Abstract 3039: Combinatorial CRISPR-Cas9 gene knockout to enable genetic interaction mapping in human cells
Authors: Shen John Paul , Zhao Dongxin , Sasik Roman , Luebeck Jens , Bojorquez-Gomez Ana , Licon Katherine , Ideker Trey , Mali Prashant 
Published: July 2017

Genetic interactions, in particular negative or ‘synthetic-lethal’ interactions for which simultaneous disruption of two genes causes cell killing, have implications for therapeutic development. The feasibility of this approach has been demonstrated with the recent approval of the drug olaparib, an inhibitor of PARP1, specifically for tumors with loss-of-function mutations in BRCA1/2. However, beyond olaparib, further applications of synthetic-lethal cancer therapy have been limited by poor understanding of the important genetic interactions in a cancer cell, and how these vary from one cancer type to another or from patient to patient. To enable systematic mapping of these genetic interaction networks, we developed a CRISPR-Cas9 screening methodology for knocking out single and pairs of genes in high-throughput. Here, we combined multiplex targeting with array-based oligonucleotide synthesis to create dual-gRNA libraries covering up to 10^5 defined gene pairs. In these libraries, each construct bears two gRNAs, with each gRNA designed to target either a gene or a scrambled non-targeting sequence absent from the genome. We conducted genetic interaction screens by transducing the dual-gRNA lentiviral library into a population of cells stably expressing Cas9, maintaining these cells in exponential growth over the course of four weeks, then sampling the relative changes in gRNAs at days 3, 14, 21 and 28 post-transduction. To robustly quantify gene fitness and genetic interactions, we developed a computational analysis framework that integrates all samples across the multiple days of the experiment. Using this method we evaluated all pairwise gene knockout combinations among a panel of 73 genes divided between tumor-suppressor genes (TSG) and cancer-relevant drug targets (DT); including negative controls this amounted to a total of 23,652 combinations. Experiments were performed in three cancer cell lines: HeLa, A549 and 293T. In total 162 therapeutically relevant interactions were identified, of which 146 (90.1%) were private to one cell line. None of the interactions were observed in all three cell lines. These patterns replicated in low throughput assays with combinatorial drugs at 80% precision. In summary, we have introduced a combinatorial CRISPR-Cas9 genetic interaction mapping technology that successfully identifies many therapeutically-relevant genetic interactions in cancer and shows the great importance of cellular context on the architecture of the genetic interaction network. Recognizing that there will be great diversity in genetic interaction between different tumors it will be important to perform future studies across a large number of samples, which is enabled by the high-throughput method we have developed.

Citation Format: John Paul Shen, Dongxin Zhao, Roman Sasik, Jens Luebeck, Ana Bojorquez-Gomez, Katherine Licon, Trey Ideker, Prashant Mali. Combinatorial CRISPR-Cas9 gene knockout to enable genetic interaction mapping in human cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3039. doi:10.1158/1538-7445.AM2017-3039