Current knowledge and tomorrows challenges of breast, ovarian and prostate cancer genetics

Authors


Per Hall, MD, PhD, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden.
(fax: +46 8314975; e-mail: per.hall@ki.se).

Introduction

Collaborative Oncological Gene Environment Study (COGS) is a large-scale genotyping project, funded by the European Commission that was initiated in 2009. The overarching goal of COGS is to identify the genetic alterations associated with the risk of breast, ovarian and prostate cancer. COGS consists of four consortia and more than 150 research groups from all over the world and is coordinated by the Karolinska Institutet, Stockholm, Sweden. In 2 years, a large number of single-nucleotide polymorphisms (SNPs) have been genotyped in more than 150 000 individuals. The consortium has identified the majority of the presently known and established susceptibility SNPs for the three cancers.

The basis of genetic susceptibility to cancer is slowly unravelling. The initial work of familial-based studies to identify high-penetrance susceptibility genes has been followed by large population-based genetic association studies. Groups within COGS have published several landmark papers [1–3], and there will be more genetic alterations identified in the years to come.

Identification of common low-penetrance susceptibility alleles is warranted for several reasons. First, it provides possible insight into the mechanisms of tumour biology. Secondly, if the mechanisms can be revealed, it may offer potential targets for novel therapy. Lastly, knowledge of susceptibility genes enables identification of individuals at increased risk of cancer. This in turn provides the opportunity for targeted primary and secondary preventive strategies.

On 15 June 2011, a meeting of the COGS members was organized at the Karolinska Institutet. The aims of the meeting were to discuss how knowledge on inheritance of cancer could be used in the clinical setting, to provide an update on the wealth of information on inheritance of cancer generated over the last few years and to speculate on the future developments. Six of the presentations at the meeting, focusing on these areas, are included in this issue of the Journal of Internal Medicine.

Professor Anthony Howell, Genesis Prevention Centre and Nightingale Breast Screening Centre, University Hospital of South Manchester, described the increasing breast cancer incidence seen worldwide and discussed how prevention is one strategy for reducing mortality from breast cancer [4]. Preventive measures are possible through defining women at greatest risk of breast cancer and offering appropriate diagnostic and therapeutic interventions. The establishment of genetic counselling units has been shown to improve survival in young women at high risk of breast cancer. Essential for risk reduction is adequate risk prediction that includes both genetic and nongenetic risk factors. Professor Howell described how preventive measures such as the use of anti-oestrogens and aromatase inhibitors have proven beneficial in large randomized clinical trials.

Dr Antonis Antoniou gave a comprehensive presentation on the influence of common genetic variants on high-penetrance mutations, that is, which other genetic factors influence the risk in BRCA1 and BRCA2 carriers [5]. Mutations in the tumour suppressor genes BRCA1 and BRCA2 increase the risk of breast and ovarian cancer. There is a large interindividual difference in risk, implying that other factors, genetic and nongenetic, influence the risk of these high-penetrance genes. Such factors are likely to cluster in families. Recently, through data from large genome-wide association studies (GWASs), several common alleles have been found to modify breast and/or ovarian cancer risk for mutation carriers.

Dr Jianfeng Xu, Center for Cancer Genomics, Wake Forest University School of Medicine, explained how GWASs have identified hundreds of consistently replicated associations between genetic markers and cancer [6]. It was underlined that individually these markers have limited power to predict the risk of cancer. However, used in combination, the predictive performance appears to be similar to currently available clinical predictors. There is clinical concern about the use of genetic predictors, and translational projects are needed to benefit from the new discoveries.

Professor Rosalind Eeles, Institute of Cancer Research and Royal Marsden Hospital, described the susceptibility SNPs associated with the risk of prostate cancer and how these findings could be brought to the clinical setting [7]. Through familial and twin studies, it has long been known that prostate cancer has an inherited component, but the discovery of these variants has proven difficult. However, with the emergence of large-scale GWASs, it has been possible to identify over 46 susceptibility loci. Professor Eeles has both a clinical and genetic background and gave an outstanding comprehensive presentation describing current knowledge and future challenges.

Dr Andrew Berchuck, Duke Cancer Institute, Durham, reviewed the current knowledge of the genetics of epithelial ovarian cancer [8]. The ovarian cancer association consortium (OCAC) was established to facilitate large-scale replication analyses for reported genetic associations. Several GWASs have been conducted, and six established loci for ovarian cancer have been identified. Dr Berchuck described the next steps that are required, including combining established GWAS data and deep sequencing. In common with several of the speakers, Dr Berchuck underlined the necessity of translating the data into clinical practice but at the same time acknowledged the challenges ahead.

In an attempt to predict future developments in the field, Professor Julian Knight gave an excellent presentation on the topic Resolving the variable genome and epigenome in human disease [9]. He described how advances in sequencing technologies will make it possible to define the human genome at a resolution not seen before. He described the concept of functional genomics that, through information on the genome and epigenome, expression quantitative trait mapping and analysis of allele-specific gene expression, has the ability to create an integrated picture of the regulatory genomic landscape.

The future

A causal link between the common low-penetrance susceptibility alleles and the development of breast, ovarian and prostate cancer has yet to be determined. The risk alleles significantly associated with these diseases should be seen as markers in linkage disequilibrium with one or more functional variants. It is of utmost importance that the true causal variants are identified because these variants will have a stronger effect size than their corresponding markers, which means risk predictions will improve. Furthermore, to capture the underlying biology of the genetic alteration, the true susceptibility loci must be identified.

The next step will be fine mapping of the relevant genes. As extremely large numbers of samples are needed to discriminate between correlated variants, future studies need to include groups from different ethnic backgrounds and thereby different patterns of linkage disequilibrium. Genotyping and sequencing will be followed by experimental and bioinformatic approaches to identify SNPs with plausible functional effects.

Genetic risk prediction today is mainly based on mutation screening of the high-penetrance BRCA1/2 genes. It is currently unclear whether the identification of a number of common genetic susceptibility variants is sufficient for reliable risk prediction. We know that the risk associated with each SNP is low and that a combination of several SNPs is probably required.

Furthermore, SNPs alone do not entirely determine genetic risk. Additional heritability will be explained by gene–environment interactions, gene–gene interactions, and epigenetics and variants more rare than most SNPs. Rarer variants (minor allele frequencies <5%) have already been shown to influence susceptibility to, for instance, breast cancer, but there are probably many more such variants to be found. ‘Rare variants’ chips based on the 1000 Genomes Project data will provide low-frequency variant data. In addition, exome and whole-genome sequencing will be crucial in the quest for rare variants, but these new methods are still considered too costly. However, this situation is likely to change rapidly, and in a few years, we will have whole-genome sequencing studies mimicking the size and design of an ordinary GWAS.

Conflict of interest statement

No conflict of interest was declared.

Ancillary