Magali Olivier

Tobacco smoke carcinogens, DNA damage and p53 mutations in smoking-associated cancers.

It is estimated that cigarette smoking kills over 1 000 000 people each year by causing lung cancer as well as many other neoplasmas. p53 mutations are frequent in tobacco-related cancers and the mutation load is often higher in cancers from smokers than from nonsmokers. In lung cancers, the p53 mutational patterns are different between smokers and nonsmokers with an excess of G to T transversions in smoking-associated cancers. The prevalence of G to T transversions is 30% in smokers’ lung cancer but only 12% in lung cancers of nonsmokers. A similar trend exists, albeit less marked, in laryngeal cancers and in head and neck cancers. This type of mutation is infrequent in most other tumors aside from hepatocellular carcinoma. At several p53 mutational hotspots common to all cancers, such as codons 248 and 273, a large fraction of the mutations are G to T events in lung cancers but are almost exclusively G to A transitions in non-tobacco-related cancers. Two important classes of tobacco smoke carcinogens are the polycyclic aromatic hydrocarbons (PAH) and the nicotine-derived nitrosamines. Recent studies have indicated that there is a strong coincidence of G to T transversion hotspots in lung cancers and sites of preferential formation of PAH adducts along the p53 gene. Endogenously methylated CpG dinucleotides are the preferred sites for G to T transversions, accounting for more than 50% of such mutations in lung tumors. The same dinucleotide, when present within CpG-methylated mutational reporter genes, is the target of G to T transversion hotspots in cells exposed to the model PAH compound benzo[a]pyrene-7,8-diol-9,10-epoxide. As summarized here, a number of other tobacco smoke carcinogens also can cause G to T transversion mutations. The available data suggest that p53 mutations in lung cancers can be attributed to direct DNA damage from cigarette smoke carcinogens rather than to selection of pre-existing endogenous mutations.

TP53 Mutations in Human Cancers: Origins, Consequences, and Clinical Use

Somatic mutations in the TP53 gene are one of the most frequent alterations in human cancers, and germline mutations are the underlying cause of Li-Fraumeni syndrome, which predisposes to a wide spectrum of early-onset cancers. Most mutations are single-base substitutions distributed throughout the coding sequence. Their diverse types and positions may inform on the nature of mutagenic mechanisms involved in cancer etiology. TP53 mutations are also potential prognostic and predictive markers, as well as targets for pharmacological intervention. All mutations found in human cancers are compiled in the IARC TP53 Database (http://www-p53.iarc.fr/). A human TP53 knockin mouse model (Hupki mouse) provides an experimental model to study mutagenesis in the context of a human TP53 sequence. Here, we summarize current knowledge on TP53 gene variations observed in human cancers and populations, and current clinical applications derived from this knowledge.

TP53 mutations in human cancers: functional selection and impact on cancer prognosis and outcomes

A large amount of data is available on the functional impact of missense mutations in TP53 and on mutation patterns in many different cancers. New data on mutant p53 protein function, cancer phenotype and prognosis have recently been integrated in the International Agency for Research on Cancer TP53 database (http://www-p53.iarc.fr/). Based on these data, we summarize here current knowledge on the respective roles of mutagenesis and biological selection of mutations with specific functional characteristic in shaping the patterns and phenotypes of mutations observed in human cancers. The main conclusion is that intrinsic mutagenicity rates, loss of transactivation activities, and to a lesser extent, dominant-negative activities are the main driving forces that determine TP53 mutation patterns and influence tumor phenotype. In contrast, current experimental data on the acquisition of oncogenic activities (gain of function) by p53 mutants are too scarce and heterogenous to assess whether this property has an impact on tumor development and outcome. In the case of inherited TP53 mutations causing Li–Fraumeni and related syndromes, the age at onset of some tumor types is in direct relation with the degree of loss of transactivation capacity of missense mutations. Finally, studies on large case series demonstrate that TP53 mutations are independent markers of bad prognosis in breast and several other cancers, and that the exact type and position of the mutation influences disease outcome. Further studies are needed to determine how TP53 haplotypes or loss of alleles interact with mutations to modulate their impact on cancer development and prognosis.

The clinical value of somatic TP53 gene mutations in 1,794 patients with breast cancer.

