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Article ; Online: Letter to the editor.

Soussi, Thierry

2023 Volume 32, Issue 13, Page(s) 2121–2123

Language	English
Publishing date	2023-03-07
Publishing country	England
Document type	Journal Article
ZDB-ID	1108742-0
ISSN	1460-2083 ; 0964-6906
ISSN (online)	1460-2083
ISSN	0964-6906
DOI	10.1093/hmg/ddad037
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Article ; Online: Benign SNPs in the Coding Region of TP53: Finding the Needles in a Haystack of Pathogenic Variants.

Soussi, Thierry

Cancer research

2022 Volume 82, Issue 19, Page(s) 3420–3431

Abstract: With the recent explosion in high-throughput genotyping technology, the amount and quality of SNP data have increased exponentially, facilitating the discovery of multiple uncommon SNPs in the human population. To provide unified and centralized ... ...

Abstract	With the recent explosion in high-throughput genotyping technology, the amount and quality of SNP data have increased exponentially, facilitating the discovery of multiple uncommon SNPs in the human population. To provide unified and centralized resources for the scientific community, several repositories have been developed that aggregate numerous population studies and serve widely as references to filter natural variants in genetic analyses. However, they are largely biased toward European populations. TP53 gene is the most frequently mutated gene in human cancer, and pathogenic germline TP53 variants are associated with several cancer susceptibility disorders such as Li-Fraumeni syndrome. For these reasons, it is essential that TP53 SNPs are rigorously evaluated to avoid misclassifications that could impair patient management. The recent discovery of numerous benign SNPs within the coding region of TP53 can be attributed to surveillance of both global repositories and population-specific databases, with the latter enabling the recognition of additional TP53 SNPs in Japanese, African, and Indian populations. This review summarizes the body of evidence behind the identification of 21 TP53 variants and the information defining them as bona fide SNPs. This illustrates the need to include populations of different ethnic origins in genetic studies and the substantial benefits that can be derived from the information.
MeSH term(s)	Genetic Predisposition to Disease/genetics ; Genetic Testing ; Germ-Line Mutation ; Humans ; Li-Fraumeni Syndrome/genetics ; Polymorphism, Single Nucleotide ; Tumor Suppressor Protein p53/genetics
Chemical Substances	TP53 protein, human ; Tumor Suppressor Protein p53
Language	English
Publishing date	2022-07-23
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	1432-1
ISSN	1538-7445 ; 0008-5472
ISSN (online)	1538-7445
ISSN	0008-5472
DOI	10.1158/0008-5472.CAN-22-0172
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Article: Landscape of TP53 Alterations in Chronic Lymphocytic Leukemia

Soussi, Thierry / Baliakas, Panagiotis

Frontiers in oncology

2022 Volume 12, Page(s) 808886

Abstract: Locus-specific databases are invaluable tools for both basic and clinical research. The extensive information they contain is gathered from the literature and manually curated by experts. Cancer genome sequencing projects generate an immense amount of ... ...

Abstract	Locus-specific databases are invaluable tools for both basic and clinical research. The extensive information they contain is gathered from the literature and manually curated by experts. Cancer genome sequencing projects generate an immense amount of data, which are stored directly in large repositories (cancer genome databases). The presence of a
Language	English
Publishing date	2022-02-16
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2649216-7
ISSN	2234-943X
ISSN	2234-943X
DOI	10.3389/fonc.2022.808886
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Article ; Online: Locus-specific databases in cancer: what future in a post-genomic era? The TP53 LSDB paradigm.

Soussi, Thierry

Human mutation

2014 Volume 35, Issue 6, Page(s) 643–653

Abstract: Locus-specific databases (LSDBs) are curated compilations of sequence variants in genes associated with disease and have been invaluable tools for both basic and clinical research. These databases contain extensive information provided by the literature ... ...

