24 research outputs found

    Canine Ependymoma: Diagnostic Criteria and Common Pitfalls

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    Reports of canine ependymoma are generally restricted to single case reports with tumor incidence estimated at 2% to 3% of primary central nervous system (CNS) tumors. While most commonly reported in the lateral ventricle, tumors can occur anywhere in the ventricular system and in extraventricular locations. Rosettes and pseudorosettes are a common histologic feature; however, these features can be mimicked by other CNS neoplasms. Thirty-seven potential ependymoma cases were identified in a retrospective database search of 8 institutions, and a histologic review of all cases was conducted. Of 37 cases, 22 candidate cases were further subjected to a consensus histologic and immunohistochemical review, and only 5 of 37 (13.5%) were conclusively identified as ependymoma. The neuroanatomic locations were the lateral ventricle (3/5), third ventricle (1/5), and mesencephalic aqueduct (1/5). Subtypes were papillary (4/5) and tanycytic (1/5). Histologic features included rosettes (5/5), pseudorosettes (5/5), ependymal canals (2/5), tanycytic differentiation (1/5), blepharoplasts (1/5), ciliated cells (1/5), and high nuclear to cytoplasmic ratio (5/5). Immunolabeling for GFAP (4/4) and CKAE1/3 (3/4) was found in pseudorosettes, rosettes, and scattered individual neoplastic cells. Diffuse but variably intense cytoplasmic S100 immunolabeling was detected in 3 of 4 cases. Olig2 intranuclear immunolabeling was observed in less than 1% of the neoplastic cells (3/3). Tumors that had pseudorosettes and mimicked ependymoma included oligodendroglioma, choroid plexus tumor, pituitary corticotroph adenoma, papillary meningioma, and suprasellar germ cell tumor. These findings indicate that canine ependymoma is an extremely rare neoplasm with histomorphologic features that overlap with other primary CNS neoplasms

    Nuclear Morphometry using a Deep Learning-based Algorithm has Prognostic Relevance for Canine Cutaneous Mast Cell Tumors

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    Variation in nuclear size and shape is an important criterion of malignancy for many tumor types; however, categorical estimates by pathologists have poor reproducibility. Measurements of nuclear characteristics (morphometry) can improve reproducibility, but manual methods are time consuming. In this study, we evaluated fully automated morphometry using a deep learning-based algorithm in 96 canine cutaneous mast cell tumors with information on patient survival. Algorithmic morphometry was compared with karyomegaly estimates by 11 pathologists, manual nuclear morphometry of 12 cells by 9 pathologists, and the mitotic count as a benchmark. The prognostic value of automated morphometry was high with an area under the ROC curve regarding the tumor-specific survival of 0.943 (95% CI: 0.889 - 0.996) for the standard deviation (SD) of nuclear area, which was higher than manual morphometry of all pathologists combined (0.868, 95% CI: 0.737 - 0.991) and the mitotic count (0.885, 95% CI: 0.765 - 1.00). At the proposed thresholds, the hazard ratio for algorithmic morphometry (SD of nuclear area 9.0μm2\geq 9.0 \mu m^2) was 18.3 (95% CI: 5.0 - 67.1), for manual morphometry (SD of nuclear area 10.9μm2\geq 10.9 \mu m^2) 9.0 (95% CI: 6.0 - 13.4), for karyomegaly estimates 7.6 (95% CI: 5.7 - 10.1), and for the mitotic count 30.5 (95% CI: 7.8 - 118.0). Inter-rater reproducibility for karyomegaly estimates was fair (κ\kappa = 0.226) with highly variable sensitivity/specificity values for the individual pathologists. Reproducibility for manual morphometry (SD of nuclear area) was good (ICC = 0.654). This study supports the use of algorithmic morphometry as a prognostic test to overcome the limitations of estimates and manual measurements

    Automated Nuclear Morphometry: A Deep Learning Approach for Prognostication in Canine Pulmonary Carcinoma to Enhance Reproducibility

