Genome-wide prediction of synthetic rescue mediators of resistance to targeted and immunotherapy

Avinash Das Sahu; Joo S Lee; Zhiyong Wang; Gao Zhang; Ramiro Iglesias-Bartolome; Tian Tian; Zhi Wei; Benchun Miao; Nishanth Ulhas Nair; Olga Ponomarova; Adam A. Friedman; Arnaud Amzallag; Tabea Moll; Gyulnara Kasumova; Patricia Greninger; Regina K. Egan; Leah J. Damon; Dennie T. Frederick; Livnat Jerby-Arnon; Allon Wagner; Kuoyuan Cheng; Seung Gu Park; Welles Robinson; Kevin Gardner; Genevieve Boland; Sridhar Hannenhalli; Meenhard Herlyn; Cyril Benes; Keith Flaherty; Ji Luo; J. Silvio Gutkind; Eytan Ruppin

doi:10.15252/msb.20188323

Genome-wide prediction of synthetic rescue mediators of resistance to targeted and immunotherapy

Avinash Das Sahu, Joo S Lee, Zhiyong Wang, Gao Zhang, Ramiro Iglesias-Bartolome, Tian Tian, Zhi Wei, Benchun Miao, Nishanth Ulhas Nair, Olga Ponomarova, Adam A. Friedman, Arnaud Amzallag, Tabea Moll, Gyulnara Kasumova, Patricia Greninger, Regina K. Egan, Leah J. Damon, Dennie T. Frederick, Livnat Jerby-Arnon, Allon WagnerKuoyuan Cheng, Seung Gu Park, Welles Robinson, Kevin Gardner, Genevieve Boland, Sridhar Hannenhalli, Meenhard Herlyn, Cyril Benes, Keith Flaherty, Ji Luo, J. Silvio Gutkind, Eytan Ruppin

Computer Science

Research output: Contribution to journal › Article › peer-review

20 Scopus citations

Abstract

Most patients with advanced cancer eventually acquire resistance to targeted therapies, spurring extensive efforts to identify molecular events mediating therapy resistance. Many of these events involve synthetic rescue (SR) interactions, where the reduction in cancer cell viability caused by targeted gene inactivation is rescued by an adaptive alteration of another gene (the rescuer). Here, we perform a genome-wide in silico prediction of SR rescuer genes by analyzing tumor transcriptomics and survival data of 10,000 TCGA cancer patients. Predicted SR interactions are validated in new experimental screens. We show that SR interactions can successfully predict cancer patients’ response and emerging resistance. Inhibiting predicted rescuer genes sensitizes resistant cancer cells to therapies synergistically, providing initial leads for developing combinatorial approaches to overcome resistance proactively. Finally, we show that the SR analysis of melanoma patients successfully identifies known mediators of resistance to immunotherapy and predicts novel rescuers.

Original language	English (US)
Article number	e8323
Journal	Molecular Systems Biology
Volume	15
Issue number	3
DOIs	https://doi.org/10.15252/msb.20188323
State	Published - Mar 2019

All Science Journal Classification (ASJC) codes

Information Systems
General Immunology and Microbiology
Applied Mathematics
General Biochemistry, Genetics and Molecular Biology
General Agricultural and Biological Sciences
Computational Theory and Mathematics

Keywords

drug combination
drug resistance
immunotherapy
synergy

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10.15252/msb.20188323

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Sahu, A. D., S Lee, J., Wang, Z., Zhang, G., Iglesias-Bartolome, R., Tian, T., Wei, Z., Miao, B., Nair, N. U., Ponomarova, O., Friedman, A. A., Amzallag, A., Moll, T., Kasumova, G., Greninger, P., Egan, R. K., Damon, L. J., Frederick, D. T., Jerby-Arnon, L., ... Ruppin, E. (2019). Genome-wide prediction of synthetic rescue mediators of resistance to targeted and immunotherapy. Molecular Systems Biology, 15(3), Article e8323. https://doi.org/10.15252/msb.20188323

@article{d93f3c2f801c4de8978d11c1a45da3f5,

title = "Genome-wide prediction of synthetic rescue mediators of resistance to targeted and immunotherapy",

abstract = "Most patients with advanced cancer eventually acquire resistance to targeted therapies, spurring extensive efforts to identify molecular events mediating therapy resistance. Many of these events involve synthetic rescue (SR) interactions, where the reduction in cancer cell viability caused by targeted gene inactivation is rescued by an adaptive alteration of another gene (the rescuer). Here, we perform a genome-wide in silico prediction of SR rescuer genes by analyzing tumor transcriptomics and survival data of 10,000 TCGA cancer patients. Predicted SR interactions are validated in new experimental screens. We show that SR interactions can successfully predict cancer patients{\textquoteright} response and emerging resistance. Inhibiting predicted rescuer genes sensitizes resistant cancer cells to therapies synergistically, providing initial leads for developing combinatorial approaches to overcome resistance proactively. Finally, we show that the SR analysis of melanoma patients successfully identifies known mediators of resistance to immunotherapy and predicts novel rescuers.",