Abstract	Locus-specific databases (LSDBs) are curated compilations of sequence variants in genes associated with disease and have been invaluable tools for both basic and clinical research. These databases contain extensive information provided by the literature and benefit from manual curation by experts. Cancer genome sequencing projects have generated an explosion of data that are stored directly in centralized databases, thus possibly alleviating the need to develop independent LSDBs. A single cancer genome contains several thousand somatic mutations. However, only a handful of these mutations are truly oncogenic and identifying them remains a challenge. However, we can expect that this increase in data and the development of novel biocuration algorithms will ultimately result in more accurate curation and the release of stable sets of data. Using the evolution and content of the TP53 LSDB as a paradigm, it is possible to draw 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 is also possible to make 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.
MeSH term(s)	Computational Biology ; Databases, Genetic ; Genomics ; High-Throughput Nucleotide Sequencing ; Humans ; Internet ; Mutation ; Neoplasms/genetics ; Neoplasms/pathology ; Software ; Tumor Suppressor Protein p53/genetics
Chemical Substances	TP53 protein, human ; Tumor Suppressor Protein p53
Language	English
Publishing date	2014-06
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	1126646-6
ISSN	1098-1004 ; 1059-7794
ISSN (online)	1098-1004
ISSN	1059-7794
DOI	10.1002/humu.22518
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Article ; Online: The TP53 gene network in a postgenomic era.

Soussi, Thierry

Human mutation

2014 Volume 35, Issue 6, Page(s) 641–642

Abstract: Inactivation of TP53 pathways are the most common defects observed in human cancer. Although missense mutations remain the most frequent genetic event, it is now evident that dysfunction of several members of this network such as MDM2, MDM4 (mdmX), or ... ...

Abstract	Inactivation of TP53 pathways are the most common defects observed in human cancer. Although missense mutations remain the most frequent genetic event, it is now evident that dysfunction of several members of this network such as MDM2, MDM4 (mdmX), or miR-125b can substitute for TP53 mutations. This special issue on TP53 brings the TP53 gene into the post-genomic era. Several fundamental features of wild type and mutant proteins and their modifications are reviewed, as well as animal models and clinical aspects such as recommendations for patient care. The complex structure of this gene warrants innovative strategies to infer a more accurate status of human tumors. Recommendations and guidelines for reporting and annotating TP53 variants are also provided, to help researchers generate standardized data that are easy to understand, analyze, and exchange across various cancer variant databases.
MeSH term(s)	Gene Regulatory Networks ; Genome, Human ; Genomics ; Humans ; MicroRNAs/genetics ; Mutation, Missense ; Neoplasms/genetics ; Neoplasms/pathology ; Neoplasms/therapy ; Nuclear Proteins/genetics ; Proto-Oncogene Proteins/genetics ; Proto-Oncogene Proteins c-mdm2/genetics ; Signal Transduction/genetics ; Tumor Suppressor Protein p53/genetics ; Tumor Suppressor Protein p53/metabolism
Chemical Substances	MDM4 protein, human ; MIRN125 microRNA, human ; MicroRNAs ; Nuclear Proteins ; Proto-Oncogene Proteins ; TP53 protein, human ; Tumor Suppressor Protein p53 ; MDM2 protein, human (EC 2.3.2.27) ; Proto-Oncogene Proteins c-mdm2 (EC 2.3.2.27)
Language	English
Publishing date	2014-06
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	1126646-6
ISSN	1098-1004 ; 1059-7794
ISSN (online)	1098-1004
ISSN	1059-7794
DOI	10.1002/humu.22562
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Article ; Online: Comprehensive assessment of TP53 loss of function using multiple combinatorial mutagenesis libraries.

Carbonnier, Vincent / Leroy, Bernard / Rosenberg, Shai / Soussi, Thierry

Scientific reports

2020 Volume 10, Issue 1, Page(s) 20368

Abstract: The diagnosis of somatic and germline TP53 mutations in human tumors or in individuals prone to various types of cancer has now reached the clinic. To increase the accuracy of the prediction of TP53 variant pathogenicity, we gathered functional data from ...

