Perturbation biology nominates upstream-downstream drug combinations in RAF inhibitor resistant melanoma cells. Academic Article uri icon

Overview

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.

publication date

  • August 18, 2015

Research

keywords

  • Antineoplastic Agents
  • Computational Biology
  • Cytological Techniques
  • Drug Resistance
  • Melanoma

Identity

PubMed Central ID

  • PMC4539601

Scopus Document Identifier

  • 84940527513

Digital Object Identifier (DOI)

  • 10.1073/pnas.1323934111

PubMed ID

  • 26284497

Additional Document Info

volume

  • 4