPMC4539601 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature

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

Korkut Anil A   Wang Weiqing W   Demir Emek E   Aksoy Bülent Arman BA   Jing Xiaohong X   Molinelli Evan J EJ   Babur Özgün Ö   Bemis Debra L DL   Onur Sumer Selcuk S   Solit David B DB   Pratilas Christine A CA   Sander Chris C  

eLife 20150818


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 computationall  ...[more]

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