Polygenic Inherited Predisposition to Breast Cancer

Department of Oncology & Public Health & Cancer Research UK Genetic Epidemiology Unit, Strangeways Research Laboratories, University of Cambridge, UK.
Cold Spring Harbor Symposia on Quantitative Biology 02/2005; 70:35-41. DOI: 10.1101/sqb.2005.70.029
Source: PubMed


The known breast cancer predisposing genes account for only about 20% of inherited susceptibility. Epidemiological analyses suggest that much of the remaining 80% is explained by the combined effect of many individually weak genetic variants, rather than by further rare, highly penetrant mutations. In the near term, identification of variants may indicate new pathways or mechanisms in breast cancer development. The polygenic model implies a wide distribution of risk in the population. In the longer term, it may be possible to construct individual risk profiles to guide public health interventions. The search for genetic variants has so far proved difficult. A key unanswered question is the "genetic architecture" of predisposition-that is, strong or weak alleles, common or rare. We describe a genome-wide scan designed to provide a first-pass answer to this question.

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    • "A family history of breast cancer and/or ovarian cancer is among the strongest known risk factors. Approximately 5–10% of breast cancers result from inheritance of rare, but highly to moderately penetrant, mutations in a small number of well-studied tumor suppressor genes, including BRCA1 and BRCA2 (Ponder et al. 2005). More recently, genome-wide association studies (GWAS) have localized within the human genome more than 70 common genetic variants that act as low-penetrance determinants of breast cancer risk, and together these variants are estimated to explain approximately 15% of heritable risk Copyright © 2014 Colletti II et al. doi: 10.1534/g3.114.011163 "
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    ABSTRACT: When treated with 17β-estradiol, female ACI rats (Rattus norvegicus) rapidly develop mammary cancers that share multiple phenotypes with luminal breast cancers. Seven distinct quantitative trait loci that harbor genetic determinants of susceptibility to 17β-estradiol-induced mammary cancer have been mapped in reciprocal intercrosses between susceptible ACI rats and resistant Brown Norway (BN) rats. A panel of unique congenic rat strains has now been generated and characterized to confirm the existence of these quantitative trait loci, designated Emca3 through Emca9, and to quantify their individual effects on susceptibility to 17β-estradiol-induced mammary cancer. Each congenic strain carries BN alleles spanning an individual Emca locus, introgressed onto the ACI genetic background. Data presented herein indicate that BN alleles at Emca3, Emca4, Emca5, Emca6 and Emca9 reduce susceptibility to 17β-estradiol-induced mammary cancer, whereas BN alleles at Emca7 increase susceptibility, thereby confirming the previous interval mapping data. All of these Emca loci are orthologous to regions of the human genome that have been demonstrated in genome wide association studies to harbor genetic variants that influence breast cancer risk. Moreover, four of the Emca loci are orthologous to loci in humans that have been associated with mammographic breast density, a biomarker of breast cancer risk. This study further establishes the relevance of the ACI and derived congenic rat models of 17β-estradiol-induced mammary cancer for defining the genetic bases of breast cancer susceptibility and elucidating the mechanisms through which 17β-estradiol contributes to breast cancer development.
    G3-Genes Genomes Genetics 05/2014; 4(8). DOI:10.1534/g3.114.011163 · 3.20 Impact Factor
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    • "Genetic counselling can then be provided, based on mutation screening. A significant proportion of the families are not associated with mutations in BRCA1 or BRCA2 or other known genes [2-5] and may in part be explained by recessive alleles or a polygenic model with risk variants of lower penetrance jointly affecting risk in miscellaneous combinations [6-8]. However, the gene most recently identified, RAD51C [9], demonstrates that some proportion may still have a high-risk-allele cause. "
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    ABSTRACT: A significant proportion of high-risk breast cancer families are not explained by mutations in known genes. Recent genome-wide searches (GWS) have not revealed any single major locus reminiscent of BRCA1 and BRCA2, indicating that still unidentified genes may explain relatively few families each or interact in a way obscure to linkage analyses. This has drawn attention to possible benefits of studying populations where genetic heterogeneity might be reduced. We thus performed a GWS for linkage on nine Icelandic multiple-case non-BRCA1/2 families of desirable size for mapping highly penetrant loci. To follow up suggestive loci, an additional 13 families from other Nordic countries were genotyped for selected markers. GWS was performed using 811 microsatellite markers providing about five centiMorgan (cM) resolution. Multipoint logarithm of odds (LOD) scores were calculated using parametric and nonparametric methods. For selected markers and cases, tumour tissue was compared to normal tissue to look for allelic loss indicative of a tumour suppressor gene. The three highest signals were located at chromosomes 6q, 2p and 14q. One family contributed suggestive LOD scores (LOD 2.63 to 3.03, dominant model) at all these regions, without consistent evidence of a tumour suppressor gene. Haplotypes in nine affected family members mapped the loci to 2p23.2 to p21, 6q14.2 to q23.2 and 14q21.3 to q24.3. No evidence of a highly penetrant locus was found among the remaining families. The heterogeneity LOD (HLOD) at the 6q, 2p and 14q loci in all families was 3.27, 1.66 and 1.24, respectively. The subset of 13 Nordic families showed supportive HLODs at chromosome 6q (ranging from 0.34 to 1.37 by country subset). The 2p and 14q loci overlap with regions indicated by large families in previous GWS studies of breast cancer. Chromosomes 2p, 6q and 14q are candidate sites for genes contributing together to high breast cancer risk. A polygenic model is supported, suggesting the joint effect of genes in contributing to breast cancer risk to be rather common in non-BRCA1/2 families. For genetic counselling it would seem important to resolve the mode of genetic interaction.
    Breast cancer research: BCR 07/2010; 12(4):R50. DOI:10.1186/bcr2608 · 5.49 Impact Factor
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    ABSTRACT: Breast cancer (BC) is a complex disease, and the incidence rates for BC increase with age. Both environmental factors and genetics have an impact on the risk of BC. Although the effects of environmental factors may vary with age, it has been assumed generally that the penetrance of single nucleotide polymorphisms (SNPs) is constant throughout life. In the current study, the results demonstrated that certain SNPs exhibit BC risk associations that vary considerably with age. SNPs in 12 steroid hormone pathway genes were investigated for associations with BC risk in white women who were enrolled in an age-matched, case-control (1:2 for cases and controls, respectively) study that consisted of a discovery set (n = 5000 women) and an independent validation set (n = 1583 women). Significant age-related trends were identified and confirmed for SNPs in 4 genes associated with BC risk. The cytosine/cytosine (C/C) genotype of cytochrome P450 XIB2 (CYP11B2) was associated with decreased risk at younger ages (ages 30-44 years) but an increased risk at older ages (ages 55-69 years). The homozygous cytosine-guanine (CG/CG) genotype of uridine phosphorylase glycosyltransferase 1A7 (UGT1A7) was associated with increased risk at younger ages but decreased risk at older ages. Associations in cytochrome P450 19 (CYP19) and progesterone receptor (PGR) were confined to middle age (ages 45-54 years). The identification of age-specific genetic associations may have profound implications for future etiologic studies of BC and for the use of SNP genotyping to accurately predict the risk of BC in women.
    Cancer 05/2007; 109(10):1940-8. DOI:10.1002/cncr.22634 · 4.89 Impact Factor
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