한빛사 논문
Sanju Sinha1,2,3,9, Karina Barbosa4,9, Kuoyuan Cheng1,3,9, Mark D. M. Leiserson3, Prashant Jain4, Anagha Deshpande4, David M. Wilson III5, Bríd M. Ryan2, Ji Luo6, Ze’ev A. Ronai4, Joo Sang Lee7,8,10, Aniruddha J. Deshpande4,10 & Eytan Ruppin1,10,*
1 Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. 2 Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20850, USA. 3 Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA. 4 Tumor Initiation Program, Cancer Center, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA 92037, USA. 5 Laboratory of Molecular Gerontology, National Institute on Aging, Intramural Research Program, National Institutes of Health, Baltimore, MD 21224, USA. 6 Laboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, National Institute of Health, Bethesda, MD 20850, USA. 7 Samsung Medical Center, Sungkyunkwan University School of Medicine, Suwon 16419, Republic of Korea. 8Department of Precision Medicine, School of Medicine and Department of Artificial Intelligence, Sungkyunkwan University, Suwon 16419, Republic of Korea. 9 These authors contributed equally: Sanju Sinha, Karina Barbosa, Kuoyuan Cheng. 10These authors jointly supervised this work: Joo Sang Lee, Aniruddha J. Deshpande, Eytan Ruppin.
*Corresponding author.
Abstract
Recent studies have reported that genome editing by CRISPR–Cas9 induces a DNA damage response mediated by p53 in primary cells hampering their growth. This could lead to a selection of cells with pre-existing p53 mutations. In this study, employing an integrated computational and experimental framework, we systematically investigated the possibility of selection of additional cancer driver mutations during CRISPR-Cas9 gene editing. We first confirm the previous findings of the selection for pre-existing p53 mutations by CRISPR-Cas9. We next demonstrate that similar to p53, wildtype KRAS may also hamper the growth of Cas9-edited cells, potentially conferring a selective advantage to pre-existing KRAS-mutant cells. These selective effects are widespread, extending across cell-types and methods of CRISPR-Cas9 delivery and the strength of selection depends on the sgRNA sequence and the gene being edited. The selection for pre-existing p53 or KRAS mutations may confound CRISPR-Cas9 screens in cancer cells and more importantly, calls for monitoring patients undergoing CRISPR-Cas9-based editing for clinical therapeutics for pre-existing p53 and KRAS mutations.
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