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Analysis of KLLN as a high-penetrance breast cancer predisposition gene

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Abstract

KLLN is a p53 target gene with DNA binding function and represents a highly plausible candidate breast cancer predisposition gene. We screened for predisposing variants in 860 high-risk breast cancer families using high resolution melt analysis. A germline c.339_340delAG variant predicted to cause premature termination of the protein after 57 alternative amino acid residues was identified in 3/860 families who tested negative for BRCA1 and BRCA2 mutations and in 1/84 sporadic breast cancer cases. However, the variant was also detected in 2/182 families with known BRCA1 or BRCA2 mutations and in 2/464 non-cancer controls. Furthermore, loss of the mutant allele was detected in 2/2 breast tumors. Our data suggest that pathogenic mutations in KLLN are rare in breast cancer families and the c.339_340delAG variant does not represent a high-penetrance breast cancer risk allele.

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References

  1. Mann GJ, Thorne H, Balleine RL, Butow PN, Clarke CL, Edkins E, Evans GM, Fereday S, Haan E, Gattas M, Giles GG, Goldblatt J, Hopper JL, Kirk J, Leary JA, Lindeman G, Niedermayr E, Phillips KA, Picken S, Pupo GM, Saunders C, Scott CL, Spurdle AB, Suthers G, Tucker K, Chenevix-Trench G (2006) Analysis of cancer risk and BRCA1 and BRCA2 mutation prevalence in the kConFab familial breast cancer resource. Breast Cancer Res 8(1):R12. doi:10.1186/bcr1377

    Article  PubMed  Google Scholar 

  2. Cho YJ, Liang P (2008) Killin is a p53-regulated nuclear inhibitor of DNA synthesis. Proc Natl Acad Sci USA 105(14):5396–5401. doi:10.1073/pnas.0705410105

    Article  PubMed  CAS  Google Scholar 

  3. Bennett KL, Mester J, Eng C (2010) Germline epigenetic regulation of KILLIN in Cowden and Cowden-like syndrome. JAMA 304(24):2724–2731. doi:10.1001/jama.2010.1877

    Article  PubMed  CAS  Google Scholar 

  4. Eccles DM, Englefield P, Soulby MA, Campbell IG (1998) BRCA1 mutations in southern England. Br J Cancer 77:2199–2203

    Article  PubMed  CAS  Google Scholar 

  5. Bryan EJ, Watson RH, Davis M, Hitchcock A, Foulkes WD, Campbell IG (1996) Localization of an ovarian cancer tumor suppressor gene to a 0.5-cM region between D22S284 and CYP2D, on chromosome 22q. Cancer Res 56(4):719–721

    PubMed  CAS  Google Scholar 

  6. Baxter SW, Choong DY, Eccles DM, Campbell IG (2001) Polymorphic variation in CYP19 and the risk of breast cancer. Carcinogenesis 22(2):347–349

    Article  PubMed  CAS  Google Scholar 

  7. Rozen S, Skaletsky H (2000) Primer3 on the WWW for general users and for biologist programmers. Methods Mol Biol 132:365–386

    PubMed  CAS  Google Scholar 

  8. Gorringe KL, Choong DY, Williams LH, Ramakrishna M, Sridhar A, Qiu W, Bearfoot JL, Campbell IG (2008) Mutation and methylation analysis of the chromodomain-helicase-DNA binding 5 gene in ovarian cancer. Neoplasia 10(11):1253–1258

    PubMed  CAS  Google Scholar 

  9. Jacobs S, Thompson ER, Nannya Y, Yamamoto G, Pillai R, Ogawa S, Bailey DK, Campbell IG (2007) Genome-wide, high-resolution detection of copy number, loss of heterozygosity, and genotypes from formalin-fixed, paraffin-embedded tumor tissue using microarrays. Cancer Res 67(6):2544–2551. doi:10.1158/0008-5472.CAN-06-3597

    Article  PubMed  CAS  Google Scholar 

  10. Knudson AG Jr (1971) Mutation and cancer: statistical study of retinoblastoma. Proc Natl Acad Sci USA 68(4):820–823

    Article  PubMed  Google Scholar 

  11. Cavenee WK, Hansen MF, Nordenskjold M, Kock E, Maumenee I, Squire JA, Phillips RA, Gallie BL (1985) Genetic origin of mutations predisposing to retinoblastoma. Science 228(4698):501–503

    Article  PubMed  CAS  Google Scholar 

  12. Ng PC, Henikoff S (2001) Predicting deleterious amino acid substitutions. Genome Res 11(5):863–874. doi:10.1101/gr.176601

    Article  PubMed  CAS  Google Scholar 

  13. Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, Kondrashov AS, Sunyaev SR (2010) A method and server for predicting damaging missense mutations. Nat Methods 7(4):248–249. doi:10.1038/nmeth0410-248

    Article  PubMed  CAS  Google Scholar 

  14. Li B, Krishnan VG, Mort ME, Xin F, Kamati KK, Cooper DN, Mooney SD, Radivojac P (2009) Automated inference of molecular mechanisms of disease from amino acid substitutions. Bioinformatics 25(21):2744–2750. doi:10.1093/bioinformatics/btp528

    Article  PubMed  CAS  Google Scholar 

  15. Ferrer-Costa C, Gelpi JL, Zamakola L, Parraga I, de la Cruz X, Orozco M (2005) PMUT: a web-based tool for the annotation of pathological mutations on proteins. Bioinformatics 21(14):3176–3178

    Article  PubMed  CAS  Google Scholar 

  16. Schwarz JM, Rodelsperger C, Schuelke M, Seelow D (2010) MutationTaster evaluates disease-causing potential of sequence alterations. Nat Methods 7(8):575–576. doi:10.1038/nmeth0810-575

    Article  PubMed  CAS  Google Scholar 

  17. Bromberg Y, Rost B (2007) SNAP: predict effect of non-synonymous polymorphisms on function. Nucleic Acids Res 35(11):3823–3835. doi:10.1093/nar/gkm238

    Article  PubMed  CAS  Google Scholar 

  18. The 1000 Genomes Project Consortium (2010) A map of human genome variation from population-scale sequencing. Nature 467(7319):1061–1073. doi:10.1038/nature09534

    Article  Google Scholar 

  19. Haga H, Yamada R, Ohnishi Y, Nakamura Y, Tanaka T (2002) Gene-based SNP discovery as part of the Japanese Millennium Genome Project: identification of 190,562 genetic variations in the human genome. Single-nucleotide polymorphism. J Hum Genet 47(11):605–610. doi:10.1007/s100380200092

    Article  PubMed  CAS  Google Scholar 

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Acknowledgments

This work was supported by the Victorian Breast Cancer Research Consortium.

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The authors declare no conflicts of interest.

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Correspondence to Ian G. Campbell.

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IGC and GM conceived of the study; ERT and DYHC carried out experiments and analyzed data; KLG interpreted data and generated the figure; IGC, KLG, and ERT were involved in writing the paper. All authors had final approval of the submitted and published versions.

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Thompson, E.R., Gorringe, K.L., Choong, D.Y.H. et al. Analysis of KLLN as a high-penetrance breast cancer predisposition gene. Breast Cancer Res Treat 134, 543–547 (2012). https://doi.org/10.1007/s10549-012-2088-3

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  • DOI: https://doi.org/10.1007/s10549-012-2088-3

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