CRISPR knockout screening identifies combinatorial drug targets in pancreatic cancer and models cellular drug response. Issue 1 (December 2018)

• Record Type: Journal Article
• Authors: Szlachta, Karol; Kuscu, Cem; Tufan, Turan; Adair, Sara; Shang, Stephen; Michaels, Alex; Mullen, Matthew; Fischer, Natasha; Yang, Jiekun; Liu, Limin; Trivedi, Prasad; Stelow, Edward; Stukenberg, P.; Parsons, J.; Bauer, Todd; Adli, Mazhar
• Is Part Of: Nature communications. Volume 9:Issue 1(2018)
• Page Start: 1
• Page End: 13
• Publication Date: 2018-12
• Subjects: Biology -- Periodicals; Physical sciences -- Periodicals; 505
• DOI: 10.1038/s41467-018-06676-2
• Languages: English
• ISSNs: 2041-1723

Abstract

Abstract Predicting the response and identifying additional targets that will improve the efficacy of chemotherapy is a major goal in cancer research. Through large-scale in vivo and in vitro CRISPR knockout screens in pancreatic ductal adenocarcinoma cells, we identified genes whose genetic deletion or pharmacologic inhibition synergistically increase the cytotoxicity of MEK signaling inhibitors. Furthermore, we show that CRISPR viability scores combined with basal gene expression levels could model global cellular responses to the drug treatment. We develop drug response evaluation by in vivo CRISPR screening (DREBIC) method and validated its efficacy using large-scale experimental data from independent experiments. Comparative analyses demonstrate that DREBIC predicts drug response in cancer cells from a wide range of tissues with high accuracy and identifies therapeutic vulnerabilities of cancer-causing mutations to MEK inhibitors in various cancer types. Predicting the response to chemotherapy is a major goal of cancer research. Here the authors use CRISPR knockout screens in pancreatic ductal adenocarcinoma cells to identify deletions synergistic with MEK inhibitors.