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Identifying women at high risk for breast cancer can trigger a personal program of annual mammograms and magnetic resonance imaging scans for early detection, prophylactic surgery, or chemoprevention to reduce the risk of cancer. Yet, current strategies to identify high-risk mutations based on sequencing panels of genes have significant false-positive and false-negative results, suggesting the need for alternative approaches. Flow-variant assays (FVAs) that assess the effects of mutations in the double-strand break (DSB) repair genetic pathway in lymphoblastoid cells in response to treatment with radiomimetic agents were assessed for sensitivity, specificity, and accuracy both alone and as part of a logistic regression classification score. In turn, these assays were validated in circulating B cells and applied to individuals with personal and/or family history of breast and/or ovarian cancer. A three-FVA classification score based on logistic regression had 95% accuracy. Individuals from a breast cancer–positive cohort with affected family members had high-risk FVA classification scores. Application of a classification score based on multiple FVAs could represent an alternative to panel sequencing for identifying women at high risk for cancer. Genet Med advance online publication 16 March 2017

Carrier screening programs that identify the presence of known mutations have been effective for reducing the incidence of autosomal recessive conditions in the Ashkenazi Jewish (AJ) population and other populations. Yet, these programs have not realized their full potential. Furthermore, many known autosomal recessive and dominant conditions are not screened for and the molecular basis of other conditions for which screening might be offered is unknown. Through literature review and annotation of full sequenced genomes from healthy individuals, we expanded the list of mutations. Mutations were identified in a sample of 128 fully sequenced AJ genomes that were filtered through clinical databases and curated manually for clinical validity and utility using the American College of Medical Genetics and Genomics scoring (ACMG) system. Other known mutations were identified through literature review. A panel of 163 mutations was identified for 76 autosomal recessive, 24 autosomal dominant, and 3 X-linked disorders. Screening for a broader range of disorders not only could further reduce the incidence of autosomal recessive disorders but also could offer the benefits of early or presymptomatic diagnosis. Genet Med 18 5, 522–528.

Prostate cancer is the most commonly diagnosed male cancer and the second leading cause of cancer deaths among men in the United States, with approximately 220,000 new diagnoses and approximately 27,000 deaths each year. Men with clinical low-risk disease can receive active surveillance to safely preserve quality of life, provided that the risk of an undetected aggressive cancer can be managed. Thus, prediction of a tumor's metastatic potential, ideally using only a biopsy sample, is critical to choosing appropriate treatment. We previously proposed and verified a metastasis potential score (MPS) based on regions prone to copy number alterations in metastatic prostate cancer; MPS is highly predictive of metastatic potential in primary tumors. We developed a novel, targeted postligation amplification sequencing approach, which we call the next-generation copy number alteration assay, to efficiently interrogate 902 genomic sites that belong to 194 genomic regions used in the MPS calculation. The assay is designed to work with the latest generation of sequencing platforms to produce estimates of copy number alteration events. The assay's technical reproducibility, robustness to low starting genomic material, and accuracy have been verified. The assay performed very well on cell lines, a cohort of prostate cancer surgical research samples, and matched punched biopsy samples, making it a significant step toward incorporating sequencing techniques for prostate cancer evaluation.

Objectives:This second segment of the two-part review summarises several modern high-throughput methods in genomics, epigenetics and molecular biology. Many principles from nucleotide sequencing and transcriptomics can be applied to other high-throughput molecular biology techniques. Specifically, this manuscript reviews: array comparative genome hybridisation; single nucleotide polymorphism arrays; microarray technology, used to study epigenetics; and methodology applied in proteomics. Finally, the review describes current methods for the integration of multiple molecular biology platforms.Conclusion:Progress in treating human disease in general will require close collaboration with experts in bioinformatics. Improved understanding, by clinicians and physician-scientists in our field, of the concepts presented in both parts of this review will advance diagnosis and therapy for diseases of the head and neck.