Varghese JS, Easton DF. Genome-wide association studies in common cancers: what have we learnt
ABSTRACT Genome-wide association studies (GWAS) have led to the identification of more than 100 common, low-penetrance loci for cancer. At these loci, common genetic variants are associated with moderate increases in risk, typically <1.5-fold. Almost all loci lie in genomic regions not previously suspected to be involved in cancer. A plausible functional basis for a few loci, such as FGFR2 for breast cancer and MSMB for prostate cancer, has been elucidated, but the majority are not understood and suggest new mechanisms of carcinogenesis. Most loci are specific to a single cancer type, and are often subtype specific (e.g. ER-positive breast cancer). There are notable differences in the genetic architecture for different cancer types, with a greater contribution of common variants for prostate cancer. The clinical utility of variants to predict individual disease risk of disease is currently limited, but this may change as more variants are identified.
- SourceAvailable from: Francesca Demichelis
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- ": 1.1–1.3) in overall risk of prostate cancer         "
ABSTRACT: Objective: Prostate cancer is the second most frequent cancer in men worldwide and kills over 250,000 men worldwide every year. Prostate cancer is a heterogeneous disease at the clinical and the molecular level. The Scandinavian Twin Registry Study demonstrated that in contrast to most malignancies where environment was the overriding influence, heritable factors account for more than fifty percent of prostate cancers. Methods and materials: We review the literature on prostate cancer risk variants (rare and common) including SNPs and Copy Number Variants (CNVs) and discuss the potential implications of significant variants for prostate cancer patient care. Results: The search for prostate cancer susceptibility genes has included both family-based studies and case-control studies utilizing a variety of approaches from array-based to sequencing-based studies. A major challenge is to identify genetic variants associated with more aggressive, potentially lethal prostate cancer and to understand their role in the progression of the disease. Conclusion: Future risk models useful in the clinical setting will likely incorporate several risk loci rather than single variants and may be dependent on an individual patient's ethnic background.Urologic Oncology 07/2014; 33(2). DOI:10.1016/j.urolonc.2014.04.021 · 3.36 Impact Factor
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- "GWAS have identified some risk factors for type II diabetes (Prokopenko et al., 2008) and for a few other common diseases (Manolio et al., 2008; Wellcome Trust Case Control Consortium, 2007). GWAS have been modestly successful in pharmacogenetics (Grant and Hakonarson, 2007) and cancer research (Varghese and Easton, 2010). The size and structure of a study cohort are the main limiting factors in such studies, as the individual impact of genomic differences is usually small. "
ABSTRACT: Motivation: Increased availability of various genotyping techniques has initiated a race for finding genetic markers that can be used in diagnostics and personalized medicine. Although many genetic risk factors are known, key causes of common diseases with complex heritage patterns are still unknown. Identification of such complex traits requires a targeted study over a large collection of data. Ideally, such studies bring together data from many biobanks. However, data aggregation on such a large scale raises many privacy issues. Results: We show how to conduct such studies without violating privacy of individual donors and without leaking the data to third parties. The presented solution has provable security guarantees. Contact: firstname.lastname@example.org Supplementary information: Supplementary data are available at Bioinformatics online.Bioinformatics 03/2013; 29(7). DOI:10.1093/bioinformatics/btt066 · 4.62 Impact Factor
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- "In addition, loci associated with tumor progression after treatment will offer targets for therapeutic intervention, and the risk predictions based on accumulated knowledge of cancer genetics, together with environmental risk factors, will help to identify individuals with an elevated risk of cancer (Fletcher & Houlston, 2010). Although each of the common loci identified through GWAS only account for a small proportion of risk, collectively more than 20% of familial risk of prostate cancer has been explained, and ∼7%, ∼6%, and ∼5% of familial risk of lung, colorectal, and breast cancers, respectively, can now be explained by GWAS results (Varghese & Easton, 2010). These estimates are likely to be conservative, as the effects of causal variants are typically larger than the associations detected through tag single-nucleotide polymorphisms (SNPs); Fletcher & Houlston, 2010). "
ABSTRACT: Recent Genome-Wide Association Studies (GWAS) have identified four low-penetrance ovarian cancer susceptibility loci. We hypothesized that further moderate- or low-penetrance variants exist among the subset of single-nucleotide polymorphisms (SNPs) not well tagged by the genotyping arrays used in the previous studies, which would account for some of the remaining risk. We therefore conducted a time- and cost-effective stage 1 GWAS on 342 invasive serous cases and 643 controls genotyped on pooled DNA using the high-density Illumina 1M-Duo array. We followed up 20 of the most significantly associated SNPs, which are not well tagged by the lower density arrays used by the published GWAS, and genotyping them on individual DNA. Most of the top 20 SNPs were clearly validated by individually genotyping the samples used in the pools. However, none of the 20 SNPs replicated when tested for association in a much larger stage 2 set of 4,651 cases and 6,966 controls from the Ovarian Cancer Association Consortium. Given that most of the top 20 SNPs from pooling were validated in the same samples by individual genotyping, the lack of replication is likely to be due to the relatively small sample size in our stage 1 GWAS rather than due to problems with the pooling approach. We conclude that there are unlikely to be any moderate or large effects on ovarian cancer risk untagged by less dense arrays. However, our study lacked power to make clear statements on the existence of hitherto untagged small-effect variants.Twin Research and Human Genetics 07/2012; 15(5):615-23. DOI:10.1017/thg.2012.38 · 1.92 Impact Factor