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.
Accurate annotation of genomic variants in human diseases is essential to allow personalized medicine. Assessment of somatic and germline TP53 alterations has now reached the clinic and is required in several circumstances such as the identification of the most effective cancer therapy for patients with chronic lymphocytic leukemia (CLL). Here, we present Seshat, a Web service for annotating TP53 information derived from sequencing data. A flexible framework allows the use of standard file formats such as Mutation Annotation Format (MAF) or Variant Call Format (VCF), as well as common TXT files. Seshat performs accurate variant annotations using the Human Genome Variation Society (HGVS) nomenclature and the stable TP53 genomic reference provided by the Locus Reference Genomic (LRG). In addition, using the 2017 release of the UMD_TP53 database, Seshat provides multiple statistical information for each TP53 variant including database frequency, functional activity, or pathogenicity. The information is delivered in standardized output tables that minimize errors and facilitate comparison of mutational data across studies. Seshat is a beneficial tool to interpret the ever-growing TP53 sequencing data generated by multiple sequencing platforms and it is freely available via the TP53 Website, http://p53.fr or directly at http://vps338341.ovh.net/.
- MeSH
- anotace sekvence MeSH
- databáze genetické * MeSH
- genetická variace genetika MeSH
- genomika trendy MeSH
- internet MeSH
- lidé MeSH
- mutace MeSH
- nádorový supresorový protein p53 genetika MeSH
- software * MeSH
- výpočetní biologie trendy MeSH
- vysoce účinné nukleotidové sekvenování MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Accurate assessment of TP53 gene status in sporadic tumors and in the germline of individuals at high risk of cancer due to Li-Fraumeni Syndrome (LFS) has important clinical implications for diagnosis, surveillance, and therapy. Genomic data from more than 20,000 cancer genomes provide a wealth of information on cancer gene alterations and have confirmed TP53 as the most commonly mutated gene in human cancer. Analysis of a database of 70,000 TP53 variants reveals that the two newly discovered exons of the gene, exons 9β and 9γ, generated by alternative splicing, are the targets of inactivating mutation events in breast, liver, and head and neck tumors. Furthermore, germline rearrange-ments in intron 1 of TP53 are associated with LFS and are frequently observed in sporadic osteosarcoma. In this context of constantly growing genomic data, we discuss how screening strategies must be improved when assessing TP53 status in clinical samples. Finally, we discuss how TP53 alterations should be described by using accurate nomenclature to avoid confusion in scientific and clinical reports. Cancer Res; 77(6); 1250-60. ©2017 AACR.
- MeSH
- genetická variace genetika MeSH
- lidé MeSH
- nádorový supresorový protein p53 genetika MeSH
- nádory diagnóza genetika terapie MeSH
- řízení kvality * MeSH
- směrnice pro lékařskou praxi jako téma normy MeSH
- validační studie jako téma MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
