Identification and functional characterization of new missense SNPs in the coding region of the TP53 gene

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Publikace nespadá pod Ekonomicko-správní fakultu, ale pod Středoevropský technologický institut. Oficiální stránka publikace je na webu muni.cz.
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DOFFE Flora CARBONNIER Vincent TISSIER Manon LEROY Bernard MARTINS Isabelle MATTSSON Johanna S. M. MICKE Patrick PAVLOVÁ Šárka POSPÍŠILOVÁ Šárka ŠMARDOVÁ Jana JOERGER Andreas C. WIMAN Klas G. KROEMER Guido SOUSSI Thierry

Rok publikování 2021
Druh Článek v odborném periodiku
Časopis / Zdroj Cell Death and Differentiation
Fakulta / Pracoviště MU

Středoevropský technologický institut

Citace
www https://doi.org/10.1038/s41418-020-00672-0
Doi http://dx.doi.org/10.1038/s41418-020-00672-0
Klíčová slova Genetics research; Tumour-suppressor proteins
Popis Infrequent and rare genetic variants in the human population vastly outnumber common ones. Although they may contribute significantly to the genetic basis of a disease, these seldom-encountered variants may also be miss-identified as pathogenic if no correct references are available. Somatic and germline TP53 variants are associated with multiple neoplastic diseases, and thus have come to serve as a paradigm for genetic analyses in this setting. We searched 14 independent, globally distributed datasets and recovered TP53 SNPs from 202,767 cancer-free individuals. In our analyses, 19 new missense TP53 SNPs, including five novel variants specific to the Asian population, were recurrently identified in multiple datasets. Using a combination of in silico, functional, structural, and genetic approaches, we showed that none of these variants displayed loss of function compared to the normal TP53 gene. In addition, classification using ACMG criteria suggested that they are all benign. Considered together, our data reveal that the TP53 coding region shows far more polymorphism than previously thought and present high ethnic diversity. They furthermore underline the importance of correctly assessing novel variants in all variant-calling pipelines associated with genetic diagnoses for cancer.
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