To investigate the clinical value of somatic TP53 mutations in breast cancer, we assembled clinical and molecular data on 1,794 women with primary breast cancer with long-term follow-up and whose tumor has been screened for mutation in exons 5 to 8 of TP53 by gene sequencing. TP53 mutations were more frequent in tumors of ductal and medullar types, aggressive phenotype (high grade, large size, node positive cases, and low hormone receptor content) and in women <60 years old. TP53 mutations within exons 5 to 8 conferred an elevated risk of breast cancer-specific death of 2.27 (relative risk >10 years; P < 0.0001) compared with patients with no such mutation. The prognostic value of TP53 mutation was independent of tumor size, node status, and hormone receptor content, confirming and reconciling previous findings in smaller series. Moreover, an interaction between TP53 mutation and progesterone receptor (PR) status was revealed, TP53 mutation combined with the absence of progesterone receptor being associated with the worst prognosis. Whereas previous studies have emphasized the fact that missense mutations in the DNA-binding motifs have a worse prognosis than missense mutations outside these motifs, we show that non-missense mutations have prognostic value similar to missense mutations in DNA-binding motifs. Nonetheless, specific missense mutants (codon 179 and R248W) seem to be associated with an even worse prognosis. These results, obtained on the largest series analyzed thus far, show that TP53 mutations identified by gene sequencing have an independent prognostic value in breast cancer and could have potential uses in clinical practice.

Computational approaches for predicting the biological effect of p53 missense mutations: a comparison of three sequence analysis based methods

Prediction of the biological effect of missense substitutions has become important because they are often observed in known or candidate disease susceptibility genes. In this paper, we carried out a 3-step analysis of 1514 missense substitutions in the DNA-binding domain (DBD) of TP53, the most frequently mutated gene in human cancers. First, we calculated two types of conservation scores based on a TP53 multiple sequence alignment (MSA) for each substitution: (i) Grantham Variation (GV), which measures the degree of biochemical variation among amino acids found at a given position in the MSA; (ii) Grantham Deviation (GD), which reflects the ‘biochemical distance’ of the mutant amino acid from the observed amino acid at a particular position (given by GV). Second, we used a method that combines GV and GD scores, Align-GVGD, to predict the transactivation activity of each missense substitution. We compared our predictions against experimentally measured transactivation activity (yeast assays) to evaluate their accuracy. Finally, the prediction results were compared with those obtained by the program Sorting Intolerant from Tolerant (SIFT) and Dayhoffs classification. Our predictions yielded high prediction accuracy for mutants showing a loss of transactivation (∼88% specificity) with lower prediction accuracy for mutants with transactivation similar to that of the wild-type (67.9 to 71.2% sensitivity). Align-GVGD results were comparable to SIFT (88.3 to 90.6% and 67.4 to 70.3% specificity and sensitivity, respectively) and outperformed Dayhoffs classification (80 and 40.9% specificity and sensitivity, respectively). These results further demonstrate the utility of the Align-GVGD method, which was previously applied to BRCA1. Align-GVGD is available online at .

Biological functions of p53 isoforms through evolution: lessons from animal and cellular models

The TP53 tumour-suppressor gene is expressed as several protein isoforms generated by different mechanisms, including use of alternative promoters, splicing sites and translational initiation sites, that are conserved through evolution and within the TP53 homologues, TP63 and TP73. Although first described in the eighties, the importance of p53 isoforms in regulating the suppressive functions of p53 has only become evident in the last 10 years, by analogy with observations that p63 and p73 isoforms appeared indispensable to fully understand the biological functions of TP63 and TP73. This review summarizes recent advances in the field of ‘p53 isoforms’, including new data on p63 and p73 isoforms. Details of the alternative mechanisms that produce p53 isoforms and cis- and trans-regulators identified are provided. The main focus is on their biological functions (apoptosis, cell cycle, aging and so on) in cellular and animal models, including mouse, zebrafish and Drosophila. Finally, the deregulation of p53 isoform expression in human cancers is reviewed. Based on these latest results, several developments are expected in the future: the identification of drugs modulating p53 isoform expression; the generation of animal models and the evaluation of the use of p53 isoform as biomarkers in human cancers.

Noninvasive diagnosis of actionable mutations by deep sequencing of circulating free DNA in lung cancer from never-smokers: a proof-of-concept study from BioCAST/IFCT-1002.

