Easton DF, Eeles RA.. Genome-wide association studies in cancer. Hum Mol Genet 17: R109-R115

Cancer Research UK Genetic Epidemiology Unit, University of Cambridge, Strangeways Research Laboratory, Worts Causeway, Cambridge CB1 8RN, UK.
Human Molecular Genetics (Impact Factor: 6.39). 11/2008; 17(R2):R109-15. DOI: 10.1093/hmg/ddn287
Source: PubMed


Genome-wide association studies (GWAS) provide a powerful approach to identify common, low-penetrance disease loci without
prior knowledge of location or function. GWAS have been conducted in five of the commonest cancer types: breast, prostate,
colorectal and lung, and melanoma, and have identified more than 20 novel disease loci, confirming that susceptibility to
these diseases is polygenic. Many of these loci were detected at low power, indicating that many further loci will probably
be detected with larger studies. For the most part, the loci were not previously suspected to be related to carcinogenesis,
and point to new disease mechanisms. The risks conferred by the susceptibility alleles are low, generally 1.3-fold or less.
The combined effects may, however, be sufficiently large to be useful for risk prediction, and targeted screening and prevention,
particularly as more loci are identified.

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    • "Thus, it is possible that the observed effects of the variants are particularly relevant to populations where Se intake in low. Interestingly, a GWAs carried out in UK identified a locus located close to the SEPP1 gene to be associated with BC risk [49] but it is not known if it is linked to either rs3877899 or rs7579. In addition, the present study population was well characterised in terms of disease stage and HRT, and this may reduce confounding of genetic effects by such factors. "
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    ABSTRACT: Breast cancer (BC) is one of the most common cancers in women. Evidence suggests that genetic variation in antioxidant enzymes could influence BC risk, but to date the relationship between selenoproteins and BC risk remains unclear. In this report, a study population including 975 Danish cases and 975 controls matched for age and hormone replacement therapy (HRT) use was genotyped for five functional single nucleotide polymorphisms (SNPs) in SEPP1, GPX1, GPX4 and the antioxidant enzyme SOD2 genes. The influence of genetic polymorphisms on breast cancer risk was assessed using conditional logistic regression. Additionally pre-diagnosis erythrocyte GPx (eGPx) activity was measured in a sub-group of the population. A 60% reduction in risk of developing overall BC and ductal BC was observed in women who were homozygous Thr carriers for SEPP1 rs3877899. Additionally, Leu carriers for GPX1 Pro198Leu polymorphism (rs1050450) were at ∼2 fold increased risk of developing a non-ductal BC. Pre-diagnosis eGPx activity was found to depend on genotype for rs713041 (GPX4), rs3877899 (SEPP1), and rs1050450 (GPX1) and on HRT use. Moreover, depending on genotype and HRT use, eGPx activity was significantly lower in women who developed BC later in life compared with controls. Furthermore, GPx1 protein levels increased in human breast adenocarcinoma MCF7 cells exposed to β-estradiol and sodium selenite.In conclusion, our data provide evidence that SNPs in SEPP1 and GPX1 modulate risk of BC and that eGPx activity is modified by SNPs in SEPP1, GPX4 and GPX1 and by estrogens. Our data thus suggest a role of selenoproteins in BC development.
    Full-text · Article · Sep 2013 · PLoS ONE
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    • "A number of SNPs have been identified through genome wide association studies (GWAS) as being breast cancer risk SNPs. In many cases these SNPs relate to the risk of developing a particular subtype of disease, often the ER+ type [14]. Overall, the genetic basis of the estrogen receptor cancer sub-types is not well understood and worthy of further analysis [1]. "
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    ABSTRACT: Two major breast cancer sub-types are defined by the expression of estrogen receptors on tumour cells. Cancers with large numbers of receptors are termed estrogen receptor positive and those with few are estrogen receptor negative. Using genome-wide single nucleotide polymorphism genotype data for a sample of early-onset breast cancer patients we developed a Support Vector Machine (SVM) classifier from 200 germline variants associated with estrogen receptor status (p<0.0005). Using a linear kernel Support Vector Machine, we achieved classification accuracy exceeding 93%. The model indicates that polygenic variation in more than 100 genes is likely to underlie the estrogen receptor phenotype in early-onset breast cancer. Functional classification of the genes involved identifies enrichment of functions linked to the immune system, which is consistent with the current understanding of the biological role of estrogen receptors in breast cancer.
    Full-text · Article · Jul 2013 · PLoS ONE
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    • "For this reason, much research effort has been focused on determining genetic variants with low penetrability associated with PCa. Recently, genome-wide association studies (GWAS) have provided a new approach in determining common genetic variants associated with human diseases, including malignancies [5]. The major contribution of this type of studies is identification of novel biomarkers which would eventually be implemented in accurate risk and disease course assessment [6] [7]. "
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    ABSTRACT: Recent study, which included meta-analysis of two genome-wide association studies (GWAS), followed by a replication, identified the association between single nucleotide polymorphism (SNP) rs3787016 at 19p13 and prostate cancer (PCa) risk. Considering possible genetic differences between populations, we conducted the study in order to evaluate the association of this polymorphism with prostate cancer risk in Serbian population. 261 samples of peripheral blood were obtained from the patients with PCa and 257 samples from patients with benign prostatic hyperplasia (BPH). 106 volunteers who gave samples of bucal swabs comprised the control group. For individuals diagnosed with PCa clinicopathological characteristics including serum prostate-specific antigen (PSA) level at diagnosis, Gleason score (GS) and clinical stage were determined. Genotypization of rs3787016 was performed by using Taqman(®) SNP Genotyping Assay. The differences in alelle and genotype frequencies between analyzed groups of subjects were performed by using PLINK, SPSS 17.0 for Windows and SNPStats statistical software. No significant association of rs3787016 with PCa risk was determined comparing allele and genotype frequencies among group of patients diagnosed with PCa and the control group, as well as among groups of patients with PCa and BPH. Also, no evidence of association of rs3787016 with PCa risk was shown using tests for association under dominant and recessive genetic models. SNP rs3787016 showed no significant association with standard prognostic parameters regarding PCa progression, nor with the risk of disease progression assessed according to two different risk classification systems.
    Full-text · Article · Jan 2013 · International Journal of Clinical and Experimental Medicine
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