Thierry Soussi's Group

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Analysis of p53 mutations heterogeneity in human tumours. The objective of the group is to understand how alterations of the p53 tumour suppressor gene contribute to the heterogeneity of the clinical manifestation of human cancer.

p53 alterations are the most frequent genetic event in human cancer. Recent observations have challenged several dogma concerning p53 mutations. Among them, are the number of p53 mutations per tumour and the biological function of p53 targeted by the various mutations. Furthermore, using novel statistical analysis, we have shown that some p53 mutations are only passenger mutations that are co-selected during the neoplastic transformation.

In order to have a more accurate picture on the heterogeneity of p53 loss of function in human cancer, we have undertake a multidisciplinary program that will combine clinical, in silico and basic analysis to understand how alterations of the p53 tumour suppressor gene contribute to the heterogeneity of the clinical manifestation of human cancer.

Analysis of p53 mutations heterogeneity in human tumours

Identification of novel genes associated with tumour development will provide new insights into cancer biology, and might also clarify whether some of these mutated genes could be effective targets for anticancer drug development. For this purpose, partial and whole cancer genome sequencing has been initiated and has led to the discovery of an unexpected landscape of in vivo somatic mutations with 10 to 20,000 base substitutions per genome (Stratton et al., 2009; Strausberg and Simpson, 2010). The majority of these variations are somatic passenger mutations (or hitchhiking mutations) that have no active role in cancer progression and are co-selected by the driver mutations which are the true driving force for cell transformation (Chanock and Thomas, 2007). Passenger mutations can be found in coding or non-coding regions of any genes and the distinction of these genes from driving mutations is a difficult but necessary task to obtain an accurate picture of the cancer genome.

Reporting, storing, classifying and analysing these mutations constitute a major challenge (Horaitis and Cotton, 2004). For a long time, locus-specific databases (LSDB) have been developed for this purpose. Most of them are a list of mutations collected in publications and no information indicating whether or not these are passenger or driver mutations are available. TP53 mutation (TP53; MIM# 191170) database is a paradigm, as it constitutes the largest collection of somatic mutations for a single gene. The UMD p53 mutation database has been created in 1990. ( This web site, designed and updated by our team is the oldest p53 web site (1994). It contains useful information on p53 and on the other members of the p53 family (number of pages visited, Jan 2011: 2 310 000). The last issue of the UMD-TP53 database includes 31,000 mutations from 29,000 patients (T. Soussi, Unpublished). A unique feature of the UMD-P53 database is the information regarding the biological activity of the majority of mutant p53 (transcriptional assay in yeast) {Soussi et al., 2005, #79304}.

In 2006, we published a meta-analysis of 2,000 reports describing TP53 mutations and revealed that although the most frequent TP53 mutants sustain a clear loss of transactivation activity, more than 50% of the rare p53 mutants display significant activity similar to wild type p53 (figure 1).

Figure 1. Activity of mutant p53s according to their frequency in the database. Mutant p53 have been classified into eight categories according to their frequencies. Boxes and whisker plots show the upper and lower quartiles and range (box), median value (horizontal line inside the box), and full range distribution (whisker line). Analysis was performed using the activity of the WAF1promoter. The black arrow indicates the value of wt p53 activity this promoter. Further analysis have shown that part of these rare mutants were artifactual mutations associated with methodological bias for p53 analysis (Soussi et al., 2005)

A meta analysis on 3000 publications reporting p53 mutations in various cancer demonstrates that 10 to 20% of these rare p53 mutants are laboratory artefacts whereas the other could be considered as passenger mutations (Soussi et al., 2006). Our recent work on 1,200 cell lines, has shown that there are discrepancies in the p53 status for 23% of cell lines, for which the p53 status was established independently in different laboratories (Berglind et al., 2008).

Novel algorithms are currently under development to achieve a better classification of TP53 mutant (Carlsson et al., 2009). The server is available via under Services.

Massively parallel sequencing has the potential to identify the compendia of rare sub clones of genetic variants that may exist in human tumours. As amplification and sequencing are performed on every single molecule, the sensitivity of the detection will only depend on the number of different sequencing reaction that will be processed. The high throughput of the SOLID platform can be used for this study and we expect at least 5 000 reads for each analysis. Tumours that express multiple p53 mutations will be easily detected even if one of the mutations is poorly expressed.

Tumours from lung, breast and colorectal carcinoma are currently analysed using both conventional and UDS. The panel of lung cancer collected at the department of Pathology of Uppsala has been extensively analysed for gene expression and p53 mutations is used for this study (Available as frozen tumours, J. Botling and P. Micke, unpublished study). Tumoural DNA from 30 patients with breast cancer that were previously analysed for p53 mutation by conventional DNA sequencing are also available for this analysis. Colon tumours have been collected prospectively from the department of Pathology of Uppsala. Tumour cells content ranges from a minimum of 50 % (lung cancer) to 70% for breast tumours.

The choice of these three types of cancer is not genuine as the aetiology and their pattern of p53 mutations is totally different and well defined (Soussi and Beroud, 2003). The entire p53 gene (exons and introns) is covered by the analysis. The p73 gene, a member of the p53 family that is rarely muted in human cancer is used as a negative control to assess mutations due to the experimental procedure.


Group members

Thierry Soussi, Group leader
Julie Bianchi, Post doc

Selected publications

The TP53 website: an integrative resource centre for the TP53 mutation database and TP53 mutant analysis.
Leroy B, Fournier J, Ishioka C, Monti P, Inga A, Fronza G, et al
Nucleic Acids Res. 2013 Jan;41(Database issue):D962-9

Data-driven unbiased curation of the TP53 tumor suppressor gene mutation database and validation by ultradeep sequencing of human tumors.
Edlund K, Larsson O, Ameur A, Bunikis I, Gyllensten U, Leroy B, et al
Proc. Natl. Acad. Sci. U.S.A. 2012 Jun;109(24):9551-6

The history of p53. A perfect example of the drawbacks of scientific paradigms.
Soussi T
EMBO Rep. 2010 Nov;11(11):822-6

Mutant p53 protein localized in the cytoplasm inhibits autophagy.
Morselli E, Tasdemir E, Maiuri M, Galluzzi L, Kepp O, Criollo A, et al
Cell Cycle 2008 Oct;7(19):3056-61

Analysis of p53 mutation status in human cancer cell lines: a paradigm for cell line cross-contamination.
Berglind H, Pawitan Y, Kato S, Ishioka C, Soussi T
Cancer Biol. Ther. 2008 May;7(5):699-708

Shaping genetic alterations in human cancer: the p53 mutation paradigm.
Soussi T, Wiman K
Cancer Cell 2007 Oct;12(4):303-12

Meta-analysis of the p53 mutation database for mutant p53 biological activity reveals a methodologic bias in mutation detection.
Soussi T, Asselain B, Hamroun D, Kato S, Ishioka C, Claustres M, et al
Clin. Cancer Res. 2006 Jan;12(1):62-9

Locus-specific mutation databases: pitfalls and good practice based on the p53 experience.
Soussi T, Ishioka C, Claustres M, Béroud C
Nat. Rev. Cancer 2006 Jan;6(1):83-90

The TP53 colorectal cancer international collaborative study on the prognostic and predictive significance of p53 mutation: influence of tumor site, type of mutation, and adjuvant treatment.
Russo A, Bazan V, Iacopetta B, Kerr D, Soussi T, Gebbia N, et al
J. Clin. Oncol. 2005 Oct;23(30):7518-28

p53 mutations and resistance to chemotherapy: A stab in the back for p73.
Soussi T
Cancer Cell 2003 Apr;3(4):303-5

Full list of publications