2. Academic Validation
  3. CRISPR knockout screening identifies combinatorial drug targets in pancreatic cancer and models cellular drug response

CRISPR knockout screening identifies combinatorial drug targets in pancreatic cancer and models cellular drug response

  • Nat Commun. 2018 Oct 15;9(1):4275. doi: 10.1038/s41467-018-06676-2.
Karol Szlachta  # 1,  Cem Kuscu  # 1,  Turan Tufan  # 1,  Sara J Adair 2,  Stephen Shang 1,  Alex D Michaels 2,  Matthew G Mullen 2,  Natasha Lopes Fischer 1,  Jiekun Yang 1,  Limin Liu 1,  Prasad Trivedi 1,  Edward B Stelow 3,  P Todd Stukenberg 1,  J Thomas Parsons 4,  Todd W Bauer 2,  Mazhar Adli 5
Affiliations

Affiliations

  • 1 Department of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, 1340 JPA, Pinn Hall, Charlottesville, VA, 22908, USA.
  • 2 Department of Surgery, University of Virginia School of Medicine, 1215 Lee St, Charlottesville, VA, 22908, USA.
  • 3 Department of Pathology, University of Virginia School of Medicine, Charlottesville, 1215 Lee St, Charlottesville, VA, 22908, USA.
  • 4 Department of Microbiology, Immunology, and Cancer Biology, University of Virginia School of Medicine, 1340 JPA, Pinn Hall, Charlottesville, VA, 22908, USA.
  • 5 Department of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, 1340 JPA, Pinn Hall, Charlottesville, VA, 22908, USA. adli@virginia.edu.
  • # Contributed equally.
PMID: 30323222 DOI: 10.1038/s41467-018-06676-2
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.

Figures
Products