Abstract
Deciding whether a missense allelic variant affects protein function is important in many contexts. We previously demonstrated that a detailed analysis of p53 intragenic conservation correlates with somatic mutation hotspots. Here we refine these evolutionary studies and expand them to the p16/Ink4a gene. We calculated that in order for ‘absolute conservation’ of a codon across multiple species to achieve P<0.05, the evolutionary substitution database must contain at least 3(M) variants, where M equals the number of codons in the gene. Codons in p53 were divided into high (73% of codons), intermediate (29% of codons), and low (0 codons) likelihood of being mutation hotspots. From a database of 263 somatic missense p16 mutations, we identified only four codons that are mutational hotspots at P<0.05 (8 mutations). However, data on function, structure, and disease association support the conclusion that 11 other codons with ≥5 somatic mutations also likely indicate functionally critical residues, even though P0.05. We calculated p16 evolution using amino acid substitution matrices and nucleotide substitution distances. We looked for evolutionary parameters at each codon that would predict whether missense mutations were disease associated or disrupted function. The current p16 evolutionary substitution database is too small to determine whether observations of ‘absolute conservation’ are statistically significant. Increasing the number of sequences from three to seven significantly improved the predictive value of evolutionary computations. The sensitivity and specificity for conservation scores in predicting disease association of p16 codons is 70–80%. Despite the small p16 sequence database, our calculations of high conservation correctly predicted loss of cell cycle arrest function in 75% of tested codons, and low conservation correctly predicted wild-type function in 80–90% of codons. These data validate our hypothesis that detailed evolutionary analyses help predict the consequences of missense amino-acid variants.
This is a preview of subscription content, access via your institution
Access options
Subscribe to this journal
Receive 50 print issues and online access
$259.00 per year
only $5.18 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
References
Bottema CDK, Ketterling RP, Li S, Yoon H-S, Phillips JA and Sommer SS . (1991). Am. J. Hum. Genet., 49, 820–838.
Ciotti P, Struewing JP, Mantelli M, Chompret A, Avril MF, Santi PL, Tucker MA, Bianchi-Scarra G, Bressac-de Paillerets B and Goldstein AM . (2000) Am. J. Hum. Genet., 67, 311–319.
Fitch WM . (1971). Systematic Zool., 20, 406–416.
Greenblatt MS, Bennett WP, Hollstien M and Harris CC . (1994) Cancer Res., 55, 4855–4878.
Greenblatt MS, Grollman AP and Harris CC . (1996) Cancer Res., 56, 2130–2136.
Greenblatt MS, Chappuis PO, Bond JP, Hamel N and Foulkes WD . (2001) Cancer Res., 61, 4092–4097.
Henikoff S and Henikoff JG . (1993) Proteins, 17, 49–61.
Ina Y . (1995) J. Mol. Evol., 40, 190–226.
International Human Genome Sequencing Consortium, (2001). Nature, 409, 860–921.
Li W-H . (1997). Molecular Evolution, Sinauer Associates: Sunderland, MA.
Makalowski W and Boguski MS . (1998). Proc. Natl. Acad. Sci. USA, 95, 9407–9412.
Miller MP and Kumar S . (2001). Hum. Mol. Genet., 10, 2319–2328.
Pollock PM, Pearson JV, Hayward NK (1996). Genes Chrom Cancer, 15, 77–78.
Ruas M and Peters G . (1998). Biochim. Biophys. Acta., 1378, F115–F177.
Ruas M, Brookes S, McDonald NQ and Peters G . (1999). Oncogene, 18, 5423–5434.
Russo AA, Tong L, Lee J-O, Jeffery BB and Parletech NP (1998). Nature, 395, 237–243.
Saitou N and Nei M . (1987). Mol. Biol. Evol., 4, 406–425.
Sharpless NE and DePinho RA . (1999). Curr. Opin. Genet. Devel., 9, 22–30.
Smith-Sorensen B and Hovig E . (1996). Hum. Mut., 7, 294–303.
Wacey AI, Krawczak M, Kakkar VV and Cooper DN . (1994). Hum. Genet., 94, 594–608.
Walker DR, Bond JP, Tarone RE, Harris CC, Makalowski W, Boguski MS and Greenblatt MS . (1999a). Oncogene, 18, 211–219.
Walker GJ, Gabrielli BG, Castellano M and Hayward NK . (1999b). Int. J. Cancer, 82, 305–312.
Yang Z . (1997). Comput. Appl. Biosci., 5, 555–556.
Yang Z and Kumar S . (1996). Mol. Biol. Evol., 13, 650–659.
Yarbrough WG, Buckmire RA, Bessho M and Liu ET . (1999). J. Natl. Cancer Inst., 91, 1569–1574.
Acknowledgements
We thank Tim Hunter, Mary Lou Shane, and Scott Tighe of the Vermont Cancer Center (VCC) for their technical support, and Takamaru Ashikaga, PhD, Director of the VCC Biostatistics Shared Resource, for assistance with statistical issues. We are grateful to the laboratory of the late Dr Norman Lassam, University of Toronto, for supplying p16 wild-type and mutant plasmids. This work was supported by grants to MSG from the American Cancer Society, Inc., Vermont Division, the Wendy Will Case Cancer Fund, Inc., and the Lake Champlain Cancer Research Organization; to JPB from the National Institutes of Health, and to JK from the V Foundation. The automated DNA sequencing was performed in the VCC DNA Analysis Facility, the Flow Cytometry was performed in the VCC Flow Cytometry Facility, and computational analysis was performed in the VCC Molecular Modeling Facility, all supported in part by Cancer Center Support Grant P30CA22435 from the NCI. The views expressed are those of the authors and do not represent the views of the NCI.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Greenblatt, M., Beaudet, J., Gump, J. et al. Detailed computational study of p53 and p16: using evolutionary sequence analysis and disease-associated mutations to predict the functional consequences of allelic variants. Oncogene 22, 1150–1163 (2003). https://doi.org/10.1038/sj.onc.1206101
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/sj.onc.1206101
Keywords
This article is cited by
-
ctDNA detected by ddPCR reveals changes in tumour load in metastatic malignant melanoma treated with bevacizumab
Scientific Reports (2019)
-
Leucine to proline substitution by SNP at position 197 in Caspase-9 gene expression leads to neuroblastoma: a bioinformatics analysis
3 Biotech (2013)
-
In silico study of Alzheimer’s disease in relation to FYN gene
Interdisciplinary Sciences: Computational Life Sciences (2012)
-
Rare, evolutionarily unlikely missense substitutions in CHEK2contribute to breast cancer susceptibility: results from a breast cancer family registry case-control mutation-screening study
Breast Cancer Research (2011)
-
Natural selection and mammalian BRCA1 sequences: elucidating functionally important sites relevant to breast cancer susceptibility in humans
Mammalian Genome (2006)