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

Elife. 2015 Aug 18;4:e04640. doi: 10.7554/eLife.04640.


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.

Keywords: cancer drug resistance; cell biology; cellular signaling; computational biology; drug synergy; human; melanoma; network modeling; proteomics; systems biology.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antineoplastic Agents / pharmacology*
  • Cell Line, Tumor
  • Computational Biology / methods*
  • Cytological Techniques / methods*
  • Drug Combinations
  • Drug Resistance*
  • Gene Regulatory Networks
  • Humans
  • Melanoma / drug therapy*
  • Models, Biological
  • Models, Theoretical
  • raf Kinases / antagonists & inhibitors


  • Antineoplastic Agents
  • Drug Combinations
  • raf Kinases