Literature DB >> 30720243

High prevalence of cancer-associated TP53 variants in the gnomAD database: A word of caution concerning the use of variant filtering.

Thierry Soussi1,2,3, Bernard Leroy1, Michal Devir4, Shai Rosenberg4,5.   

Abstract

The 1,000 genome project, the Exome Aggregation Consortium (ExAC) or the Genome Aggregation database (gnomAD) datasets, were developed to provide large-scale reference data of genetic variations for various populations to filter out common benign variants and identify rare variants of clinical importance based on their frequency in the human population. Using a TP53 repository of 80,000 cancer variants, as well as TP53 variants from multiple cancer genome projects, we have defined a set of certified oncogenic TP53 variants. This specific set has been independently validated by functional and in silico predictive analysis. Here we show that a significant number of these variants are included in gnomAD and ExAC. Most of them correspond to TP53 hotspot variants occurring as somatic and germline events in human cancer. Similarly, disease-associated variants for five other tumor suppressor genes, including BRCA1, BRCA2, APC, PTEN, and MLH1, have also been identified. This study demonstrates that germline TP53 variants in the human population are more frequent than previously thought. Furthermore, population databases such as gnomAD or ExAC must be used with caution and need to be annotated for the presence of oncogenic variants to improve their clinical utility.
© 2019 Wiley Periodicals, Inc.

Entities:  

Keywords:  Exome Aggregation Consortium (ExAC); Genome Aggregation database (gnomAD); TP53 variants; single-nucleotide polymorphism (SNP); variant pathogenicity

Mesh:

Substances:

Year:  2019        PMID: 30720243     DOI: 10.1002/humu.23717

Source DB:  PubMed          Journal:  Hum Mutat        ISSN: 1059-7794            Impact factor:   4.878


  7 in total

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Authors:  Kristen E Schratz; Amy E DeZern
Journal:  Hematol Oncol Clin North Am       Date:  2020-01-06       Impact factor: 3.722

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

Authors:  Flora Doffe; Vincent Carbonnier; Manon Tissier; Bernard Leroy; Isabelle Martins; Johanna S M Mattsson; Patrick Micke; Sarka Pavlova; Sarka Pospisilova; Jana Smardova; Andreas C Joerger; Klas G Wiman; Guido Kroemer; Thierry Soussi
Journal:  Cell Death Differ       Date:  2020-11-30       Impact factor: 15.828

3.  Comprehensive assessment of TP53 loss of function using multiple combinatorial mutagenesis libraries.

Authors:  Vincent Carbonnier; Bernard Leroy; Shai Rosenberg; Thierry Soussi
Journal:  Sci Rep       Date:  2020-11-23       Impact factor: 4.379

4.  In cis TP53 and RAD51C pathogenic variants may predispose to sebaceous gland carcinomas.

Authors:  Diana Le Duc; Julia Hentschel; Sonja Neuser; Mathias Stiller; Carolin Meier; Elisabeth Jäger; Rami Abou Jamra; Konrad Platzer; Astrid Monecke; Mirjana Ziemer; Aleksander Markovic; Hendrik Bläker; Johannes R Lemke
Journal:  Eur J Hum Genet       Date:  2020-12-15       Impact factor: 4.246

5.  APC Splicing Mutations Leading to In-Frame Exon 12 or Exon 13 Skipping Are Rare Events in FAP Pathogenesis and Define the Clinical Outcome.

Authors:  Vittoria Disciglio; Giovanna Forte; Candida Fasano; Paola Sanese; Martina Lepore Signorile; Katia De Marco; Valentina Grossi; Filomena Cariola; Cristiano Simone
Journal:  Genes (Basel)       Date:  2021-02-28       Impact factor: 4.096

6.  Annotation of Human Exome Gene Variants with Consensus Pathogenicity.

Authors:  Victor Jaravine; James Balmford; Patrick Metzger; Melanie Boerries; Harald Binder; Martin Boeker
Journal:  Genes (Basel)       Date:  2020-09-14       Impact factor: 4.096

7.  TP53_PROF: a machine learning model to predict impact of missense mutations in TP53.

Authors:  Gil Ben-Cohen; Flora Doffe; Michal Devir; Bernard Leroy; Thierry Soussi; Shai Rosenberg
Journal:  Brief Bioinform       Date:  2022-03-10       Impact factor: 11.622

  7 in total

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