Abstract	The diagnosis of somatic and germline TP53 mutations in human tumors or in individuals prone to various types of cancer has now reached the clinic. To increase the accuracy of the prediction of TP53 variant pathogenicity, we gathered functional data from three independent large-scale saturation mutagenesis screening studies with experimental data for more than 10,000 TP53 variants performed in different settings (yeast or mammalian) and with different readouts (transcription, growth arrest or apoptosis). Correlation analysis and multidimensional scaling showed excellent agreement between all these variables. Furthermore, we found that some missense mutations localized in TP53 exons led to impaired TP53 splicing as shown by an analysis of the TP53 expression data from the cancer genome atlas. With the increasing availability of genomic, transcriptomic and proteomic data, it is essential to employ both protein and RNA prediction to accurately define variant pathogenicity.
MeSH term(s)	Alternative Splicing ; Animals ; Apoptosis/genetics ; Atlases as Topic ; Cell Cycle Checkpoints/genetics ; Computational Biology/methods ; Exons ; Gene Expression Regulation, Neoplastic ; Gene Library ; Genetic Predisposition to Disease ; Humans ; Introns ; Multidimensional Scaling Analysis ; Mutagenesis ; Mutation ; Neoplasm Proteins/genetics ; Neoplasm Proteins/metabolism ; Neoplasms/genetics ; Neoplasms/metabolism ; Neoplasms/pathology ; Saccharomyces cerevisiae/genetics ; Saccharomyces cerevisiae/metabolism ; Transcription, Genetic ; Tumor Suppressor Protein p53/deficiency ; Tumor Suppressor Protein p53/genetics
Chemical Substances	Neoplasm Proteins ; TP53 protein, human ; Tumor Suppressor Protein p53
Language	English
Publishing date	2020-11-23
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-020-74892-2
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Article ; Online: TP53 mutations in human cancer: database reassessment and prospects for the next decade.

Soussi, Thierry

Advances in cancer research

2011 Volume 110, Page(s) 107–139

Abstract: TP53 mutations are the most frequent genetic alterations found in human cancer. For more than 20 years, TP53 mutation databases have collected over 30,000 somatic mutations from various types of cancer. Analyses of these mutations have led to many types ... ...

Abstract	TP53 mutations are the most frequent genetic alterations found in human cancer. For more than 20 years, TP53 mutation databases have collected over 30,000 somatic mutations from various types of cancer. Analyses of these mutations have led to many types of studies and have improved our knowledge about the TP53 protein and its function. The recent advances in sequencing methodologies and the various cancer genome sequencing projects will lead to a profound shift in database curation and data management. In this paper, we will review the current status of the TP53 mutation database, its application to various fields of research, and how data quality and curation can be improved. We will also discuss how the genetic data will be stored and handled in the future and the consequences for database management.
MeSH term(s)	Animals ; Database Management Systems ; Databases, Genetic ; Humans ; Mutation ; Neoplasms/genetics ; Tumor Suppressor Protein p53/genetics
Chemical Substances	Tumor Suppressor Protein p53
Language	English
Publishing date	2011
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	127-2
ISSN	2162-5557 ; 0065-230X
ISSN (online)	2162-5557
ISSN	0065-230X
DOI	10.1016/B978-0-12-386469-7.00005-0
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Article ; Online: TP53_PROF: a machine learning model to predict impact of missense mutations in TP53.

Ben-Cohen, Gil / Doffe, Flora / Devir, Michal / Leroy, Bernard / Soussi, Thierry / Rosenberg, Shai

Briefings in bioinformatics

2022 Volume 23, Issue 2

Abstract: Correctly identifying the true driver mutations in a patient's tumor is a major challenge in precision oncology. Most efforts address frequent mutations, leaving medium- and low-frequency variants mostly unaddressed. For TP53, this identification is ... ...

Abstract	Correctly identifying the true driver mutations in a patient's tumor is a major challenge in precision oncology. Most efforts address frequent mutations, leaving medium- and low-frequency variants mostly unaddressed. For TP53, this identification is crucial for both somatic and germline mutations, with the latter associated with the Li-Fraumeni syndrome (LFS), a multiorgan cancer predisposition. We present TP53_PROF (prediction of functionality), a gene specific machine learning model to predict the functional consequences of every possible missense mutation in TP53, integrating human cell- and yeast-based functional assays scores along with computational scores. Variants were labeled for the training set using well-defined criteria of prevalence in four cancer genomics databases. The model's predictions provided accuracy of 96.5%. They were validated experimentally, and were compared to population data, LFS datasets, ClinVar annotations and to TCGA survival data. Very high accuracy was shown through all methods of validation. TP53_PROF allows accurate classification of TP53 missense mutations applicable for clinical practice. Our gene specific approach integrated machine learning, highly reliable features and biological knowledge, to create an unprecedented, thoroughly validated and clinically oriented classification model. This approach currently addresses TP53 mutations and will be applied in the future to other important cancer genes.
MeSH term(s)	Genetic Predisposition to Disease ; Humans ; Li-Fraumeni Syndrome/genetics ; Machine Learning ; Mutation, Missense ; Precision Medicine ; Tumor Suppressor Protein p53/genetics
Chemical Substances	TP53 protein, human ; Tumor Suppressor Protein p53
Language	English
Publishing date	2022-01-18
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2068142-2
ISSN	1477-4054 ; 1467-5463
ISSN (online)	1477-4054
ISSN	1467-5463
DOI	10.1093/bib/bbab524
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Article: Advances in carcinogenesis: a historical perspective from observational studies to tumor genome sequencing and TP53 mutation spectrum analysis.

