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They Sought Answers and They Found: The COGS Consortium and the Illumina iCOGS Array

Maria Celeste Ramirez
| Mar 29, 2013

ID 10020396Cancer is a complex disease arising from the accumulation of genetic changes within multiple loci over time. Once a threshold is reached, these changes collectively lead to the dysregulation of pathways that control normal cell proliferation, differentiation, and survival. The identification of loci that confer susceptibility to developing cancer is important in understanding the molecular basis of the disease and should translate into better risk prediction.

The Case of Missing Heritability

Although there is strong evidence pointing to genetic predisposition, there have been relatively few loci associated with susceptibility to the three most common hormone-related cancers: breast, prostate, and ovarian. For breast cancer, which is the most commonly occurring malignancy in women, only 30% of familial risk can be accounted for by the variants identified to date, including highly penetrant variants (BRCA1 and BRCA2), moderate-risk alleles (like ATM) and low-penetrance variants (which account for only 9% of familial risk of the disease). Genome-wide association studies (GWAS) of prostate cancer, the most commonly diagnosed cancer in males in the developing world, have only identified 53 susceptibility loci for common, low-penetrance variants with modest effects. In the case of ovarian cancer, only four loci have been reported to be associated with the disease at genome-wide significance. It is therefore very likely that there are other susceptibility loci associated with these cancers that have been missed due to the limited power of the studies.

The Power of Many

The strong evidence of genetic predisposition is in stark contrast to the low number of identified loci associated with the disease. For an association between a locus or allele and the disease to be detected in genome-wide association studies, there is an underlying assumption of the variant having a reasonable frequency within the population being tested or, if the allele frequency is low, that the variant has a large effect size. So if the variant is of low frequency and has a small effect size, it is likely to be missed by GWAS. To enable efficient identification of these common, low-penetrance variants, various consortia combined efforts to conduct large-scale genotyping studies which greatly increased the number of cases and controls, thereby increasing the power of detecting other loci that contribute to disease susceptibility.

The Collaborative Oncological Gene-Environment Study (COGS) Consortium is composed of four consortia: The BCAC1, the OCAC2, PRACTICAL3, and CIMBA4. The COGS project, funded by the European Union (EU), aims to advance the understanding of genetic susceptibility to the three hormone-related cancers: breast, prostate, and ovarian. To accomplish this, meta-analysis of previous genome-wide association studies was performed to select single nucleotide polymorphisms (SNPs) for inclusion in a large replication study for each of the three cancers. These selected SNPs, 211,115 in total, were combined on a custom iSelect array (iCOGS array) which was used to genotype more than 200,000 individuals.  These studies resulted in a collection of 13 coordinated research papers, five of which appear in the April issue of Nature Genetics.

Why is this important?

This represents the largest collaborative effort to catalog susceptibility variants and highlights the advantage of replicating previous GWAS experiments on a large scale to increase the power of detection leading to the identification of novel low-penetrance alleles. These efforts resulted in the identification of 41 new susceptibility loci for breast cancer and 23 new loci for prostate cancer. For epithelial ovarian cancer, 3 new alleles have been associated with susceptibility to the disease and 2 previously reported loci were confirmed. These results almost double the number of known susceptibility loci associated with breast, prostate, and ovarian cancers, enabling a more comprehensive understanding of the determinants of susceptibility.

In addition, the studies also help to validate findings about the etiology of cancer:

  1. Hormone-related cancers have shared etiology. A common thread throughout these studies is the finding that loci associated with one of the hormone-related cancers have been implicated in other cancers. Additionally, analysis of pathways where these SNPs may play a role showed an overrepresentation of pathways already known to be involved in the onset and progression of cancer, suggesting a shared mechanism among these cancers despite the differences in tissue of origin.
  2. Some associations are specific to cancer subtypes. Some susceptibility loci demonstrate strong or exclusive associations with one cancer subtype over another, indicating that initiating events distinguish a particular subtype over another.
  3. Some SNPs within loci implicated in more than one cancer may present stronger associations with one cancer over another. This observation suggests that the locus itself is a key driver for the induction of events that lead to cancer, but the SNPs may modulate the tissue-specific mechanisms that lead to the development of particular cancers.
  4. Novel SNPs were found in various contexts.
    • Some SNPs were found within genes and may impact coding, splicing, and mRNA stability
    • Some SNPs were found outside of genes but in close proximity to genes and may impact regulation of expression of these nearby genes
    • Some SNPs were found in gene deserts and may impact long-range interactions between loci

Results suggest that more susceptibility loci with small effects remain to be found. Further interrogation of this collection of susceptibility loci by fine-resolution mapping, perhaps through sequencing, may uncover other SNPs that are more strongly associated to the disease and account for missing heritability. Taken together, these findings greatly advance the understanding of inherited susceptibility to these hormone-related cancers. As David Bentley, Chief Scientist at Illumina stated, “The data resulting from COGS is a true testament to the power of genotyping in the quest for better prediction and management of these cancers. As a result of the study, researchers have a better understanding of the genetic basis of cancer.”



1 Breast Cancer Association Consortium

2 Ovarian Cancer Association Consortium

3 Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome

4 Consortium of Investigators of Modifiers of BRCA 1/2



Image courtesy of Salvatore Vuono /