Analysis p53 mutations heterogeneity in human tumours

 The objective of our group is to understand how alterations of the p53 tumor suppressor gene contribute to the heterogeneity of the clinical manifestations of human cancer using a multidisciplinary program combining clinical, in silico and biological analyses

More than 50% of human tumors carry TP53 gene mutations and, consequently, more than 45,000 somatic and germline mutations have been collected in the UMD TP53 database developed in our laboratory ( Analyses of these mutations have been invaluable for furthering our knowledge on the structure–function relationships within the TP53 protein and the high degree of heterogeneity of the various TP53 mutants in human cancer. Using the evolution and content of the TP53 LSDB as a paradigm, it has been possible to construct a model of gene mutation analysis covering initial descriptions, the accumulation and organization of knowledge in databases, and the use of this knowledge in clinical practice. It has also been possible to formulate several assumptions on the future of LSDBs and how centralized databases could change the accessibility of data, with interfaces optimized for different types of users and adapted to the specificity of each region of the genome, coding or noncoding, associated with tumor development

TP53 mutations are heterogeneous among the various types of cancers. This can be linked to either the specific mutagenic pattern associated with the various types of cancer or a specific selection for TP53 in a given cancer. Developing novel in vitro and in vivo models for these specific variants should provide novel insight into the oncogenic functions of TP53 mutants.

 TP53 Cancer

Frequency of cancer deaths worldwide and relationship to the frequency of TP53 mutations. Cancer death numbers from GLOBOCAN 2008 ( TP53 mutation data from the UMD TP53 database 2017

a) The frequency of TP53 mutations in lung cancer varies among the diverse subtypes;
b) The frequency of TP53 mutation in liver cancer can vary depending on the etiology of the tumor, e.g., viral infection or exposure to food contaminants such as aflatoxin B1; 
c) The frequency of TP53 mutations in breast cancer varies among the diverse subtypes; 
d) TP53 mutation is negatively correlated to human papillomavirus infection in cervical cancer; 
e) TP53 mutation in prostate cancer is more frequent in metastatic tumors; 
f) The frequency of TP53 mutations in leukemia and lymphoma is highly heterogeneous among the various types, usually uncommon at diagnosis but can reach 50% at relapse or during blastic transformation. 

Recent publications

Soussi T & Kroemer G (2017) TP53 and 53BP1 Reunited. Trends Cell Biol, 27: 311–313

Soussi T, Taschner PE & Samuels Y (2017) Synonymous Somatic Variants in Human Cancer Are Not Infamous: A Plea for Full Disclosure in Databases and Publications. Hum Mutat, 38: 339–342

Leroy B, Ballinger ML, Baran-Marszak F, Bond GL, Braithwaite A, Concin N, Donehower LA, El-Deiry WS, Fenaux P, Gaidano G, Langerød A, Hellstrom-Lindberg E, Iggo R, Lehmann-Che J, Mai PL, Malkin D, Moll UM, Myers JN, Nichols KE, Pospisilova S, Ashton-Prolla P, Rossi D, Savage SA, Strong LC, Tonin PN, Zeillinger R, Zenz T, Fraumeni JF, Taschner PE, Hainaut P & Soussi T (2017) Recommended Guidelines for Validation, Quality Control, and Reporting of TP53 Variants in Clinical Practice. Cancer Res, 6: 1250–1260

Lazarian G, Tausch E, Eclache V, Sebaa A, Bianchi V, Letestu R, Collon JF, Lefebvre V, Gardano L, Varin-Blank N, Soussi T, Stilgenbauer S, Cymbalista F & Baran-Marszak F (2016) TP53 mutations are early events in chronic lymphocytic leukemia disease progression and precede evolution to complex karyotypes. Int J Cancer, 139: 1759–1763

Lodé L, Cymbalista F & Soussi T (2016) Genetic profiling of CLL: a ‘TP53 addict’ perspective. Cell Death Dis, 7: e2042

Soussi T & Wiman KG (2015) TP53: an oncogene in disguise. Cell Death Differ, 22: 1239–1249

Soussi, T. (2014). Locus-Specific Databases in Cancer: What Future in a Post-Genomic Era? The TP53 LSDB Paradigm. Hum Mutat 35, 643-653.

Leroy, B., Anderson, M., and Soussi, T. (2014). TP53 Mutations in Human Cancer: Database Reassessment and Prospects for the Next Decade. Hum Mutat 35, 672-688.

Soussi, T. (2014). The TP53 gene network in a postgenomic era. Hum Mutat 35, 641-642.

Soussi, T., Leroy, B., and Taschner, P. E. (2014). Recommendations for Analyzing and Reporting TP53 Gene Variants in the High-Throughput Sequencing Era. Hum Mutat 35, 766-778.

Leroy, B., Girard, L., Hollestelle, A., Minna, J. D., Gazdar, A. F., and Soussi, T. (2014). Analysis of TP53 Mutation Status in Human Cancer Cell Lines: A Reassessment. Hum Mutat 35, 756-765.

Edlund K, Larsson O, Ameur A, Bunikis I, Gyllensten U, Leroy B, Sundstrom M, Micke P, Botling J, and Soussi T. 2012. Data-driven unbiased curation of the TP53 tumor suppressor gene mutation database and validation by ultra deep sequencing of human tumors. Proc Natl Acad Sci U S A 109: 9551-9556.

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