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    The integration of deep learning-based tools into diagnostic workflows is increasingly prevalent due to their efficiency and reproducibility in various settings. We investigated the utility of automated nuclear morphometry for assessing nuclear pleomorphism (NP), a criterion of malignancy in the current grading system in canine pulmonary carcinoma (cPC), and its prognostic implications. We developed a deep learning-based algorithm for evaluating NP (variation in size, i.e., anisokaryosis and/or shape) using a segmentation model. Its performance was evaluated on 46 cPC cases with comprehensive follow-up data regarding its accuracy in nuclear segmentation and its prognostic ability. Its assessment of NP was compared to manual morphometry and established prognostic tests (pathologists’ NP estimates (n = 11), mitotic count, histological grading, and TNM-stage). The standard deviation (SD) of the nuclear area, indicative of anisokaryosis, exhibited good discriminatory ability for tumor-specific survival, with an area under the curve (AUC) of 0.80 and a hazard ratio (HR) of 3.38. The algorithm achieved values comparable to manual morphometry. In contrast, the pathologists’ estimates of anisokaryosis resulted in HR values ranging from 0.86 to 34.8, with slight inter-observer reproducibility (k = 0.204). Other conventional tests had no significant prognostic value in our study cohort. Fully automated morphometry promises a time-efficient and reproducible assessment of NP with a high prognostic value. Further refinement of the algorithm, particularly to address undersegmentation, and application to a larger study population are required

    Phenotypic Characterization of EIF2AK4 Mutation Carriers in a Large Cohort of Patients Diagnosed Clinically With Pulmonary Arterial Hypertension.

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    BACKGROUND: Pulmonary arterial hypertension (PAH) is a rare disease with an emerging genetic basis. Heterozygous mutations in the gene encoding the bone morphogenetic protein receptor type 2 (BMPR2) are the commonest genetic cause of PAH, whereas biallelic mutations in the eukaryotic translation initiation factor 2 alpha kinase 4 gene (EIF2AK4) are described in pulmonary veno-occlusive disease/pulmonary capillary hemangiomatosis. Here, we determine the frequency of these mutations and define the genotype-phenotype characteristics in a large cohort of patients diagnosed clinically with PAH. METHODS: Whole-genome sequencing was performed on DNA from patients with idiopathic and heritable PAH and with pulmonary veno-occlusive disease/pulmonary capillary hemangiomatosis recruited to the National Institute of Health Research BioResource-Rare Diseases study. Heterozygous variants in BMPR2 and biallelic EIF2AK4 variants with a minor allele frequency of <1:10 000 in control data sets and predicted to be deleterious (by combined annotation-dependent depletion, PolyPhen-2, and sorting intolerant from tolerant predictions) were identified as potentially causal. Phenotype data from the time of diagnosis were also captured. RESULTS: Eight hundred sixty-four patients with idiopathic or heritable PAH and 16 with pulmonary veno-occlusive disease/pulmonary capillary hemangiomatosis were recruited. Mutations in BMPR2 were identified in 130 patients (14.8%). Biallelic mutations in EIF2AK4 were identified in 5 patients with a clinical diagnosis of pulmonary veno-occlusive disease/pulmonary capillary hemangiomatosis. Furthermore, 9 patients with a clinical diagnosis of PAH carried biallelic EIF2AK4 mutations. These patients had a reduced transfer coefficient for carbon monoxide (Kco; 33% [interquartile range, 30%-35%] predicted) and younger age at diagnosis (29 years; interquartile range, 23-38 years) and more interlobular septal thickening and mediastinal lymphadenopathy on computed tomography of the chest compared with patients with PAH without EIF2AK4 mutations. However, radiological assessment alone could not accurately identify biallelic EIF2AK4 mutation carriers. Patients with PAH with biallelic EIF2AK4 mutations had a shorter survival. CONCLUSIONS: Biallelic EIF2AK4 mutations are found in patients classified clinically as having idiopathic and heritable PAH. These patients cannot be identified reliably by computed tomography, but a low Kco and a young age at diagnosis suggests the underlying molecular diagnosis. Genetic testing can identify these misclassified patients, allowing appropriate management and early referral for lung transplantation

