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Breast Cancer Research

Open Access

Large-scale single nucleotide polymorphism analysis of candidates for low-penetrance breast cancer genes

  • A Vega1, 2,
  • A Salas2, 3,
  • C Phillips2,
  • B Sobrino2,
  • B Carracedo2,
  • C Ruíz-Ponte1, 2,
  • R Rodríguez-López4,
  • G Rivas4,
  • J Benítez4 and
  • A Carracedo1, 2, 3
Breast Cancer Research20057(Suppl 2):P1.14

https://doi.org/10.1186/bcr1101

Published: 17 June 2005

Keywords

Breast CancerBreast Cancer RiskFamilial Breast CancerHereditary Breast CancerGenotyping Platform

BRCA1 and BRCA2 are high-penetrance genes that account for around 25% of families with hereditary breast cancer [1]. Given that no additional high-penetrance susceptibility genes have been found to be involved in breast cancer, it has been proposed that different genetic backgrounds due to the combination of low-penetrance genes (polygenic mechanism) could explain the remaining familial breast cancer risk [2]. Hence there is much interest in the search for low-penetrance gene/variants for breast cancer, which exist with high prevalence in the general population.

Single nucleotide polymorphisms (SNPs) have emerged as genetic markers of choice because of their high density and relatively even distribution in the human genomes [3, 4], and are being using for fine mapping of disease loci and for candidate gene association studies. Approximately 10 million SNPs have been identified across the human genome and new technologies are available today for high-throughput genotyping.

In this study we used the SNPlex (Applied Biosystems, Foster City, CA, USA) high-throughput genotyping platform, which allows the study of up to 48 SNPs simultaneously, to study 984 SNPs of 92 cancer-related genes, in a total of 480 female cases of breast cancer and 480 female controls.

Gene selection was made on the basis of their involvement in different cancer pathways and genes: DNA reparation, cell cycle control, BRCA1-associated binding proteins, and so on. SNP selection was performed using an indirect approach (1 SNP/10 kb) and based on the individual allele frequency (FAM ≤ 10%) in the European population, using public and private SNP databases and bioinformatics tools (dbSNP, HapMap, Sequenom Real SNP, PUPASNPI Ensembl, and Celera, among others).

To date, 415 SNPs from 44 genes have been genotyped in nine SNPlex pools. A case–control analysis was conducted for the 318 remaining SNPs. Preliminary results showed association in 24 SNPs from 12 candidate genes (P < 0.05). We will present the analysis of the remaining 48 genes at the time of the congress.

Declarations

Acknowledgments

This work was supported by grants from the Ministerio de Sanidad y Consumo (Fondo de Investigación Sanitaria; Instituto de Salud Carlos III, PI030893; SCO/3425/2002) and Genoma España (CeGen; Centro Nacional de Genotipado; Nodo Santiago de Compostela).

Authors’ Affiliations

(1)
Fundación Pública Galega de Medicina Xenómica, Hospital Clínico Universitario, Universidad de Santiago de Compostela, Galicia, Spain
(2)
Centro Nacional de Xenotipado, Hospital Clínico Universitario, Santiago de Compostela, Spain
(3)
Unidade de Xenética, Instituto de Medicina Legal, Facultad de Medicina, Universidad de Santiago de Compostela, Galicia, Spain
(4)
Departamento de Genética Humana, Centro Nacional Investigaciones Oncológicas, Madrid, Spain

References

  1. Ford D, Easton DF, Stratton M, Narod S, Goldgar D, Devilee P, Bishop DT, Weber B, Lenoir G, Chang-Claude J, et al: Genetic heterogeneity and penetrance analysis of the BRCA1 and BRCA2 genes in breast cancer families. Breast Cancer Linkage Consortium. Am J Hum Genet. 1998, 62: 676-689. 10.1086/301749.View ArticlePubMedPubMed CentralGoogle Scholar
  2. Pharoah PD, Antoniou A, Bobrow M, Zimmern RL, Easton DF, Ponder BA: Polygenic susceptibility to breast cancer and implications for prevention. Nat Genet. 2002, 31: 33-36. 10.1038/ng853.View ArticlePubMedGoogle Scholar
  3. Kruglyak L: Prospects for whole-genome linkage disequilibrium mapping of common disease genes. Nat Genet. 1999, 22: 139-144. 10.1038/9642.View ArticlePubMedGoogle Scholar
  4. Venter JC, Adams MD, Myers EW, Li PW, Mural RJ, Sutton GG, et al: The sequence of the human genome. Science. 2001, 291: 1304-1351. 10.1126/science.1058040.View ArticlePubMedGoogle Scholar

Copyright

© BioMed Central 2005

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