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Perineuriomas are rare nerve sheath tumors, divided into intraneural and extraneural (soft tissue) types. Intraneural perineuriomas frequently contain TRAF7 mutations, and rarely, chr22q12 deletions. While chr22q losses can occur in soft tissue perineuriomas, comprehensive high-resolution molecular profiling has not been reported in these tumors and TRAF7 status is unknown. We used whole-exome sequencing and OncoScan single nucleotide polymorphism (SNP) array to evaluate 14 soft tissue perineuriomas. Thirteen cases showed 2 or more chromosomal abnormalities, composed primarily of large deletions. Recurrent chr22q deletions, containing the NF2 locus (n=6) and the previously unreported finding of chr17q deletions, with the NF1 locus (n=4) were frequent events and were mutually exclusive in all but1 case. In addition, 5 cases had varying chr2 deletions; and 4 cases had chr6 deletions. A chr10 deletion (previously reported in the sclerosing variant of soft tissue perineurioma) was observed in one case and another case had chr7 chromothripsis as the sole chromosomal abnormality. No TRAF7 mutations or alterations were identified in any case and no other evaluated gene (MAF<0.0001) had recurrent, deleterious mutations in >2 cases. The molecular genetic profiles showed no association with patient sex, age, tumoral histology or anatomic site. OncoScan SNP array analysis was performed on 10 cases and showed high concordance with the whole exome data, validating the large-scale deletions, duplications, and chr7 chromothripsis findings. In soft tissue perineuriomas, recurrent 22q12 deletions (with NF2) and 17q11 deletions (with NF1) appear to be mutually exclusive events, and alterations in NF1 or NF2 likely contribute to perineurioma pathogenesis, similar to other nerve sheath tumors. Moreover, the lack of TRAF7 mutations in soft tissue perineuriomas indicates divergent pathogenetic mechanisms from those of intraneural perineuriomas.

AbstractObjectiveAcute myeloid leukemia (AML) can be subtyped based on recurrent cytogenetic and molecular genetic abnormalities with diagnostic and prognostic significance. Although cytogenetic characterization classically involves conventional chromosome and/or fluorescence in situ hybridization (FISH) assays, limitations of these techniques include poor resolution and the inability to precisely identify breakpoints.MethodWe evaluated whether an NGS‐based methodology that detects structural abnormalities and copy number changes using mate pair sequencing (MPseq) can enhance the diagnostic yield for patients with AML.ResultsUsing 68 known abnormal and 20 karyotypically normal AML samples, each recurrent primary AML‐specific abnormality previously identified in the abnormal samples was confirmed using MPseq. Importantly, in eight cases with abnormalities that could not be resolved by conventional cytogenetic studies, MPseq was utilized to molecularly define eight recurrent AML‐fusion events. In addition, MPseq uncovered two cryptic abnormalities that were missed by conventional cytogenetic studies. Thus, MPseq improved the diagnostic yield in the detection of AML‐specific structural rearrangements in 10/88 (11%) of cases analyzed.ConclusionUtilization of MPseq represents a precise, molecular‐based technique that can be used as an alternative to conventional cytogenetic studies for newly diagnosed AML patients with the potential to revolutionize the diagnosis of hematologic malignancies.

Background Exercise intolerance, obesity, and low hemoglobin (hemoglobin<13 and <12 g/dl, men/women, respectively) are common features of heart failure. Despite serving as potent contributors to metabolic dysfunction, the impact of obesity and low hemoglobin on exercise intolerance is unknown. This study tested the hypotheses, compared with non-obese (NO) heart failure with normal hemoglobin, (a) counterparts with low hemoglobin and obesity or non-obesity will demonstrate reduced peak exercise oxygen uptake; (b) obese with normal hemoglobin will demonstrate decreased peak exercise oxygen uptake; (c) compared across stratifications, obese with low hemoglobin will demonstrate the sharpest decrement in peak exercise oxygen uptake. Methods Adults with heart failure ( n = 315; left ventricular ejection fraction≤40%; 77% men) (Group 1: normal hemoglobin and non-obese, n = 137; Group 2: low hemoglobin and non-obese, n = 51; Group 3: normal hemoglobin+obesity, n = 89; Group 4, n = 38: low hemoglobin+obesity; body mass index = 26 ± 3, 26 ± 2, 34 ± 4, 34 ± 4 kg/m 2 , respectively) completed treadmill cardiopulmonary exercise testing as part of routine clinical management. Peak exercise oxygen uptake was measured via standard metabolic system. Results There were no group-wise differences for heart failure class, gender, left ventricular ejection fraction, and resting cardiopulmonary function. Group 1 demonstrated increased peak exercise oxygen uptake versus Groups 2–4 (20 ± 6 versus 17 ± 6, 17 ± 5, 13 ± 4 ml/kg/min, respectively; all p < 0.001); whereas Group 4 peak exercise oxygen uptake was reduced versus all groups ( p < 0.001). Additionally, both body mass index (R 2 = 0.10) and hemoglobin (R 2 = 0.12) were significant predictors of peak exercise oxygen uptake in Group 1; which were relationships not mirrored for Groups 2–4. Conclusion These data suggest obesity together with low hemoglobin are potent contributors to impaired peak exercise oxygen uptake and, hence, oxidative metabolic capacity. In diverse populations of heart failure where obesity and/or low hemoglobin are present, it is important to consider these features together when interpreting peak exercise oxygen uptake and underlying exercise limitations.

