Σφακιανάκης Αλέξανδρος
ΩτοΡινοΛαρυγγολόγος
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Τετάρτη 26 Ιουλίου 2017

A Landscape of Therapeutic Cooperativity in KRAS Mutant Cancers Reveals Principles for Controlling Tumor Evolution

Publication date: 25 July 2017
Source:Cell Reports, Volume 20, Issue 4
Author(s): Grace R. Anderson, Peter S. Winter, Kevin H. Lin, Daniel P. Nussbaum, Merve Cakir, Elizabeth M. Stein, Ryan S. Soderquist, Lorin Crawford, Jim C. Leeds, Rachel Newcomb, Priya Stepp, Catherine Yip, Suzanne E. Wardell, Jennifer P. Tingley, Moiez Ali, Mengmeng Xu, Meagan Ryan, Shannon J. McCall, Autumn J. McRee, Christopher M. Counter, Channing J. Der, Kris C. Wood
Combinatorial inhibition of effector and feedback pathways is a promising treatment strategy for KRAS mutant cancers. However, the particular pathways that should be targeted to optimize therapeutic responses are unclear. Using CRISPR/Cas9, we systematically mapped the pathways whose inhibition cooperates with drugs targeting the KRAS effectors MEK, ERK, and PI3K. By performing 70 screens in models of KRAS mutant colorectal, lung, ovarian, and pancreas cancers, we uncovered universal and tissue-specific sensitizing combinations involving inhibitors of cell cycle, metabolism, growth signaling, chromatin regulation, and transcription. Furthermore, these screens revealed secondary genetic modifiers of sensitivity, yielding a SRC inhibitor-based combination therapy for KRAS/PIK3CA double-mutant colorectal cancers (CRCs) with clinical potential. Surprisingly, acquired resistance to combinations of growth signaling pathway inhibitors develops rapidly following treatment, but by targeting signaling feedback or apoptotic priming, it is possible to construct three-drug combinations that greatly delay its emergence.

Graphical abstract

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Teaser

Anderson et al. develop a screening approach to rapidly uncover potent and durable combination therapies in KRAS-driven cancers. This scalable approach can be applied to diverse cancer types for the discovery of potent treatment strategies. Furthermore, they describe rational methods to engineer higher-order therapies to control tumor evolution.


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