Soussi, Thierry

Biochimica et biophysica acta

2011 Volume 1816, Issue 2, Page(s) 199–208

Abstract: Tumor sequencing projects have been initiated over the last decade with the promising goal of identifying novel cancer genes and potential therapeutic targets. One of the unexpected findings of these projects was the discovery that cancer genomes contain ...

Abstract	Tumor sequencing projects have been initiated over the last decade with the promising goal of identifying novel cancer genes and potential therapeutic targets. One of the unexpected findings of these projects was the discovery that cancer genomes contain thousands of passenger mutations that are irrelevant to tumor development and are coselected by a small number of driver mutations that constitute the true selection power in cancer progression. Although often discarded and considered to be irrelevant, the value of passenger mutations should not be underestimated, as they are the most important markers of the exposure to various carcinogens and are essential to assess the etiology of individual tumors. Over the last century, the history of cancer epidemiology evolved in different stages and concepts from occupational observational studies beginning in the 18th century, in vitro and in vivo experimental analyses and cancer gene analyses, such as Ha-ras or TP53. Mutation spectra of passenger mutations from various types of cancers not only confirm the findings of molecular epidemiology analysis, but also reveal novel profiles that will extend this knowledge to single tumors in all types of cancer.
MeSH term(s)	Animals ; Brain Neoplasms/genetics ; Breast Neoplasms/genetics ; Colorectal Neoplasms/genetics ; Female ; Genes, p53 ; Genome ; Humans ; Liver Neoplasms/genetics ; Lung Neoplasms/genetics ; Mutation ; Neoplasms/genetics ; Sequence Analysis, DNA ; Skin Neoplasms/genetics
Language	English
Publishing date	2011-12
Publishing country	Netherlands
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	60-7
ISSN	1879-2596 ; 1879-260X ; 1872-8006 ; 1879-2642 ; 1879-2618 ; 1879-2650 ; 0006-3002 ; 0005-2728 ; 0005-2736 ; 0304-4165 ; 0167-4838 ; 1388-1981 ; 0167-4889 ; 0167-4781 ; 0304-419X ; 1570-9639 ; 0925-4439 ; 1874-9399
ISSN (online)	1879-2596 ; 1879-260X ; 1872-8006 ; 1879-2642 ; 1879-2618 ; 1879-2650
ISSN	0006-3002 ; 0005-2728 ; 0005-2736 ; 0304-4165 ; 0167-4838 ; 1388-1981 ; 0167-4889 ; 0167-4781 ; 0304-419X ; 1570-9639 ; 0925-4439 ; 1874-9399
DOI	10.1016/j.bbcan.2011.07.003
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Article ; Online: TP53 and 53BP1 Reunited.

Soussi, Thierry / Kroemer, Guido

Trends in cell biology

2017 Volume 27, Issue 5, Page(s) 311–313

Abstract: Identified as a TP53-binding protein, 53BP1 is a key regulator of the cellular response to double-strand breaks, a TP53-independent activity. Recent data have established a new TP53-dependent function for 53BP1 in mitotic surveillance after centrosome ... ...

Abstract	Identified as a TP53-binding protein, 53BP1 is a key regulator of the cellular response to double-strand breaks, a TP53-independent activity. Recent data have established a new TP53-dependent function for 53BP1 in mitotic surveillance after centrosome loss.
Language	English
Publishing date	2017-05
Publishing country	England
Document type	Journal Article
ZDB-ID	30122-x
ISSN	1879-3088 ; 0962-8924
ISSN (online)	1879-3088
ISSN	0962-8924
DOI	10.1016/j.tcb.2016.10.004
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