Differences in white matter detected by ex vivo 9.4T MRI are associated with axonal changes in the R6/1 model of Huntington’s Disease

White matter (WM) volume loss has been reported in people with Huntington’s disease (HD), but the cellular basis of this deficit remains to be elucidated. To address this, we assessed ex vivo WM microstructure in the transgenic R6/1 mouse model of HD with magnetic resonance imaging (MRI) and studied the neurobiological basis of the MRI brain signals with histological and electron microscopy analyses in a separate cohort of age- and sex-matched mice. Differences in the macromolecular proton fraction (MPF) from quantitative magnetization transfer (qMT) as a proxy myelin measure, and the intra-axonal signal fraction (FR) from the composite hindered and restricted model of diffusion (CHARMED) as a proxy marker of axon density, were assessed alongside diffusion tensor imaging (DTI) parameters. A tractometry approach was employed to inspect region-specific differences across the corpus callosum (CC). Furthermore, voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS) were used to explore brain-wise WM macro- and microstructure abnormalities. To gain insight into disease-associated impairments in attentional and visuospatial processing, a third cohort of age-matched mice was assessed with the 5-choice serial reaction time task (5-CSRTT). We report cognitive impairments in R6/1 mice and, by evaluating MRI and light and electron microscopy results, we show that this HD mouse model presents disruptions in axonal morphology (i.e. less complex, thinner axons) and organization (i.e. more densely packed axons). Furthermore, we show that, at least early in disease progression, R6/1 mice present a reduction in the expression or content of myelin-associated proteins without significant alterations in the structure of myelin sheaths. Finally, our findings indicate that neuroinflammation-driven glial and axonal swelling might also affect this mouse model early in disease progression. Crucially, we demonstrate the potential of FR, an in vivo estimate of axon density, as a novel MRI biomarker of HD-associated changes in WM microstructure

Epstein-Barr-virus-positive large B-cell lymphoma associated with breast implants: an analysis of eight patients suggesting a possible pathogenetic relationship.

Breast implant anaplastic large cell lymphoma (ALCL) is a T-cell neoplasm arising around textured breast implants that was recognized recently as a distinct entity by the World Health Organization. Rarely, other types of lymphoma have been reported in patients with breast implants, raising the possibility of a pathogenetic relationship between breast implants and other types of lymphoma. We report eight cases of Epstein-Barr virus (EBV)-positive large B-cell lymphoma associated with breast implants. One of these cases was invasive, and the other seven neoplasms were noninvasive and showed morphologic overlap with breast implant ALCL. All eight cases expressed B-cell markers, had a non-germinal center B-cell immunophenotype, and were EBV+ with a latency type III pattern of infection. We compared the noninvasive EBV+ large B-cell lymphoma cases with a cohort of breast implant ALCL cases matched for clinical and pathologic stage. The EBV+ large B-cell lymphoma cases more frequently showed a thicker capsule, and more often were associated with calcification and prominent lymphoid aggregates outside of the capsule. The EBV+ B-cell lymphoma cells were more often arranged within necrotic fibrinoid material in a layered pattern. We believe that this case series highlights many morphologic similarities between EBV+ large B-cell lymphoma and breast implant ALCL. The data presented suggest a pathogenetic role for breast implants (as well as EBV) in the pathogenesis of EBV+ large B-cell lymphoma. We also provide some histologic findings useful for distinguishing EBV+ large B-cell lymphoma from breast implant ALCL in this clinical setting

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment