Evidence for 28 genetic disorders discovered by combining healthcare and research data.

De novo mutations in protein-coding genes are a well-established cause of developmental disorders1. However, genes known to be associated with developmental disorders account for only a minority of the observed excess of such de novo mutations1,2. Here, to identify previously undescribed genes associated with developmental disorders, we integrate healthcare and research exome-sequence data from 31,058 parent-offspring trios of individuals with developmental disorders, and develop a simulation-based statistical test to identify gene-specific enrichment of de novo mutations. We identified 285 genes that were significantly associated with developmental disorders, including 28 that had not previously been robustly associated with developmental disorders. Although we detected more genes associated with developmental disorders, much of the excess of de novo mutations in protein-coding genes remains unaccounted for. Modelling suggests that more than 1,000 genes associated with developmental disorders have not yet been described, many of which are likely to be less penetrant than the currently known genes. Research access to clinical diagnostic datasets will be critical for completing the map of genes associated with developmental disorders.

Differences in cancer prevalence among CHEK2 carriers identified via multi-gene panel testing.

PURPOSE: Although CHEK2 is a well-established cancer gene, questions remain including whether risks vary substantially between different variants and whether biallelic carriers have higher risks than heterozygotes. We report on a cohort of individuals with CHEK2 pathogenic and likely pathogenic variants (collectively, PV) in order to better characterize this gene. METHODS: We retrospectively queried samples submitted for multi-gene hereditary cancer testing to identify individuals with CHEK2 PVs and assessed differences in phenotypes among various genotypes. RESULTS: CHEK2 PVs were identified in 2508 individuals, including 32 individuals with biallelic CHEK2 PVs. Breast (female, 59.9% and male, 11.8%), prostate (20.1%), and colorectal (3.5%), were among the most frequently reported cancers. Select missense PVs showed similar cancer prevalence to truncating PVs while some others showed lower prevalence. No significant differences were observed between biallelic carriers and heterozygotes. CONCLUSIONS: Our data support that some, but not all, CHEK2 missense PVs demonstrate lower cancer prevalence; further studies are needed to continue characterizing possible variant specific risks. In addition, biallelic CHEK2 PVs do not appear to be associated with a more severe phenotype than single CHEK2 PVs. Furthermore, co-occurrences with PVs in other cancer risk genes are common among CHEK2 heterozygotes and often warrant additional management.

Age-adjusted association of homologous recombination genes with ovarian cancer using clinical exomes as controls.

BACKGROUND: Genes in the homologous recombination pathway have shown varying results in the literature regarding ovarian cancer (OC) association. Recent case-control studies have used allele counts alone to quantify genetic associations with cancer. METHODS: A retrospective case-control study was performed on 6,182 women with OC referred for hereditary cancer multi-gene panel testing (cases) and 4,690 mothers from trios who were referred for whole-exome sequencing (controls). We present age-adjusted odds ratios (ORAdj) to determine association of OC with pathogenic variants (PVs) in homologous recombination genes. RESULTS: Significant associations with OC were observed in BRCA1, BRCA2, RAD51C and RAD51D. Other homologous recombination genes, BARD1, NBN, and PALB2, were not significantly associated with OC. ATM and CHEK2 were only significantly associated with OC by crude odds ratio (ORCrude) or by ORAdj, respectively. However, there was no significant difference between ORCrude and ORAdj for these two genes. The significant association of PVs in BRIP1 by ORCrude (2.05, CI = 1.11 to 3.94, P = 0.03) was not observed by ORAdj (0.87, CI = 0.41 to 1.93, P = 0.73). Interestingly, the confidence intervals of the two effect sizes were significantly different (P = 0.04). CONCLUSION: The lack of association of PVs in BRIP1 with OC by ORAdj is inconsistent with some previous literature and current management recommendations, highlighted by the significantly older age of OC onset for BRIP1 PV carriers compared to non-carriers. By reporting ORAdj, this study presents associations that reflect more informed genetic contributions to OC when compared to traditional count-based methods.

Germline pathogenic variants identified in women with ovarian tumors.