SummaryObjectiveWe aimed to determine the frequency of probable obstructive sleep apnea (pOSA) in refractory epilepsy monitoring unit inpatients and clinical features associated with pOSA, including risk for sudden unexpected death in epilepsy (SUDEP).MethodsWe prospectively recruited 49 consecutive adult patients admitted to the Mayo Clinic Epilepsy Monitoring Unit with focal, generalized, or unclassified epilepsy syndromes. pOSA was identified using oximetric oxyhemoglobin desaturation index (ODI) and the Sleep Apnea–Sleep Disorders Questionnaire (SA‐SDQ) and STOP‐BAG screening tools. Revised SUDEP Risk Inventory (rSUDEP‐7) scores were calculated, and epilepsy patients with and without pOSA were compared with Wilcoxon signed‐rank tests. Correlation and regression analyses were utilized to determine relationships between pOSA and rSUDEP‐7 scores.ResultsThirty‐five percent of patients had pOSA, with a mean ODI of 11.3 ± 5.1/h (range = 5.1‐22.8). Patients with pOSA were older and heavier, and more frequently had a focal epilepsy syndrome and longer epilepsy duration, with higher SA‐SDQ and STOP‐BAG scores (all P < 0.05). Median rSUDEP‐7 score was 3 ± 1.4 (range = 0‐6). Higher rSUDEP‐7 scores were positively correlated with higher ODI (P = 0.036). rSUDEP‐7 score ≥ 5 was associated with pOSA by ODI, SA‐SDQ, and STOP‐BAG questionnaire criteria (P < 0.05).SignificanceOur pilot study identified a high frequency of pOSA in refractory epilepsy monitoring patients, finding that pOSA patients were older and heavier, with higher screening symptoms for sleep apnea and more frequent focal seizures with a longer epilepsy duration. We also found a possible association between OSA and SUDEP risk. Identification and treatment of OSA in patients with epilepsy could conceivably provide a novel approach toward preventing the risk of SUDEP. Future studies with polysomnography are needed to confirm predictive features for OSA in epilepsy populations, and to determine whether OSA is associated with SUDEP risk.

PurposeThe presence of respiratory motion during radiation treatment leads to degradation of the expected dose distribution, both for target coverage and healthy tissue sparing, particularly for techniques like pencil beam scanning proton therapy which have dynamic delivery systems. While tools exist to estimate this degraded four‐dimensional (4D) dose, they typically have one or more deficiencies such as not including the particular effects from a dynamic delivery, using analytical dose calculations, and/or using nonphysical dose‐accumulation methods. This work presents a clinically useful 4D‐dose calculator that addresses each of these shortcomings.MethodsTo quickly compute the 4D dose, the three main tasks of the calculator were run on graphics processing units (GPUs). These tasks were (a) simulating the delivery of the plan using measured delivery parameters to distribute the plan amongst 4DCT phases characterizing the patient breathing, (b) using an in‐house Monte Carlo simulation (MC) dose calculator to determine the dose delivered to each breathing phase, and (c) accumulating the doses from the various breathing phases onto a single phase for evaluation. The accumulation was performed by individually transferring the energy and mass of dose‐grid subvoxels, a technique that models the transfer of dose in a more physically realistic manner. The calculator was run on three test cases, with lung, esophagus, and liver targets, respectively, to assess the various uncertainties in the beam delivery simulation as well as to characterize the dose‐accumulation technique.ResultsFour‐dimensional doses were successfully computed for the three test cases with computation times ranging from 4–6 min on a server with eight NVIDIA Titan X graphics cards; the most time‐consuming component was the MC dose engine. The subvoxel‐based dose‐accumulation technique produced stable 4D‐dose distributions at subvoxel scales of 0.5–1.0 mm without impairing the total computation time. The uncertainties in the beam delivery simulation led to moderate variations of the dose–volume histograms for these cases; the variations were reduced by implementing repainting or phase‐gating motion mitigation techniques in the calculator.ConclusionsA MC‐based and GPU‐accelerated 4D‐dose calculator was developed to estimate the effects of respiratory motion on pencil beam scanning proton therapy treatments. After future validation, the calculator could be used to assess treatment plans and its quick runtime would make it easily usable in a future 4D‐robust optimization system.