Clinical characterization of the mutational landscape of 24,639 real-world samples from patients with myeloid malignancies.

Myeloid neoplasms represent a broad spectrum of hematological disorders for which somatic mutation status in key driver genes is important for diagnosis, prognosis and treatment. Here we summarize the findings of a targeted, next generation sequencing laboratory developed test in 24,639 clinical myeloid samples. Data were analyzed comprehensively and as part of individual cohorts specific to acute myeloid leukemia (AML), myelodysplastic syndrome (MDS), and myeloproliferative neoplasms (MPN). Overall, 48,015 variants were detected, and variants were found in all 50 genes in the panel. The mean number of mutations per patient was 1.95. Mutation number increased with age (Spearman's rank correlation coefficient, ρ = 0.29, P < 0.0001) and was higher in patients with AML than MDS or MPN (Student's t-test, P < 0.0001). TET2 was the most common mutation detected (19.1% of samples; 4,695/24,639) including 7.7% (1,908/24,639) with multi-hit TET2 mutations. Mutation frequency was correlated between patients with cytopenias and MDS (Spearman's, ρ = 0.97, P < 2.2×10-16) with the MDS diagnostic gene SF3B1 being the only notable outlier. This large retrospective study shows the utility of NGS testing to inform clinical decisions during routine clinical care and highlights the mutational landscape of a broad population of myeloid patients.

Evaluation of a 27-gene inherited cancer panel across 630 consecutive patients referred for testing in a clinical diagnostic laboratory.

BACKGROUND: Extensive clinical and genetic heterogeneity of inherited cancers has allowed multi-gene panel testing to become an efficient means for identification of patients with an inherited predisposition to a broad spectrum of syndromic and nonsyndromic forms of cancer. This study reports our experience with a 27-gene inherited cancer panel on a cohort of 630 consecutive individuals referred for testing at our laboratory with the following objectives: 1. Determine the rates for positive cases and those with variants of uncertain clinical significance (VUS) relative to data published in the recent literature, 2. Examine heterogeneity among the constituent genes on the panel, and 3. Review test uptake in the cohort relative to other reports describing outcomes for expanded panel testing. METHODS: Clinical and genomic data were reviewed on 630 individuals tested on a panel of 27 genes selected on the basis of high (≥ 40%) or moderate to low (≤ 40%) lifetime risk of hereditary cancer. These patients were not enriched for adherence to the National Comprehensive Cancer Network (NCCN) criteria for Hereditary Breast and Ovarian Cancer (HBOC) or Lynch Syndrome (LS) and constitute a referral laboratory cohort. RESULTS: Sixty-five individuals with variants classified as pathogenic or likely pathogenic across 14 genes were identified for an overall positive rate of 10.3%. Although a family history of cancer constituted a major reason for referral, accounting for 84% of our cohort, excluding patients with a known familial variant did not have a significant impact on the observed positive rate (9% vs 10.3%). More than half (58%) of the pathogenic or likely pathogenic variants were observed in high or moderate to low risk genes on the panel, while only 42% occurred in classic HBOC or LS-associated genes. CONCLUSION: These results provide the actual percentage of family or personal history of cancer that can be attributed to pathogenic or likely pathogenic variants in one or more of the genes on our panel and corroborate the utility of multi-gene panels over sequential testing to identify individuals with an inherited predisposition to cancer.

Exploring the landscape of pathogenic genetic variation in the ExAC population database: insights of relevance to variant classification.

PURPOSE: We evaluated the Exome Aggregation Consortium (ExAC) database as a control cohort to classify variants across a diverse set of genes spanning dominant and recessively inherited disorders. METHODS: The frequency of pathogenic variants in ExAC was compared with the estimated maximal pathogenic allele frequency (MPAF), based on the disease prevalence, penetrance, inheritance, allelic and locus heterogeneity of each gene. Additionally, the observed carrier frequency and the ethnicity-specific variant distribution were compared between ExAC and the published literature. RESULTS: The carrier frequency and ethnic distribution of pathogenic variants in ExAC were concordant with reported estimates. Of 871 pathogenic/likely pathogenic variants across 19 genes, only 3 exceeded the estimated MPAF. Eighty-four percent of variants with ExAC frequencies above the estimated MPAF were classified as "benign." Additionally, 20% of the cardiac and 19% of the Lynch syndrome gene variants originally classified as "VUS" occurred with ExAC frequencies above the estimated MPAF, making these suitable for reassessment. CONCLUSIONS: The ExAC database is a useful source for variant classification and is not overrepresented for pathogenic variants in the genes evaluated. However, the mutational spectrum, pseudogenes, genetic heterogeneity, and paucity of literature should be considered in deriving meaningful classifications using ExAC.Genet Med 18 8, 850-854.