Melanoma mimicking malignant peripheral nerve sheath tumor with spread to the cerebellopontine angle: Utility of next-generation sequencing in diagnosis

Cutaneous spindle cell malignancy is associated with a broad differential diagnosis, particularly in the absence of a known primary melanocytic lesion. We present an unusually challenging patient who presented with clinical symptoms involving cranial nerves VII and VIII and a parotid-region mass, which was S100-positive while lacking in melanocytic pigment and markers. Over a year after resection of the parotid mass, both a cutaneous primary lentigo maligna melanoma and a metastatic CP angle melanoma were diagnosed in the same patient, prompting reconsideration of the diagnosis in the original parotid-region mass. Next-generation sequencing of a panel of cancer-associated genes demonstrated 19 identical, clinically significant mutations as well as a high tumor mutation burden in both the parotid-region and CP angle tumors, indicating a metastatic relationship between the two and a melanocytic identity of the parotid-region tumor

ATSC 3.0 Next Generation Digital TV Standard - An Overview and Preview of the Issue

"(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works."The Advanced Television Committee (ATSC) has been working on the next generation broadcast television system, known as ATSC 3.0, to replace the first-generation (ATSC 1.0) A/53 standard, the basic component technologies of which have been in use for 20 years.Chernock, R.; Gómez Barquero, D.; Whitaker, J.; Park, S.; Wu, Y. (2016). ATSC 3.0 Next Generation Digital TV Standard - An Overview and Preview of the Issue. IEEE Transactions on Broadcasting. 62(1):154-158. doi:10.1109/TBC.2016.2515542S15415862

Computerized tumor multinucleation index (MuNI) is prognostic in p16+ oropharyngeal carcinoma

BACKGROUNDPatients with p16+ oropharyngeal squamous cell carcinoma (OPSCC) are potentially cured with definitive treatment. However, there are currently no reliable biomarkers of treatment failure for p16+ OPSCC. Pathologist-based visual assessment of tumor cell multinucleation (MN) has been shown to be independently prognostic of disease-free survival (DFS) in p16+ OPSCC. However, its quantification is time intensive, subjective, and at risk of interobserver variability.METHODSWe present a deep-learning-based metric, the multinucleation index (MuNI), for prognostication in p16+ OPSCC. This approach quantifies tumor MN from digitally scanned H&E-stained slides. Representative H&E-stained whole-slide images from 1094 patients with previously untreated p16+ OPSCC were acquired from 6 institutions for optimization and validation of the MuNI.RESULTSThe MuNI was prognostic for DFS, overall survival (OS), or distant metastasis-free survival (DMFS) in p16+ OPSCC, with HRs of 1.78 (95% CI: 1.37-2.30), 1.94 (1.44-2.60), and 1.88 (1.43-2.47), respectively, independent of age, smoking status, treatment type, or tumor and lymph node (T/N) categories in multivariable analyses. The MuNI was also prognostic for DFS, OS, and DMFS in patients with stage I and stage III OPSCC, separately.CONCLUSIONMuNI holds promise as a low-cost, tissue-nondestructive, H&E stain-based digital biomarker test for counseling, treatment, and surveillance of patients with p16+ OPSCC. These data support further confirmation of the MuNI in prospective trials.FUNDINGNational Cancer Institute (NCI), NIH; National Institute for Biomedical Imaging and Bioengineering, NIH; National Center for Research Resources, NIH; VA Merit Review Award from the US Department of VA Biomedical Laboratory Research and Development Service; US Department of Defense (DOD) Breast Cancer Research Program Breakthrough Level 1 Award; DOD Prostate Cancer Idea Development Award; DOD Lung Cancer Investigator-Initiated Translational Research Award; DOD Peer-Reviewed Cancer Research Program; Ohio Third Frontier Technology Validation Fund; Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering; Clinical and Translational Science Award (CTSA) program, Case Western Reserve University; NCI Cancer Center Support Grant, NIH; Career Development Award from the US Department of VA Clinical Sciences Research and Development Program; Dan L. Duncan Comprehensive Cancer Center Support Grant, NIH; and Computational Genomic Epidemiology of Cancer Program, Case Comprehensive Cancer Center. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH, the US Department of VA, the DOD, or the US Government