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Integrated computational and experimental identification of p53, KRAS and VHL mutant selection associated with CRISPR-Cas9 editing

Sanju Sinha, Karina Barbosa Guerra, View ORCID ProfileKuoyuan Cheng, Mark DM Leiserson, David M Wilson III, Bríd M. Ryan, Ze’ev A. Ronai, Joo Sang Lee, Aniruddha J. Deshpande, Eytan Ruppin
doi: https://doi.org/10.1101/407767
Sanju Sinha
1Cancer Data Science Lab, Center for Cancer Research, National Cancer Institute, National Institute of Health, Bethesda, MD 20892, USA
2Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, National Institute of Health, Bethesda, MD 20850, USA
3Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA
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Karina Barbosa Guerra
4Tumor Initiation Program, Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA 92037, USA
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Kuoyuan Cheng
1Cancer Data Science Lab, Center for Cancer Research, National Cancer Institute, National Institute of Health, Bethesda, MD 20892, USA
3Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA
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Mark DM Leiserson
3Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA
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David M Wilson III
5Laboratory of Molecular Gerontology, National Institute on Aging, Intramural Research Program, National Institutes of Health, Baltimore, MD 21224, USA
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Bríd M. Ryan
2Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, National Institute of Health, Bethesda, MD 20850, USA
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Ze’ev A. Ronai
4Tumor Initiation Program, Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA 92037, USA
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Joo Sang Lee
6Samsung Medical Center, Sungkyunkwan University School of Medicine, Suwon 16419, Republic of Korea
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  • For correspondence: eytan.ruppin@nih.gov
Aniruddha J. Deshpande
4Tumor Initiation Program, Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA 92037, USA
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  • For correspondence: eytan.ruppin@nih.gov
Eytan Ruppin
1Cancer Data Science Lab, Center for Cancer Research, National Cancer Institute, National Institute of Health, Bethesda, MD 20892, USA
3Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA
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  • For correspondence: eytan.ruppin@nih.gov
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Abstract

Recent studies have reported that CRISPR-Cas9 gene editing induces a p53-dependent DNA damage response in primary cells, which may select for cells with oncogenic p53 mutations11,12. It is unclear whether these CRISPR-induced changes are applicable to different cell types, and whether CRISPR gene editing may select for other oncogenic mutations. Addressing these questions, we analyzed genome-wide CRISPR and RNAi screens to systematically chart the mutation selection potential of CRISPR knockouts across the whole exome. Our analysis suggests that CRISPR gene editing can select for mutants of KRAS and VHL, at a level comparable to that reported for p53. These predictions were further validated in a genome-wide manner by analyzing independent CRISPR screens and patients’ tumor data. Finally, we performed a new set of pooled and arrayed CRISPR screens to evaluate the competition between CRISPR-edited isogenic p53 WT and mutant cell lines, which further validated our predictions. In summary, our study systematically charts and points to the potential selection of specific cancer driver mutations during CRISPR-Cas9 gene editing.

Footnotes

  • ↵# Co-first author

  • We validated our previous findings in a genome-wide manner by analyzing independent CRISPR screens and performed a new set of pooled and arrayed CRISPR screens to evaluate the competition between CRISPR-edited isogenic p53 WT and mutant cell lines.

  • https://github.com/ruppinlab/crispr_risk.git

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted November 02, 2019.
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Integrated computational and experimental identification of p53, KRAS and VHL mutant selection associated with CRISPR-Cas9 editing
Sanju Sinha, Karina Barbosa Guerra, Kuoyuan Cheng, Mark DM Leiserson, David M Wilson III, Bríd M. Ryan, Ze’ev A. Ronai, Joo Sang Lee, Aniruddha J. Deshpande, Eytan Ruppin
bioRxiv 407767; doi: https://doi.org/10.1101/407767
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Integrated computational and experimental identification of p53, KRAS and VHL mutant selection associated with CRISPR-Cas9 editing
Sanju Sinha, Karina Barbosa Guerra, Kuoyuan Cheng, Mark DM Leiserson, David M Wilson III, Bríd M. Ryan, Ze’ev A. Ronai, Joo Sang Lee, Aniruddha J. Deshpande, Eytan Ruppin
bioRxiv 407767; doi: https://doi.org/10.1101/407767

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