    Comprehensive Rare Variant Analysis via Whole-Genome Sequencing to Determine the Molecular Pathology of Inherited Retinal Disease

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    Inherited retinal disease is a common cause of visual impairment and represents a highly heterogeneous group of conditions. Here, we present findings from a cohort of 722 individuals with inherited retinal disease, who have had whole-genome sequencing (n = 605), whole-exome sequencing (n = 72), or both (n = 45) performed, as part of the NIHR-BioResource Rare Diseases research study. We identified pathogenic variants (single-nucleotide variants, indels, or structural variants) for 404/722 (56%) individuals. Whole-genome sequencing gives unprecedented power to detect three categories of pathogenic variants in particular: structural variants, variants in GC-rich regions, which have significantly improved coverage compared to whole-exome sequencing, and variants in non-coding regulatory regions. In addition to previously reported pathogenic regulatory variants, we have identified a previously unreported pathogenic intronic variant in CHM\textit{CHM} in two males with choroideremia. We have also identified 19 genes not previously known to be associated with inherited retinal disease, which harbor biallelic predicted protein-truncating variants in unsolved cases. Whole-genome sequencing is an increasingly important comprehensive method with which to investigate the genetic causes of inherited retinal disease.This work was supported by The National Institute for Health Research England (NIHR) for the NIHR BioResource – Rare Diseases project (grant number RG65966). The Moorfields Eye Hospital cohort of patients and clinical and imaging data were ascertained and collected with the support of grants from the National Institute for Health Research Biomedical Research Centre at Moorfields Eye Hospital, National Health Service Foundation Trust, and UCL Institute of Ophthalmology, Moorfields Eye Hospital Special Trustees, Moorfields Eye Charity, the Foundation Fighting Blindness (USA), and Retinitis Pigmentosa Fighting Blindness. M.M. is a recipient of an FFB Career Development Award. E.M. is supported by UCLH/UCL NIHR Biomedical Research Centre. F.L.R. and D.G. are supported by Cambridge NIHR Biomedical Research Centre

    Comprehensive Cancer-Predisposition Gene Testing in an Adult Multiple Primary Tumor Series Shows a Broad Range of Deleterious Variants and Atypical Tumor Phenotypes.

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    Multiple primary tumors (MPTs) affect a substantial proportion of cancer survivors and can result from various causes, including inherited predisposition. Currently, germline genetic testing of MPT-affected individuals for variants in cancer-predisposition genes (CPGs) is mostly targeted by tumor type. We ascertained pre-assessed MPT individuals (with at least two primary tumors by age 60 years or at least three by 70 years) from genetics centers and performed whole-genome sequencing (WGS) on 460 individuals from 440 families. Despite previous negative genetic assessment and molecular investigations, pathogenic variants in moderate- and high-risk CPGs were detected in 67/440 (15.2%) probands. WGS detected variants that would not be (or were not) detected by targeted resequencing strategies, including low-frequency structural variants (6/440 [1.4%] probands). In most individuals with a germline variant assessed as pathogenic or likely pathogenic (P/LP), at least one of their tumor types was characteristic of variants in the relevant CPG. However, in 29 probands (42.2% of those with a P/LP variant), the tumor phenotype appeared discordant. The frequency of individuals with truncating or splice-site CPG variants and at least one discordant tumor type was significantly higher than in a control population (χ2 = 43.642; p ≤ 0.0001). 2/67 (3%) probands with P/LP variants had evidence of multiple inherited neoplasia allele syndrome (MINAS) with deleterious variants in two CPGs. Together with variant detection rates from a previous series of similarly ascertained MPT-affected individuals, the present results suggest that first-line comprehensive CPG analysis in an MPT cohort referred to clinical genetics services would detect a deleterious variant in about a third of individuals.JW is supported by a Cancer Research UK Cambridge Cancer Centre Clinical Research Training Fellowship. Funding for the NIHR BioResource – Rare diseases project was provided by the National Institute for Health Research (NIHR, grant number RG65966). ERM acknowledges support from the European Research Council (Advanced Researcher Award), NIHR (Senior Investigator Award and Cambridge NIHR Biomedical Research Centre), Cancer Research UK Cambridge Cancer Centre and Medical Research Council Infrastructure Award. The University of Cambridge has received salary support in respect of EM from the NHS in the East of England through the Clinical Academic Reserve. The views expressed are those of the authors and not necessarily those of the NHS or Department of Health. DGE is an NIHR Senior Investigator and is supported by the all Manchester NIHR Biomedical Research Centre

    Telomerecat: A ploidy-agnostic method for estimating telomere length from whole genome sequencing data.

