RT Journal Article
SR Electronic
T1 Genome-wide prediction of synthetic rescue mediators of resistance to targeted and immunotherapy
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 284240
DO 10.1101/284240
A1 Avinash Das
A1 Joo Sang Lee
A1 Gao Zhang
A1 Zhiyong Wang
A1 Ramiro Iglesias-Bartolome
A1 Tian Tian
A1 Zhi Wei
A1 Benchun Miao
A1 Nishanth Ulhas Nair
A1 Olga Ponomarova
A1 Adam A. Friedman
A1 Arnaud Amzallag
A1 Tabea Moll
A1 Gyulnara Kasumova
A1 Patricia Greninger
A1 Regina K. Egan
A1 Leah J. Damon
A1 Dennie T. Frederick
A1 Allon Wagner
A1 Kuoyuan Cheng
A1 Seung Gu Park
A1 Welles Robinson
A1 Kevin Gardner
A1 Genevieve Boland
A1 Sridhar Hannenhalli
A1 Meenhard Herlyn
A1 Cyril Benes
A1 J. Silvio Gutkind
A1 Keith Flaherty
A1 Eytan Ruppin
YR 2018
UL http://biorxiv.org/content/early/2018/04/08/284240.abstract
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 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.