Literature DB >> 35737245

Using CRISPR-Cas9 to Dissect Cancer Mutations in Cell Lines.

Shady Sayed1, Duran Sürün1, Jovan Mircetic1, Olga Alexandra Sidorova1, Frank Buchholz2,3,4.   

Abstract

The CRISPR-Cas9 technology has revolutionized the scope and pace of biomedical research, enabling the targeting of specific genomic sequences for a wide spectrum of applications. Here we describe assays to functionally interrogate mutations identified in cancer cells utilizing both CRISPR-Cas9 nuclease and base editors. We provide guidelines to interrogate known cancer driver mutations or functionally screen for novel vulnerability mutations with these systems in characterized human cancer cell lines. The proposed platform should be transferable to primary cancer cells, opening up a path for precision oncology on a functional level.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  CRISPR-Cas9; Cancer cell lines; Mutations

Mesh:

Year:  2022        PMID: 35737245     DOI: 10.1007/978-1-0716-2376-3_18

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  31 in total

Review 1.  Somatic mutation in cancer and normal cells.

Authors:  Iñigo Martincorena; Peter J Campbell
Journal:  Science       Date:  2015-09-24       Impact factor: 47.728

2.  Identification of cancer driver genes based on nucleotide context.

Authors:  Felix Dietlein; Donate Weghorn; Amaro Taylor-Weiner; André Richters; Brendan Reardon; David Liu; Eric S Lander; Eliezer M Van Allen; Shamil R Sunyaev
Journal:  Nat Genet       Date:  2020-02-03       Impact factor: 38.330

Review 3.  The cancer genome.

Authors:  Michael R Stratton; Peter J Campbell; P Andrew Futreal
Journal:  Nature       Date:  2009-04-09       Impact factor: 49.962

4.  Bayesian inference of negative and positive selection in human cancers.

Authors:  Donate Weghorn; Shamil Sunyaev
Journal:  Nat Genet       Date:  2017-11-06       Impact factor: 38.330

5.  Selective disruption of an oncogenic mutant allele by CRISPR/Cas9 induces efficient tumor regression.

Authors:  Taeyoung Koo; A-Rum Yoon; Hee-Yeon Cho; Sangsu Bae; Chae-Ok Yun; Jin-Soo Kim
Journal:  Nucleic Acids Res       Date:  2017-07-27       Impact factor: 16.971

6.  Universal Patterns of Selection in Cancer and Somatic Tissues.

Authors:  Iñigo Martincorena; Keiran M Raine; Moritz Gerstung; Kevin J Dawson; Kerstin Haase; Peter Van Loo; Helen Davies; Michael R Stratton; Peter J Campbell
Journal:  Cell       Date:  2017-10-19       Impact factor: 41.582

7.  Functional impact bias reveals cancer drivers.

Authors:  Abel Gonzalez-Perez; Nuria Lopez-Bigas
Journal:  Nucleic Acids Res       Date:  2012-08-16       Impact factor: 16.971

8.  Assessment of computational methods for predicting the effects of missense mutations in human cancers.

Authors:  Florian Gnad; Albion Baucom; Kiran Mukhyala; Gerard Manning; Zemin Zhang
Journal:  BMC Genomics       Date:  2013-05-28       Impact factor: 3.969

9.  Mutational heterogeneity in cancer and the search for new cancer-associated genes.

Authors:  Michael S Lawrence; Petar Stojanov; Paz Polak; Gregory V Kryukov; Kristian Cibulskis; Andrey Sivachenko; Scott L Carter; Chip Stewart; Craig H Mermel; Steven A Roberts; Adam Kiezun; Peter S Hammerman; Aaron McKenna; Yotam Drier; Lihua Zou; Alex H Ramos; Trevor J Pugh; Nicolas Stransky; Elena Helman; Jaegil Kim; Carrie Sougnez; Lauren Ambrogio; Elizabeth Nickerson; Erica Shefler; Maria L Cortés; Daniel Auclair; Gordon Saksena; Douglas Voet; Michael Noble; Daniel DiCara; Pei Lin; Lee Lichtenstein; David I Heiman; Timothy Fennell; Marcin Imielinski; Bryan Hernandez; Eran Hodis; Sylvan Baca; Austin M Dulak; Jens Lohr; Dan-Avi Landau; Catherine J Wu; Jorge Melendez-Zajgla; Alfredo Hidalgo-Miranda; Amnon Koren; Steven A McCarroll; Jaume Mora; Brian Crompton; Robert Onofrio; Melissa Parkin; Wendy Winckler; Kristin Ardlie; Stacey B Gabriel; Charles W M Roberts; Jaclyn A Biegel; Kimberly Stegmaier; Adam J Bass; Levi A Garraway; Matthew Meyerson; Todd R Golub; Dmitry A Gordenin; Shamil Sunyaev; Eric S Lander; Gad Getz
Journal:  Nature       Date:  2013-06-16       Impact factor: 49.962

10.  OncodriveFML: a general framework to identify coding and non-coding regions with cancer driver mutations.

Authors:  Loris Mularoni; Radhakrishnan Sabarinathan; Jordi Deu-Pons; Abel Gonzalez-Perez; Núria López-Bigas
Journal:  Genome Biol       Date:  2016-06-16       Impact factor: 13.583

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