keywords = "drug combination, drug resistance, immunotherapy, synergy",

author = "Sahu, {Avinash Das} and {S Lee}, Joo and Zhiyong Wang and Gao Zhang and Ramiro Iglesias-Bartolome and Tian Tian and Zhi Wei and Benchun Miao and Nair, {Nishanth Ulhas} and Olga Ponomarova and Friedman, {Adam A.} and Arnaud Amzallag and Tabea Moll and Gyulnara Kasumova and Patricia Greninger and Egan, {Regina K.} and Damon, {Leah J.} and Frederick, {Dennie T.} and Livnat Jerby-Arnon and Allon Wagner and Kuoyuan Cheng and Park, {Seung Gu} and Welles Robinson and Kevin Gardner and Genevieve Boland and Sridhar Hannenhalli and Meenhard Herlyn and Cyril Benes and Keith Flaherty and Ji Luo and Gutkind, {J. Silvio} and Eytan Ruppin",

note = "Publisher Copyright: {\textcopyright} 2019 The Authors. Published under the terms of the CC BY 4.0 license",

year = "2019",

month = mar,

doi = "10.15252/msb.20188323",

language = "English (US)",

volume = "15",

journal = "Molecular Systems Biology",

issn = "1744-4292",

publisher = "Nature Publishing Group",

number = "3",

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Sahu, AD, S Lee, J, Wang, Z, Zhang, G, Iglesias-Bartolome, R, Tian, T, Wei, Z, Miao, B, Nair, NU, Ponomarova, O, Friedman, AA, Amzallag, A, Moll, T, Kasumova, G, Greninger, P, Egan, RK, Damon, LJ, Frederick, DT, Jerby-Arnon, L, Wagner, A, Cheng, K, Park, SG, Robinson, W, Gardner, K, Boland, G, Hannenhalli, S, Herlyn, M, Benes, C, Flaherty, K, Luo, J, Gutkind, JS & Ruppin, E 2019, 'Genome-wide prediction of synthetic rescue mediators of resistance to targeted and immunotherapy', Molecular Systems Biology, vol. 15, no. 3, e8323. https://doi.org/10.15252/msb.20188323

TY - JOUR

T1 - Genome-wide prediction of synthetic rescue mediators of resistance to targeted and immunotherapy

AU - Sahu, Avinash Das

AU - S Lee, Joo

AU - Wang, Zhiyong

AU - Zhang, Gao

AU - Iglesias-Bartolome, Ramiro

AU - Tian, Tian

AU - Wei, Zhi

AU - Miao, Benchun

AU - Nair, Nishanth Ulhas

AU - Ponomarova, Olga

AU - Friedman, Adam A.

AU - Amzallag, Arnaud

AU - Moll, Tabea

AU - Kasumova, Gyulnara

AU - Greninger, Patricia

AU - Egan, Regina K.

AU - Damon, Leah J.

AU - Frederick, Dennie T.

AU - Jerby-Arnon, Livnat

AU - Wagner, Allon

AU - Cheng, Kuoyuan

AU - Park, Seung Gu

AU - Robinson, Welles

AU - Gardner, Kevin

AU - Boland, Genevieve

AU - Hannenhalli, Sridhar

AU - Herlyn, Meenhard

AU - Benes, Cyril

AU - Flaherty, Keith

AU - Luo, Ji

AU - Gutkind, J. Silvio

AU - Ruppin, Eytan

PY - 2019/3

Y1 - 2019/3

N2 - Most patients with advanced cancer eventually acquire resistance to targeted therapies, spurring extensive efforts to identify molecular events mediating therapy resistance. Many of these events involve synthetic rescue (SR) interactions, where the reduction in cancer cell viability caused by targeted gene inactivation is rescued by an adaptive alteration of another gene (the rescuer). Here, we perform a genome-wide in silico prediction of SR rescuer genes by analyzing tumor transcriptomics and survival data of 10,000 TCGA cancer patients. Predicted SR interactions are validated in new experimental screens. We show that SR interactions can successfully predict cancer patients’ response and emerging resistance. Inhibiting predicted rescuer genes sensitizes resistant cancer cells to therapies synergistically, providing initial leads for developing combinatorial approaches to overcome resistance proactively. Finally, we show that the SR analysis of melanoma patients successfully identifies known mediators of resistance to immunotherapy and predicts novel rescuers.

AB - Most patients with advanced cancer eventually acquire resistance to targeted therapies, spurring extensive efforts to identify molecular events mediating therapy resistance. Many of these events involve synthetic rescue (SR) interactions, where the reduction in cancer cell viability caused by targeted gene inactivation is rescued by an adaptive alteration of another gene (the rescuer). Here, we perform a genome-wide in silico prediction of SR rescuer genes by analyzing tumor transcriptomics and survival data of 10,000 TCGA cancer patients. Predicted SR interactions are validated in new experimental screens. We show that SR interactions can successfully predict cancer patients’ response and emerging resistance. Inhibiting predicted rescuer genes sensitizes resistant cancer cells to therapies synergistically, providing initial leads for developing combinatorial approaches to overcome resistance proactively. Finally, we show that the SR analysis of melanoma patients successfully identifies known mediators of resistance to immunotherapy and predicts novel rescuers.

KW - drug combination

KW - drug resistance

KW - immunotherapy

KW - synergy

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UR - http://www.scopus.com/inward/citedby.url?scp=85062892216&partnerID=8YFLogxK

U2 - 10.15252/msb.20188323

DO - 10.15252/msb.20188323

M3 - Article

C2 - 30858180

AN - SCOPUS:85062892216

SN - 1744-4292

VL - 15

JO - Molecular Systems Biology

JF - Molecular Systems Biology

IS - 3

M1 - e8323

ER -

Genome-wide prediction of synthetic rescue mediators of resistance to targeted and immunotherapy

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All Science Journal Classification (ASJC) codes

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