New approaches to understanding p53 gene tumor mutation spectra

doi:10.1016/S0027-5107(99)00162-1

Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis

Volume 431, Issue 2, 17 December 1999, Pages 199-209

https://doi.org/10.1016/S0027-5107(99)00162-1 Get rights and content

Abstract

The first p53 gene mutation arising in a human tumor was described a decade ago by Baker et al. [S.J. Baker, E.R. Fearon, J.M. Nigro, S.R. Hamilton, A.C. Preisinger, J.M. Jessup, P. van Tuinen, D.H. Ledbetter, D.F. Barker, Y. Nakamura, R. White, B. Vogelstein, Chromosome 17 deletions and p53 gene mutations in colorectal carcinomas, Science 244 (1989) 217–221]. There are now over 10,000 mutations extracted from the published literature in the IARC database of human p53 tumor mutations [P. Hainaut, T. Hernandez, A. Robinson, P. Rodriguez-Tome, T. Flores, M. Hollstein, C.C. Harris, R. Montesano, IARC database of p53 gene mutations in human tumors and cell lines: updated compilation, revised formats and new visualization tools, Nucleic Acids Res. 26 (1998) 205–213; Version R3, January 1999]. A large and diverse collection of tumor mutations in cancer patients provides important information on the nature of environmental factors or biological processes that are important causes of human gene mutation, since xenobiotic mutagens as well as endogenous mechanisms of genetic change produce characteristic types of patterns in target DNA [J.H. Miller, Mutational specificity in bacteria, Annu. Rev. Genet. 17 (1983) 215–238; T. Lindahl, Instability and decay of the primary structure of DNA, Nature 362 (1993) 709–715; S.P. Hussain, C.C. Harris, Molecular epidemiology of human cancer: contribution of mutation spectra studies of tumor suppressor genes, Cancer Res. 58 (1998) 4023–4037; P. Hainaut, M. Hollstein, p53 and human cancer: the first ten thousand mutations, Adv. Cancer Res. 2000]. P53 gene mutations in cancers can be compared to point mutation spectra at the HPRT locus of human lymphocytes from patients or healthy individuals with known exposure histories, and accumulated data indicate that mutation patterns at the two loci share certain general features.

Hypotheses regarding specific cancer risk factors can be tested by comparing p53 tumor mutations typical of a defined patient group against mutations generated experimentally in rodents or in prokaryotic and eukaryotic cells in vitro. Refinements of this approach to hypothesis testing are being explored that employ human p53 sequences introduced artificially into experimental organisms used in laboratory mutagenesis assays. P53-specific laboratory models, combined with DNA microchips designed for high through-put mutation screening promise to unmask information currently hidden in the compilation of human tumor p53 mutations.

Section snippets

Introduction: basic features of p53 human tumor mutations

The p53 gene encodes a multi-functional transcription factor that participates in cell-cycle control, programmed cell death, senescence differentiation, development, genomic stability, DNA replication, transcription and repair [4], [5]. These activities are mediated by direct binding of the p53 tetramer to specific target sequence motifs in promoters of downstream effector genes, and by interactions between p53 and other cellular proteins [6], [7].

The specific DNA binding domain of the p53

The p53 mutation database: Pandora's box or Rosetta stone?

Although there is controversy and uncertainty in interpretation of p53 tumor spectra, evidence is unequivocal showing that mutation patterns and frequency can vary dramatically by cancer type and/or by patient exposure category [4], [13]. Particularly convincing are differences that have been corroborated by independent investigators, are supported by data from laboratory experiments, achieve statistical significance, and suggest a plausible biological explanation [3]. Three often-cited

Mutation screening technology: the DNA microchip

A major stumbling block in interpreting mutation patterns derived from inspection of the p53 database is the failure to achieve statistical significance, or reports of positive correlations that are, in fact, chance findings, both consequences of small sample size. Although the 10,000 mutations in the IARC database (Release 3, 1999) are impressive when considered as a whole, the number of mutations observed within a single tumor subclassification, and identified within a homogeneous patient

Acknowledgements

MCH thanks H. Vrieling for helpful discussion. Gene-targeting studies are supported in part by PHS R01 CA 79493-01 to MCH and ZQW.

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New approaches to understanding p53 gene tumor mutation spectra

Abstract

Section snippets

Introduction: basic features of p53 human tumor mutations

The p53 mutation database: Pandora's box or Rosetta stone?

Mutation screening technology: the DNA microchip

Acknowledgements

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Mutat. Res.

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IARC database of p53 gene mutations in human tumors and cell lines: updated compilation, revised formats and new visualization tools

Nucleic Acids Res.

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Nature

Molecular epidemiology of human cancer: contribution of mutation spectra studies of tumor suppressor genes

Cancer Res.

p53 and human cancer: the first ten thousand mutations

Adv. Cancer Res.

P53 modulation of TFIIH-associated nucleotide excision repair activity

Nat. Genet.

Nucleic Acids Res.

Crystal structure of a p53 tumor suppressor–DNA complex: understanding tumorigenic mutations

Science

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