Deep CRISPR mutagenesis characterizes the functional diversity of TP53 mutations

Julianne Funk(Philipps University of Marburg), Maria Klimovich(Philipps University of Marburg), Daniel Drangenstein(Philipps University of Marburg), Ole Pielhoop(Philipps University of Marburg), Pascal Hunold(Philipps University of Marburg), Anna Borowek(Philipps University of Marburg), Amir Noeparast(Philipps University of Marburg), Evangelos Pavlakis(Philipps University of Marburg), Michelle M. Neumann(Philipps University of Marburg), Dimitrios-Ilias Balourdas(Goethe University Frankfurt), Katharina Kochhan(Philipps University of Marburg), Nastasja Merle(Philipps University of Marburg), Imke Bullwinkel(Philipps University of Marburg), Michael Wanzel(Philipps University of Marburg), Sabrina Elmshäuser(Philipps University of Marburg), Julia Teply‐Szymanski(Philipps University of Marburg), Andrea Nist(Philipps University of Marburg), Tara Procida(Justus-Liebig-Universität Gießen), Marek Bartkuhn(Justus-Liebig-Universität Gießen), Katharina Humpert(Philipps University of Marburg), Marco Mernberger(Philipps University of Marburg), Rajkumar Savai(Justus-Liebig-Universität Gießen), Thierry Soussi(Uppsala University Hospital), Andreas C. Joerger(Goethe University Frankfurt), Thorsten Stiewe(Philipps University of Marburg)
Nature Genetics
January 1, 2025
Cited by 72Open Access
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Abstract

The mutational landscape of TP53, a tumor suppressor mutated in about half of all cancers, includes over 2,000 known missense mutations. To fully leverage TP53 mutation status for personalized medicine, a thorough understanding of the functional diversity of these mutations is essential. We conducted a deep mutational scan using saturation genome editing with CRISPR-mediated homology-directed repair to engineer 9,225 TP53 variants in cancer cells. This high-resolution approach, covering 94.5% of all cancer-associated TP53 missense mutations, precisely mapped the impact of individual mutations on tumor cell fitness, surpassing previous deep mutational scan studies in distinguishing benign from pathogenic variants. Our results revealed even subtle loss-of-function phenotypes and identified promising mutants for pharmacological reactivation. Moreover, we uncovered the roles of splicing alterations and nonsense-mediated messenger RNA decay in mutation-driven TP53 dysfunction. These findings underscore the power of saturation genome editing in advancing clinical TP53 variant interpretation for genetic counseling and personalized cancer therapy.


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