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Severe congenital neutropenia (SCN) is a collection of diverse disorders characterized by chronically low absolute neutrophil count in the peripheral blood, increased susceptibility to infection, and a significant predisposition to the development of myeloid malignancies. SCN can be acquired or inherited. Inherited forms have been linked to variants in a group of diverse genes involved in the neutrophil-differentiation process. Variants that promote resistance to treatment have also been identified. Thus, genetic testing is important for the diagnosis, prognosis, and management of SCN. Herein we describe clinically validated assay developed for assessing patients with suspected SCN. The assay is performed from a whole-exome backbone. Variants are called across all coding exons, and results are filtered to focus on 48 genes that are clinically relevant to SCN. Validation results indicated 100% analytical sensitivity and specificity for the detection of constitutional variants among the 48 reportable genes. To date, 34 individuals have been referred for testing (age range: birth to 67 years). Several pathogenic and likely pathogenic variants have been identified, including one in a patient with late-onset disease. The pattern of cases referred for testing suggests that this assay has clinical utility in a broader spectrum of patients beyond those in the pediatric population who have classic early-onset symptoms characteristic of SCN., (Copyright © 2021 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

PCR amplification, a key step in next-generation sequencing (NGS) library construction, can generate an unlimited amount of product from limited input; however, it cannot create more information than was present in the original template. Thus, NGS libraries can be made from very little DNA, but reducing the input may compromise assay sensitivity in ways that are difficult to ascertain unless library complexity (ie, the number of unique DNA molecules represented in the library) and depth of coverage with unique sequence reads (those derived from input DNA molecules) versus duplicate sequence reads (those resulting from overamplification of particular molecules) are discretely measured. A series of experiments was performed to explore the impact of low DNA input on an amplicon-based NGS assay using unique molecular identifiers to track unique versus duplicate reads. At high sequencing depths, unique and total (unique plus duplicate) read coverage are not well correlated, so increasing the number of sequenced reads does not necessarily improve sensitivity. Unique coverage depth tends to improve with more input, but improvements are not consistent. Fluctuations in library complexity complicated variant detection using both standardized and clinical specimens, often resulting in technical replicates with vastly different estimates of variant allelic fraction. In conclusion, depth of coverage with unique reads must be tracked in clinical NGS to ensure that sensitivity and accuracy are maintained., (Copyright © 2020 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

Disorders of somatic mosaicism (DoSM) are a diverse group of syndromic and non-syndromic conditions caused by mosaic variants in genes that regulate cell survival and proliferation. Despite overlap in gene space and technical requirements, few clinical labs specialize in DoSM compared to oncology. We adapted a high-sensitivity next-generation sequencing cancer assay for DoSM in 2014. Some 343 individuals have been tested over the past 5 years, 58% of which had pathogenic and likely pathogenic (P/LP) findings, for a total of 206 P/LP variants in 22 genes. Parameters associated with the high diagnostic yield were: (1) deep sequencing (∼2,000× coverage), (2) a broad gene set, and (3) testing affected tissues. Fresh and formalin-fixed paraffin embedded tissues performed equivalently for identification of P/LP variants (62% and 71% of individuals, respectively). Comparing cultured fibroblasts to skin biopsies suggested that culturing might boost the allelic fraction of variants that confer a growth advantage, specifically gain-of-function variants in PIK3CA. Buccal swabs showed high diagnostic sensitivity in case subjects where disease phenotypes manifested in the head or brain. Peripheral blood was useful as an unaffected comparator tissue to determine somatic versus constitutional origin but had poor diagnostic sensitivity. Descriptions of all tested individuals, specimens, and P/LP variants included in this cohort are available to further the study of the DoSM population., (Copyright © 2019. Published by Elsevier Inc.)

Clinical next-generation sequencing assays are often run on tumor specimens without a matched normal specimen, which complicates the differentiation of germline from somatic variants. In tumor-only testing, population data are often used to infer germline status, though no consensus exists on the exact population frequency (PF) cutoff above which a variant should be considered likely germline. In this study, five population databases plus the Catalog of Somatic Mutations in Cancer were used to demonstrate the impact of changing the PF cutoff on assignment of variants as germline versus somatic. The 1% to 2% PF cutoffs widely used in bioinformatic pipelines resulted in high sensitivity for classification of somatic variants, but unnecessarily reduced sensitivity for germline variants. Using optimized PF cutoffs, the source of variants in The Cancer Genome Atlas (TCGA) data could be predicted with >95% accuracy. Further exploration of four TCGA cancer data sets indicated that the optimal cutoff is influenced by both cancer type and the assay region of interest. Comparing TCGA data to data generated from a clinical, hybridization capture test (approximately 615 kb capture space) showed that PF cutoffs may not be transferable between assays, even when the gene set is held constant. Thus, filtering approaches need to be carefully designed and optimized, and should be assay-specific to support tumor-only testing until tumor-normal testing becomes routine in the clinical setting., (Copyright © 2019 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.)

The 2007 World Health Organization Classification of Tumours of the Central Nervous System classifies lower-grade gliomas [LGGs (grades II to III diffuse gliomas)] morphologically as astrocytomas or oligodendrogliomas, and tumors with unclear ambiguous morphology as oligoastrocytomas. The World Health Organization's newly released (2016) classification incorporates molecular data. A single, targeted next-generation sequencing (NGS) panel was used for detecting single-nucleotide variation and copy number variation in 50 LGG cases originally classified using the 2007 criteria, including 36 oligoastrocytomas, 11 oligodendrogliomas, 2 astrocytomas, and 1 LGG not otherwise specified. NGS results were compared with those from IHC analysis and fluorescence in situ hybridization to assess concordance and to categorize the tumors according to the 2016 criteria. NGS results were concordant with those from IHC analysis in all cases. In 3 cases, NGS was superior to fluorescence in situ hybridization in distinguishing segmental chromosomal losses from whole-arm deletions. The NGS approach was effective in reclassifying 36 oligoastrocytomas as 30 astrocytomas (20 IDH1/2 mutant and 10 IDH1/2 wild type) and 6 oligodendrogliomas, and 1 oligodendroglioma as an astrocytoma (IDH1/2 mutant). Here we show that a single, targeted NGS assay can serve as the sole testing modality for categorizing LGG according to the World Health Organization's 2016 diagnostic scheme. This modality affords greater accuracy and efficiency while reducing specimen tissue requirements compared with multimodal approaches., (Copyright © 2017 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.)