Purpose: Tumor somatic mutation analysis is part of the standard management of metastatic lung cancer. However, physicians often have to deal with small biopsies and consequently with challenging mutation testing. Circulating free DNA (cfDNA) is a promising tool for accessing the tumor genome as a liquid biopsy. Here, we evaluated next-generation sequencing (NGS) on cfDNA samples obtained from a consecutive series of patients for the screening of a range of clinically relevant mutations. Experimental Design: A total of 107 plasma samples were collected from the BioCAST/IFCT-1002 lung cancer study (never-smokers cohort). Matched tumor DNA (tDNA) was obtained for 68 cases. Multiplex PCR-based assays were designed to target specific coding regions in EGFR, KRAS, BRAF, ERBB2, and PI3KCA genes, and amplicon sequencing was performed at deep coverage on the cfDNA/tDNA pairs using the NGS IonTorrent Personal Genome Machine Platform. Results: CfDNA concentration in plasma was significantly associated with both stage and number of metastatic sites. In tDNA, 50 mutations (36 EGFR, 5 ERBB2, 4 KRAS, 3 BRAF, and 2 PIK3CA) were identified, of which 26 were detected in cfDNA. Sensitivity of the test was 58% (95% confidence interval, 43%–71%) and the estimated specificity was 87% (62%–96%). Conclusion: These data demonstrate the feasibility and potential utility of mutation screening in cfDNA using IonTorrent NGS for the detection of a range of tumor biomarkers in patients with metastatic lung cancer. Clin Cancer Res; 20(17); 4613–24. ©2014 AACR.

Sarcomas in TP53 germline mutation carriers: a review of the IARC TP53 database.

Sarcoma is the index diagnosis of Li‐Fraumeni syndrome (LFS), a familial predisposition to cancer that also includes brain cancer, breast cancer, and adrenal cortical carcinoma. Germline mutations in the TP53 gene are detected in approximately 80% of families that fulfill LFS criteria and in 15% to 25% of families that fulfill criteria for Li‐Fraumeni‐like syndrome (LFS), a group of related syndromes with broader clinical criteria.

TP53 Variations in Human Cancers: New Lessons from the IARC TP53 Database and Genomics Data

TP53 gene mutations are one of the most frequent somatic events in cancer. The IARC TP53 Database (http://p53.iarc.fr) is a popular resource that compiles occurrence and phenotype data on TP53 germline and somatic variations linked to human cancer. The deluge of data coming from cancer genomic studies generates new data on TP53 variations and attracts a growing number of database users for the interpretation of TP53 variants. Here, we present the current contents and functionalities of the IARC TP53 Database and perform a systematic analysis of TP53 somatic mutation data extracted from this database and from genomic data repositories. This analysis showed that IARC has more TP53 somatic mutation data than genomic repositories (29,000 vs. 4,000). However, the more complete screening achieved by genomic studies highlighted some overlooked facts about TP53 mutations, such as the presence of a significant number of mutations occurring outside the DNA‐binding domain in specific cancer types. We also provide an update on TP53 inherited variants including the ones that should be considered as neutral frequent variations. We thus provide an update of current knowledge on TP53 variations in human cancer as well as inform users on the efficient use of the IARC TP53 Database.

Tumor protein 53 mutations and inherited cancer: Beyond Li-Fraumeni syndrome

Purpose of review Germline TP53 (tumor protein 53) mutations are the molecular basis of a complex cancer predisposition syndrome, the Li-Fraumeni syndrome. The present review discusses the diversity of tumor patterns in TP53 mutation carriers, focusing on molecular factors that may explain familial and individual differences, such as genotype/phenotype correlations, genetic modifiers and genetic anticipation. Recent findings Initially identified 20 years ago, germline TP53 mutations appear to be associated with an extremely diverse range of cancers. Although no other gene has been found in Li-Fraumeni syndrome, recent results show that the functional effects of particular mutations, polymorphisms in TP53 or in regulators such as MDM2 (murine double minute 2), variations in DNA copy number and variations in telomere length, have a strong impact on individual risk and on tumor patterns. Furthermore, recent studies in large cohorts suggest that TP53 germline mutations may occur in up to 1: 5000 individuals. Summary Germline TP53 mutations may be responsible for a large fraction (15–20%) of all inherited cancers. Although mutations are detectable by sequencing, counseling and follow-up remain problematic due to the wide variations in disease presentation. Elucidating the molecular mechanisms underlying the predisposition caused by TP53 deficiency may help to develop better, evidence-based and personalized clinical protocols.