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 Pratilas, Chris Sander

Research output: Contribution to journalArticle

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

Fingerprint

Drug Combinations
Melanoma
Proto-Oncogene Proteins c-myc
MAP Kinase Signaling System
Mitogen-Activated Protein Kinase Kinases
Protein Kinase Inhibitors
Computational Biology
Proteomics
Neoplasms
Throughput
Therapeutics
Pharmaceutical Preparations
Experiments

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Medicine(all)
  • Neuroscience(all)

Cite this

Korkut, A., Wang, W., Demir, E., Aksoy, B. A., Jing, X., Molinelli, E. J., ... Sander, C. (2015). Perturbation biology nominates upstream–downstream drug combinations in RAF inhibitor resistant melanoma cells. eLife, 4(AUGUST2015), [e04640]. https://doi.org/10.7554/eLife.04640

Perturbation biology nominates upstream–downstream drug combinations in RAF inhibitor resistant melanoma cells. / Korkut, Anil; Wang, Weiqing; Demir, Emek; Aksoy, Bulent Arman; Jing, Xiaohong; Molinelli, Evan J.; Babur, Özgün; Bemis, Debra L.; Sumer, Selcuk Onur; Solit, David B.; Pratilas, Christine; Sander, Chris.

In: eLife, Vol. 4, No. AUGUST2015, e04640, 18.08.2015.

Research output: Contribution to journalArticle

Korkut, A, Wang, W, Demir, E, Aksoy, BA, Jing, X, Molinelli, EJ, Babur, Ö, Bemis, DL, Sumer, SO, Solit, DB, Pratilas, C & Sander, C 2015, 'Perturbation biology nominates upstream–downstream drug combinations in RAF inhibitor resistant melanoma cells', eLife, vol. 4, no. AUGUST2015, e04640. https://doi.org/10.7554/eLife.04640
Korkut A, Wang W, Demir E, Aksoy BA, Jing X, Molinelli EJ et al. Perturbation biology nominates upstream–downstream drug combinations in RAF inhibitor resistant melanoma cells. eLife. 2015 Aug 18;4(AUGUST2015). e04640. https://doi.org/10.7554/eLife.04640
Korkut, Anil ; Wang, Weiqing ; Demir, Emek ; Aksoy, Bulent Arman ; Jing, Xiaohong ; Molinelli, Evan J. ; Babur, Özgün ; Bemis, Debra L. ; Sumer, Selcuk Onur ; Solit, David B. ; Pratilas, Christine ; Sander, Chris. / Perturbation biology nominates upstream–downstream drug combinations in RAF inhibitor resistant melanoma cells. In: eLife. 2015 ; Vol. 4, No. AUGUST2015.
@article{344db020f78f48f6a6f18369ba9d54fa,
title = "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.",
author = "Anil Korkut and Weiqing Wang and Emek Demir and Aksoy, {Bulent Arman} and Xiaohong Jing and Molinelli, {Evan J.} and {\"O}zg{\"u}n Babur and Bemis, {Debra L.} and Sumer, {Selcuk Onur} and Solit, {David B.} and Christine Pratilas and Chris Sander",
year = "2015",
month = "8",
day = "18",
doi = "10.7554/eLife.04640",
language = "English (US)",
volume = "4",
journal = "eLife",
issn = "2050-084X",
publisher = "eLife Sciences Publications",
number = "AUGUST2015",

}

TY - JOUR

T1 - Perturbation biology nominates upstream–downstream drug combinations in RAF inhibitor resistant melanoma cells

AU - Korkut, Anil

AU - Wang, Weiqing

AU - Demir, Emek

AU - Aksoy, Bulent Arman

AU - Jing, Xiaohong

AU - Molinelli, Evan J.

AU - Babur, Özgün

AU - Bemis, Debra L.

AU - Sumer, Selcuk Onur

AU - Solit, David B.

AU - Pratilas, Christine

AU - Sander, Chris

PY - 2015/8/18

Y1 - 2015/8/18

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84940527513&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84940527513&partnerID=8YFLogxK

U2 - 10.7554/eLife.04640

DO - 10.7554/eLife.04640

M3 - Article

VL - 4

JO - eLife

JF - eLife

SN - 2050-084X

IS - AUGUST2015

M1 - e04640

ER -