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IARC TP53 Database


NAR Molecular Biology Database Collection entry number 362
Olivier, M.1, Hollstein, M.2, Harris, C.C..3, and Hainaut, P.1
1Group of Molecular Carcinogenesis, International Agency for Research on Cancer, World Health Organization, 150 Cours Albert Thomas, 69372 Lyon cedex 08, France
22Molecular Epidemiology Unit, Leeds Institute of Genetics, University of Leeds, Leeds, UK
33Laboratory of Human Carcinogenesis, Building 37, Room 2C05, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892-4255, USA

Database Description

The IARC TP53 database is a public web-based resource for the analysis and interpretation of the biological and clinical impacts of TP53 gene variations in human cancers (http://www-p53.iarc.fr/). It contains data that are compiled from the peer-reviewed scientific literature or generalist databases. It includes annotations on predicted or experimentally assessed functional and structural impacts of mutations, as well as on tumor pathology and patient demographics and life-styles.
There are five integrated datasets (somatic mutations, germline mutations, polymorphisms, biological activities of mutant proteins, mouse-models) that can be fully downloaded. The database can be search through an interactive web interface that allows for the selection, analysis and download of specific sets of data according to user’s query. The web site also provides a comprehensive user guide, a slide-show on TP53 mutations in human cancer, protocols and references for sequencing the TP53 gene, and links to relevant publications and entries to other related cancer databases.
With over 25,000 somatic and 500 germline mutations and 2,000 citations in the world literature, this database is recognized as a major source of information on TP53 mutation patterns in human cancer. The database is meant to be a resource for a broad range of scientists and clinicians who work in different research areas: (1) basic research, to study the structural and functional aspects of the p53 protein; (2) molecular pathology of cancer, to understand the clinical significance of mutations identified in cancer patients; (3) molecular epidemiology of cancer, to investigate links between specific exposures and mutation patterns and to make inferences about possible causes of cancer; (4) molecular genetics, to study genotype/phenotype associations.

Recent Developments

Recent developments include:
- restructuring of the database which is now patient-centered, with more detailed annotations on the patient (carcinogen exposure, virus infection, genetic background).
- data on mutation prevalence (R6 update) and on clinical outcome (next update).
- an online search system that allows the online analysis of somatic mutation data (available through the 'database search' option). This ASP (Active Server Pages) application allows the identification and selection of specific sets of data according to user's queries and produces graphical outputs (histograms and pie charts) of mutation patterns, codon distribution and tumor spectrum. A search of reference criteria (author name, PubMed entry, title, etc...) allows the analysis of mutation data by individual publication to generate graphs and figures.
- the entire dataset, or sets of data selected according to the user's queries, can be downloaded as tab-delimited text files, in a compressed format.
- a comprehensive user guide is available online as well as a slide-show on TP53 mutations, database structure/content and examples of mutation analysis.

Acknowledgements

The project is funded by IARC and supported by the European Community (contract: QLG1-1999-00273).

References

1. Petitjean, A., Mathe, E., Kato, S., Ishioka, C., Tavtigian, S.V., Hainaut, P., and Olivier, M. (2007) Impact of mutant p53 functional properties on TP53 mutation patterns and tumor phenotype: lessons from recent developments of the IARC TP53 Database. Hum Mutat 28(6), 622-9
2. Mathe, E., Olivier, M., Kato, S., Ishioka, C., Hainaut, P., and Tavtigian, S.V. (2006) Computational approaches for predicting the biological effect of p53 missense mutations: a comparison of three sequence analysis based methods. Nucleic Acids Res. 2006 34(5), 1317-25
3. Olivier, M., Goldgar, D.E., Sodha, N., Ohgaki, H., Kleihues, P., Hainaut, P., and Eeles, R.A. (2003) Li-Fraumeni and related syndromes: correlation between tumor type, family structure and TP53 genotype. Cancer Research 63(20), 6643-50

Subcategory: Cancer gene databases

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