Carcinogenesis Advance Access published online on January 16, 2004
Carcinogenesis, doi:10.1093/carcin/bgh068
© 2004 by Oxford University Press
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CANCER BIOLOGY
1 School of Biosciences, Cardiff University, CF10 3US, UK; Biostatistics & Bioinformatics Unit, University of Wales College of Medicine, CF14 4XN, UK
* Corresponding author. E-mail: lewispd{at}cf.ac.uk.
Received 7 August 2003
; revised 14 November 2003
; accepted 16 December 2003
For cancer one of the primary aims of molecular epidemiology is to identify the endogenous or exogenous cause of mutations within a gene. Regarding exogenous mutagens, much mutation data has become available via in vitro and in vivo mutation assays and become publicly available through mutation databases such as the Mammalian Gene Mutation Database ((http://lisntweb.swan.ac.uk/cmgt/index.htm). One particular mutation assay incorporates the bacterial supF tRNA gene which allows selection of mutation at virtually all nucleotides. We have developed an algorithm called LwPy53 that utilises mutation data from supF that can be used to predict chemically-induced hotspots along the p53 gene. The prediction is based on a number of parameters: the mutability of supF dinucleotides after treatment by a mutagen of interest; DNA curvature along the p53 gene; the selectability of a mutation along the gene; the likelihood of a site being within a nucleosome. We applied LwPy53 to exons 5, 7 and 8 of the p53 using benzo(a)pyrene diolepoxide (BPDE) induced mutation data for supF to obtain a predicted BPDE G>T transversion spectrum after hypothetical treatment with BPDE. The resulting predicted mutation distribution reveals strong mutation hotspots at codons 157, 248 and 273 that correlate with known BPDE adduct hotspots within p53. The predicted BPDE spectrum strongly resembles the G>T mutation spectrum compiled from known lung cancer mutation data from smokers and further supports evidence that BPDE contributes to the overall smoking related mutation distribution in lung cancer. The algorithm shows how BPDE target sequence specificity and DNA curvature both shape the overall mutation distribution
In silico p53 mutation hotspots in lung cancer
2 Centre for Molecular & Genetic Toxicology, School of Biological Sciences, University of Wales Swansea, SA2 8PP, UK
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