OBJECTIVE: The recognition of genes implicated in ovarian cancer risk beyond BRCA1, BRCA2, and the Lynch syndrome genes has increased the variety of testing options available to providers and patients. We report the frequency of pathogenic variants identified among individuals with ovarian cancer undergoing clinical genetic testing via a multi-gene hereditary cancer panel. METHODS: Genetic testing of up to 32 genes using a hereditary cancer panel was performed on 4439 ovarian cancer cases, and results were analyzed for frequency of pathogenic variants. Statistical comparisons were made using t-tests and Fisher's exact tests. RESULTS: The positive yield was 13.2%. While BRCA1/2 pathogenic variants were most frequent, one third (33.7%) of positive findings were in other homologous recombination genes, and accounted for over 40.0% of findings in endometrioid and clear cell cases. Women with a personal history of breast cancer (22.1%), who reported a family history of ovarian cancer (17.7%), and/or serous histology (14.7%) were most likely to harbor a pathogenic variant. Those with very early onset (<30 years) and late onset (≥70 years) ovarian cancer had low positive yields. CONCLUSIONS: Our study highlights the genetic heterogeneity of ovarian cancer, showing that a large proportion of cases are not due to BRCA1/2 and the Lynch syndrome genes, but still have an identifiable hereditary basis. These findings substantiate the utility of multi-gene panel testing in ovarian cancer care regardless of age at diagnosis, family history, or histologic subtype, providing evidence for testing beyond BRCA1/2 and the Lynch syndrome genes.

A Transition Zone Showing Highly Discontinuous or Alternating Levels of Stem Cell and Proliferation Markers Characterizes the Development of PTEN-Haploinsufficient Colorectal Cancer.

BACKGROUND: Stepwise acquisition of oncogene mutations and deletion/inactivation of tumor suppressor genes characterize the development of colorectal cancer (CRC). These genetic events interact with discrete morphologic transitions from hyperplastic mucosa to adenomatous areas, followed by in situ malignant transformation and finally invasive carcinoma. The goal of this study was to identify tissue markers of the adenoma-carcinoma morphogenetic transitions in CRC. METHODS AND FINDINGS: We analyzed the patterns of expression of growth regulatory and stem cell markers across these distinct morphologic transition zones in 735 primary CRC tumors. In 202 cases with preserved adenoma-adenocarcinoma transition, we identified, in 37.1% of cases, a zone of adenomatous epithelium, located immediately adjacent to the invasive component, that showed rapidly alternating intraglandular stretches of PTEN+ and PTEN- epithelium. This zone exactly overlapped with similar alternating expression of Ki-67 and inversely with the transforming growth factor-beta (TGF-ß) growth regulator SMAD4. These zones also show parallel alternating levels and/or subcellular localization of multiple cancer stem/progenitor cell (CSC) markers, including ß-catenin/CTNNB1, ALDH1, and CD44. PTEN was always re-expressed in the invasive tumor in these cases, unlike those with complete loss of PTEN expression. Genomic microarray analysis of CRC with prominent CSC-like expansions demonstrated a high frequency of PTEN genomic deletion/haploinsufficiency in tumors with CSC-like transition zones (62.5%) but not in tumors with downregulated but non-alternating PTEN expression (14.3%). There were no significant differences in the levels of KRAS mutation or CTNNB1 mutation in CSC-like tumors as compared to unselected CRC cases. CONCLUSIONS: In conclusion, we have identified a distinctive CSC-like pre-invasive transition zone in PTEN-haploinsufficient CRC that shows convergent on-off regulation of the PTEN/AKT, TGF-ß/SMAD and Wnt/ß-catenin pathways. This bottleneck-like zone is usually followed by the emergence of invasive tumors with intact PTEN expression but dysregulated TP53 and uniformly high proliferation rates.

Annotation of Sequence Variants in Cancer Samples: Processes and Pitfalls for Routine Assays in the Clinical Laboratory.

As DNA sequencing of multigene panels becomes routine for cancer samples in the clinical laboratory, an efficient process for classifying variants has become more critical. Determining which germline variants are significant for cancer disposition and which somatic mutations are integral to cancer development or therapy response remains difficult, even for well-studied genes such as BRCA1 and TP53. We compare and contrast the general principles and lines of evidence commonly used to distinguish the significance of cancer-associated germline and somatic genetic variants. The factors important in each step of the analysis pipeline are reviewed, as are some of the publicly available annotation tools. Given the range of indications and uses of cancer sequencing assays, including diagnosis, staging, prognostication, theranostics, and residual disease detection, the need for flexible methods for scoring of variants is discussed. The usefulness of protein prediction tools and multimodal risk-based or Bayesian approaches are highlighted. Using TET2 variants encountered in hematologic neoplasms, several examples of this multifactorial approach to classifying sequence variants of unknown significance are presented. Although there are still significant gaps in the publicly available data for many cancer genes that limit the broad application of explicit algorithms for variant scoring, the elements of a more rigorous model are outlined.