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    Telomere length is a risk factor in disease and the dynamics of telomere length are crucial to our understanding of cell replication and vitality. The proliferation of whole genome sequencing represents an unprecedented opportunity to glean new insights into telomere biology on a previously unimaginable scale. To this end, a number of approaches for estimating telomere length from whole-genome sequencing data have been proposed. Here we present Telomerecat, a novel approach to the estimation of telomere length. Previous methods have been dependent on the number of telomeres present in a cell being known, which may be problematic when analysing aneuploid cancer data and non-human samples. Telomerecat is designed to be agnostic to the number of telomeres present, making it suited for the purpose of estimating telomere length in cancer studies. Telomerecat also accounts for interstitial telomeric reads and presents a novel approach to dealing with sequencing errors. We show that Telomerecat performs well at telomere length estimation when compared to leading experimental and computational methods. Furthermore, we show that it detects expected patterns in longitudinal data, repeated measurements, and cross-species comparisons. We also apply the method to a cancer cell data, uncovering an interesting relationship with the underlying telomerase genotype

    A high-throughput sequencing test for diagnosing inherited bleeding, thrombotic, and platelet disorders.

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    Inherited bleeding, thrombotic, and platelet disorders (BPDs) are diseases that affect ∼300 individuals per million births. With the exception of hemophilia and von Willebrand disease patients, a molecular analysis for patients with a BPD is often unavailable. Many specialized tests are usually required to reach a putative diagnosis and they are typically performed in a step-wise manner to control costs. This approach causes delays and a conclusive molecular diagnosis is often never reached, which can compromise treatment and impede rapid identification of affected relatives. To address this unmet diagnostic need, we designed a high-throughput sequencing platform targeting 63 genes relevant for BPDs. The platform can call single nucleotide variants, short insertions/deletions, and large copy number variants (though not inversions) which are subjected to automated filtering for diagnostic prioritization, resulting in an average of 5.34 candidate variants per individual. We sequenced 159 and 137 samples, respectively, from cases with and without previously known causal variants. Among the latter group, 61 cases had clinical and laboratory phenotypes indicative of a particular molecular etiology, whereas the remainder had an a priori highly uncertain etiology. All previously detected variants were recapitulated and, when the etiology was suspected but unknown or uncertain, a molecular diagnosis was reached in 56 of 61 and only 8 of 76 cases, respectively. The latter category highlights the need for further research into novel causes of BPDs. The ThromboGenomics platform thus provides an affordable DNA-based test to diagnose patients suspected of having a known inherited BPD.This study, including the enrollment of cases, sequencing, and analysis received support from the National Institute for Health Research (NIHR) BioResource–Rare Diseases. The NIHR BioResource is funded by the NIHR (http://www.nihr.ac.uk). Research in the Ouwehand Laboratory is also supported by grants from Bristol-Myers Squibb, the British Heart Foundation, the British Society of Haematology, the European Commission, the MRC, the NIHR, and the Wellcome Trust; the laboratory also receives funding from National Health Service Blood and Transplant (NHSBT). The clinical fellows received funding from the MRC (C.L. and S.K.W.); the NIHR–Rare Diseases Translational Research Collaboration (S. Sivapalaratnam); and the British Society for Haematology and National Health Service Blood and Transplant (T.K.B.).This is the author accepted manuscript. The final version is available from American Society of Hematology via http://dx.doi.org/10.1182/blood-2015-12-688267

    Publisher Correction: Telomerecat: A ploidy-agnostic method for estimating telomere length from whole genome sequencing data.

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    A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper
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