A clinical guide to hereditary cancer panel testing: evaluation of gene-specific cancer associations and sensitivity of genetic testing criteria in a cohort of 165,000 high-risk patients.

PURPOSE: Despite the rapid uptake of multigene panel testing (MGPT) for hereditary cancer predisposition, there is limited guidance surrounding indications for testing and genes to include. METHODS: To inform the clinical approach to hereditary cancer MGPT, we comprehensively evaluated 32 cancer predisposition genes by assessing phenotype-specific pathogenic variant (PV) frequencies, cancer risk associations, and performance of genetic testing criteria in a cohort of 165,000 patients referred for MGPT. RESULTS: We identified extensive genetic heterogeneity surrounding predisposition to cancer types commonly referred for germline testing (breast, ovarian, colorectal, uterine/endometrial, pancreatic, and melanoma). PV frequencies were highest among patients with ovarian cancer (13.8%) and lowest among patients with melanoma (8.1%). Fewer than half of PVs identified in patients meeting testing criteria for only BRCA1/2 or only Lynch syndrome occurred in the respective genes (33.1% and 46.2%). In addition, 5.8% of patients with PVs in BRCA1/2 and 26.9% of patients with PVs in Lynch syndrome genes did not meet respective testing criteria. CONCLUSION: Opportunities to improve upon identification of patients at risk for hereditary cancer predisposition include revising BRCA1/2 and Lynch syndrome testing criteria to include additional clinically actionable genes with overlapping phenotypes and relaxing testing criteria for associated cancers.

Comprehensive Paired Tumor/Germline Testing for Lynch Syndrome: Bringing Resolution to the Diagnostic Process.

PURPOSE: The current diagnostic testing algorithm for Lynch syndrome (LS) is complex and often involves multiple follow-up germline and somatic tests. We aimed to describe the results of paired tumor/germline testing performed on a large cohort of patients with colorectal cancer (CRC) and endometrial cancer (EC) to better determine the utility of this novel testing methodology. MATERIALS AND METHODS: We retrospectively reviewed a consecutive series of patients with CRC and EC undergoing paired tumor/germline analysis of the LS genes at a clinical diagnostic laboratory (N = 702). Microsatellite instability, MLH1 promoter hypermethylation, and germline testing of additional genes were performed if ordered. Patients were assigned to one of five groups on the basis of prior tumor screening and germline testing outcomes. Results for each group are described. RESULTS: Overall results were informative regarding an LS diagnosis for 76.1% and 60.8% of patients with mismatch-repair-deficient (MMRd) CRC and EC without and with prior germline testing, respectively. LS germline mutations were identified in 24.8% of patients in the group without prior germline testing, and interestingly, in 9.5% of patients with previous germline testing; four of these were discordant with prior tumor screening. Upon excluding patients with MLH1 promoter hypermethylation and germline mutations, biallelic somatic inactivation was seen in approximately 50% of patients with MMRd tumors across groups. CONCLUSION: Paired testing identified a cause for MMRd tumors in 76% and 61% of patients without and with prior LS germline testing, respectively. Findings support inclusion of tumor sequencing as well as comprehensive LS germline testing in the LS testing algorithm. Paired testing offers a complete, convenient evaluation for LS with high diagnostic resolution.

Detection of structural variation using target captured next-generation sequencing data for genetic diagnostic testing.

PURPOSE: Structural variation (SV) is associated with inherited diseases. Next-generation sequencing (NGS) is an efficient method for SV detection because of its high-throughput, low cost, and base-pair resolution. However, due to lack of standard NGS protocols and a limited number of clinical samples with pathogenic SVs, comprehensive standards for SV detection, interpretation, and reporting are to be established. METHODS: We performed SV assessment on 60,000 clinical samples tested with hereditary cancer NGS panels spanning 48 genes. To evaluate NGS results, NGS and orthogonal methods were used separately in a blinded fashion for SV detection in all samples. RESULTS: A total of 1,037 SVs in coding sequence (CDS) or untranslated regions (UTRs) and 30,847 SVs in introns were detected and validated. Across all variant types, NGS shows 100% sensitivity and 99.9% specificity. Overall, 64% of CDS/UTR SVs were classified as pathogenic/likely pathogenic, and five deletions/duplications were reclassified as pathogenic using breakpoint information from NGS. CONCLUSION: The SVs presented here can be used as a valuable resource for clinical research and diagnostics. The data illustrate NGS as a powerful tool for SV detection. Application of NGS and confirmation technologies in genetic testing ensures delivering accurate and reliable results for diagnosis and patient care.

Advanced bone age in a girl with Wiedemann-Steiner syndrome and an exonic deletion in KMT2A (MLL).

Recognition of the gene implicated in a Mendelian disorder subsequently leads to an expansion of potential phenotypes associated with mutations in that gene as patients with features beyond the core phenotype are identified by sequencing. Here, we present a young girl with developmental delay, short stature despite a markedly advanced bone age, hypertrichosis without elbow hair, renal anomalies, and dysmorphic facial features, found to have a heterozygous, de novo, intragenic deletion encompassing exons 2-10 of the KMT2A (MLL) gene detected by whole exome sequencing. Heterozygous mutations in this gene were recently demonstrated to cause Wiedemann-Steiner syndrome (OMIM 605130). Importantly, retrospective analysis of this patient's chromosomal microarray revealed decreased copy number of two probes corresponding to exons 2 and 9 of the KMT2A gene, though this result was not reported by the testing laboratory in keeping with standard protocols for reportable size cutoffs for array comparative genomic hybridization. This patient expands the clinical phenotype associated with mutations in KMT2A to include variable patterns of hypertrichosis and a significantly advanced bone age with premature eruption of the secondary dentition despite her growth retardation. This patient also represents the first report of Wiedemann-Steiner syndrome due to an exonic deletion, supporting haploinsufficiency as a causative mechanism. Our patient also illustrates the need for sensitive guidelines for the reporting of chromosomal microarray findings that are below traditional reporting size cutoffs, but that impact exons or other genomic regions of known function.

Copy number variation signature to predict human ancestry.

BACKGROUND: Copy number variations (CNVs) are genomic structural variants that are found in healthy populations and have been observed to be associated with disease susceptibility. Existing methods for CNV detection are often performed on a sample-by-sample basis, which is not ideal for large datasets where common CNVs must be estimated by comparing the frequency of CNVs in the individual samples. Here we describe a simple and novel approach to locate genome-wide CNVs common to a specific population, using human ancestry as the phenotype. RESULTS: We utilized our previously published Genome Alteration Detection Analysis (GADA) algorithm to identify common ancestry CNVs (caCNVs) and built a caCNV model to predict population structure. We identified a 73 caCNV signature using a training set of 225 healthy individuals from European, Asian, and African ancestry. The signature was validated on an independent test set of 300 individuals with similar ancestral background. The error rate in predicting ancestry in this test set was 2% using the 73 caCNV signature. Among the caCNVs identified, several were previously confirmed experimentally to vary by ancestry. Our signature also contains a caCNV region with a single microRNA (MIR270), which represents the first reported variation of microRNA by ancestry. CONCLUSIONS: We developed a new methodology to identify common CNVs and demonstrated its performance by building a caCNV signature to predict human ancestry with high accuracy. The utility of our approach could be extended to large case-control studies to identify CNV signatures for other phenotypes such as disease susceptibility and drug response.