한빛사 논문
Younggwang Kim1,2,9, Seungho Lee1,9, Soohyuk Cho1,2, Jinman Park1,2, Dongwoo Chae1, Taeyoung Park3, John D. Minna4 and Hyongbum Henry Kim 1,2,5,6,7,8,*
1Department of Pharmacology, Yonsei University College of Medicine, Seoul, Republic of Korea. 2Graduate School of Medical Science, Brain Korea 21 Plus Project for Medical Sciences, Yonsei University College of Medicine, Seoul, Republic of Korea. 3Department of Applied Statistics, Yonsei University, Seoul, Republic of Korea. 4Hamon Center for Therapeutic Oncology Research, University of Texas Southwestern Medical Center, Dallas, TX, USA. 5Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, Republic of Korea. 6Center for Nanomedicine, Institute for Basic Science (IBS), Seoul, Republic of Korea. 7Yonsei-IBS Institute, Yonsei University, Seoul, Republic of Korea. 8Institute for Immunology and Immunological Diseases, Yonsei University College of Medicine, Seoul, Republic of Korea. 9These authors contributed equally: Younggwang Kim, Seungho Lee.
*Corresponding author.
Abstract
Comprehensive phenotypic characterization of the many mutations found in cancer tissues is one of the biggest challenges in cancer genomics. In this study, we evaluated the functional effects of 29,060 cancer-related transition mutations that result in protein variants on the survival and proliferation of non-tumorigenic lung cells using cytosine and adenine base editors and single guide RNA (sgRNA) libraries. By monitoring base editing efficiencies and outcomes using surrogate target sequences paired with sgRNA-encoding sequences on the lentiviral delivery construct, we identified sgRNAs that induced a single primary protein variant per sgRNA, enabling linking those mutations to the cellular phenotypes caused by base editing. The functions of the vast majority of the protein variants (28,458 variants, 98%) were classified as neutral or likely neutral; only 18 (0.06%) and 157 (0.5%) variants caused outgrowing and likely outgrowing phenotypes, respectively. We expect that our approach can be extended to more variants of unknown significance and other tumor types.
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