Background Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers and cancer related traits. Methods The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. Results The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. Conclusions Results from these analyses will enable researchers to identify new susceptibility loci, perform fine mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental and lifestyle related exposures. Impact Ongoing analyses will shed light on etiology and risk assessment for many types of cancer.

Research technologies can now produce so much information that there is signifcant potential for incidental fndings (IFs). These are fndings generated in research that are beyond the aims of the study. Current law and federal regulations ofer no direct guidance on how to deal with IFs in research, nor is there adequate professional or institutional guidance. We advocate a defned set of researcher duties based on law and ethics and recommend a pathway to be followed in handling IFs in research. This article traces the underlying ethical and legal theories supporting researcher duties to manage IFs, including duties to develop a plan for management in the research protocol, to discuss the possibility of and management plan for IFs in the informed consent process, and to address, evaluate, and ultimately ofer to disclose IFs of potential clinical or reproductive signifcance to research participants when they arise.

Despite rapid technical progress and demonstrable effectiveness for some types of diagnosis and therapy, much remains to be learned about clinical genome and exome sequencing (CGES) and its role within the practice of medicine. The Clinical Sequencing Exploratory Research (CSER) consortium includes 18 extramural research projects, one National Human Genome Research Institute (NHGRI) intramural project, and a coordinating center funded by the NHGRI and National Cancer Institute. The consortium is exploring analytic and clinical validity and utility, as well as the ethical, legal, and social implications of sequencing via multidisciplinary approaches; it has thus far recruited 5,577 participants across a spectrum of symptomatic and healthy children and adults by utilizing both germline and cancer sequencing. The CSER consortium is analyzing data and creating publically available procedures and tools related to participant preferences and consent, variant classification, disclosure and management of primary and secondary findings, health outcomes, and integration with electronic health records. Future research directions will refine measures of clinical utility of CGES in both germline and somatic testing, evaluate the use of CGES for screening in healthy individuals, explore the penetrance of pathogenic variants through extensive phenotyping, reduce discordances in public databases of genes and variants, examine social and ethnic disparities in the provision of genomics services, explore regulatory issues, and estimate the value and downstream costs of sequencing. The CSER consortium has established a shared community of research sites by using diverse approaches to pursue the evidence-based development of best practices in genomic medicine.

In May 2016, the Division of Cancer Prevention and the Division of Cancer Control and Population Sciences, National Cancer Institute, convened a workshop to discuss a conceptual framework for identifying and genetically testing previously diagnosed but unreferred patients with ovarian cancer and other unrecognized BRCA1 or BRCA2 mutation carriers to improve the detection of families at risk for breast or ovarian cancer. The concept, designated Traceback, was prompted by the recognition that although BRCA1 and BRCA2 mutations are frequent in women with ovarian cancer, many such women have not been tested, especially if their diagnosis predated changes in testing guidelines. The failure to identify mutation carriers among probands represents a lost opportunity to prevent cancer in unsuspecting relatives through risk-reduction intervention in mutation carriers and to provide appropriate reassurances to noncarriers. The Traceback program could provide an important opportunity to reach families from racial, ethnic, and socioeconomic groups who historically have not sought or been offered genetic counseling and testing and thereby contribute to a reduction in health disparities in women with germline BRCA mutations. To achieve an interdisciplinary perspective, the workshop assembled international experts in genetics, medical and gynecologic oncology, clinical psychology, epidemiology, genomics, cost-effectiveness modeling, pathology, bioethics, and patient advocacy to identify factors to consider when undertaking a Traceback program. This report highlights the workshop deliberations with the goal of stimulating research and providing a framework for pilot studies to assess the feasibility and ethical and logistical considerations related to the development of best practices for implementation of Traceback studies.

In the originally published version of this article, Table 1 unfortunately included c.542G>A instead of c.542G>T. This mutation was correctly notated as c.