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

Karol Szlachta; Cem Kuscu; Turan Tufan; Sara J. Adair; Stephen Shang; Alex D. Michaels; Matthew G. Mullen; Natasha Lopes Fischer; Jiekun Yang; Limin Liu; Prasad Trivedi; Edward B. Stelow; P. Todd Stukenberg; J. Thomas Parsons; Todd W. Bauer; Mazhar Adli

doi:10.1038/s41467-018-06676-2

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

Karol Szlachta, Cem Kuscu, Turan Tufan, Sara J. Adair, Stephen Shang, Alex D. Michaels, Matthew G. Mullen, Natasha Lopes Fischer, Jiekun Yang, Limin Liu, Prasad Trivedi, Edward B. Stelow, P. Todd Stukenberg, J. Thomas Parsons, Todd W. Bauer, Mazhar Adli^*

^*Corresponding author for this work

Obstetrics and Gynecology

Research output: Contribution to journal › Article › peer-review

50 Scopus citations

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.

Original language	English (US)
Article number	4275
Journal	Nature communications
Volume	9
Issue number	1
DOIs	https://doi.org/10.1038/s41467-018-06676-2
State	Published - Dec 1 2018

ASJC Scopus subject areas

General Chemistry
General Biochemistry, Genetics and Molecular Biology
General Physics and Astronomy

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1038/s41467-018-06676-2

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Szlachta, K., Kuscu, C., Tufan, T., Adair, S. J., Shang, S., Michaels, A. D., Mullen, M. G., Fischer, N. L., Yang, J., Liu, L., Trivedi, P., Stelow, E. B., Stukenberg, P. T., Parsons, J. T., Bauer, T. W., & Adli, M. (2018). CRISPR knockout screening identifies combinatorial drug targets in pancreatic cancer and models cellular drug response. Nature communications, 9(1), Article 4275. https://doi.org/10.1038/s41467-018-06676-2

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title = "CRISPR knockout screening identifies combinatorial drug targets in pancreatic cancer and models cellular drug response",

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.",

author = "Karol Szlachta and Cem Kuscu and Turan Tufan and Adair, {Sara J.} and Stephen Shang and Michaels, {Alex D.} and Mullen, {Matthew G.} and Fischer, {Natasha Lopes} and Jiekun Yang and Limin Liu and Prasad Trivedi and Stelow, {Edward B.} and Stukenberg, {P. Todd} and Parsons, {J. Thomas} and Bauer, {Todd W.} and Mazhar Adli",

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doi = "10.1038/s41467-018-06676-2",

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Szlachta, K, Kuscu, C, Tufan, T, Adair, SJ, Shang, S, Michaels, AD, Mullen, MG, Fischer, NL, Yang, J, Liu, L, Trivedi, P, Stelow, EB, Stukenberg, PT, Parsons, JT, Bauer, TW & Adli, M 2018, 'CRISPR knockout screening identifies combinatorial drug targets in pancreatic cancer and models cellular drug response', Nature communications, vol. 9, no. 1, 4275. https://doi.org/10.1038/s41467-018-06676-2

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AU - Szlachta, Karol

AU - Kuscu, Cem

AU - Tufan, Turan

AU - Adair, Sara J.

AU - Shang, Stephen

AU - Michaels, Alex D.

AU - Mullen, Matthew G.

AU - Fischer, Natasha Lopes

AU - Yang, Jiekun

AU - Liu, Limin

AU - Trivedi, Prasad

AU - Stelow, Edward B.

AU - Stukenberg, P. Todd

AU - Parsons, J. Thomas

AU - Bauer, Todd W.

AU - Adli, Mazhar

PY - 2018/12/1

Y1 - 2018/12/1

N2 - 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.

AB - 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.

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

Abstract

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