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

Anil Korkut, Weiqing Wang, Emek Demir, Bulent Arman Aksoy, Xiaohong Jing, Evan J. Molinelli, Özgün Babur, Debra L. Bemis, Selcuk Onur Sumer, David B. Solit, Christine A. Pratilas, Chris Sander

Research output: Contribution to journalArticlepeer-review

44 Scopus citations

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.

Original languageEnglish (US)
Article numbere04640
JournaleLife
Volume4
Issue numberAUGUST2015
DOIs
StatePublished - Aug 18 2015

ASJC Scopus subject areas

  • General Neuroscience
  • General Immunology and Microbiology
  • General Biochemistry, Genetics and Molecular Biology

Fingerprint

Dive into the research topics of 'Perturbation biology nominates upstream–downstream drug combinations in RAF inhibitor resistant melanoma cells'. Together they form a unique fingerprint.

Cite this