Multiple myeloma with central nervous system relapse

Central nervous system involvement in multiple myeloma is a rare complication but carries a very poor prognosis. We provide a review of current literature, including presentation, treatment and survival data, and describe our experience in a regional hematologic malignancy diagnosis center where, over a 15-year period, ten cases were identified. Although the median age of onset, frequently between 50-60 years, is comparatively young, those diagnosed usually have a preceding diagnosis of multiple myeloma and often have had several lines of treatment. We discuss putative underlying factors such as prior treatment and associations including possible risk factors and features suggestive of a distinct biology. Central nervous system involvement may be challenging to diagnose in myeloma, displaying heterogeneous symptoms that can be confounded by neurological symptoms caused by the typical features of myeloma or treatment side-effects. We discuss the clinical features, imaging and laboratory methods used in diagnosis, and highlight the importance of considering this rare complication when neurological symptoms occur at presentation or, more commonly, during the disease pathway. In the absence of clinical trial data to inform an evidence-based approach to treatment, we discuss current and novel treatment options. Finally, we propose the establishment of an International Registry of such cases as the best way to collect and subsequently disseminate presentation, diagnostic and treatment outcome data on this rare complication of multiple myeloma

Assessment at UK medical schools varies substantially in volume, type and intensity and correlates with postgraduate attainment

BACKGROUND: In the United Kingdom (UK), medical schools are free to develop local systems and policies that govern student assessment and progression. Successful completion of an undergraduate medical degree results in the automatic award of a provisional licence to practice medicine by the General Medical Council (GMC). Such a licensing process relies heavily on the assumption that individual schools develop similarly rigorous assessment policies. Little work has evaluated variability of undergraduate medical assessment between medical schools. That absence is important in the light of the GMC's recent announcement of the introduction of the UKMLA (UK Medical Licensing Assessment) for all doctors who wish to practise in the UK. The present study aimed to quantify and compare the volume, type and intensity of summative assessment across medicine (A100) courses in the United Kingdom, and to assess whether intensity of assessment correlates with the postgraduate attainment of doctors from these schools. METHODS: Locally knowledgeable students in each school were approached to take part in guided-questionnaire interviews via telephone or Skype(TM). Their understanding of assessment at their medical school was probed, and later validated with the assessment department of the respective medical school. We gathered data for 25 of 27 A100 programmes in the UK and compared volume, type and intensity of assessment between schools. We then correlated these data with the mean first-attempt score of graduates sitting MRCGP and MRCP(UK), as well as with UKFPO selection measures. RESULTS: The median written assessment volume across all schools was 2000 min (mean = 2027, SD = 586, LQ = 1500, UQ = 2500, range = 1000-3200) and 1400 marks (mean = 1555, SD = 463, LQ = 1200, UQ = 1800, range = 1100-2800). The median practical assessment volume was 400 min (mean = 472, SD = 207, LQ = 400, UQ = 600, range = 200-1000). The median intensity (minutes per mark ratio) of summative written assessment was 1.24 min per mark (mean = 1.28, SD = 0.30, LQ = 1.11, UQ = 1.37, range = 0.85-2.08). An exploratory analysis suggested a significant correlation of total assessment time with mean first-attempt score on both the knowledge and the clinical assessments of MRCGP and of MRCP(UK). CONCLUSIONS: There are substantial differences in the volume, format and intensity of undergraduate assessment between UK medical schools. These findings suggest a potential for differences in the reliability of detecting poorly performing students, or differences in identifying and stratifying academically equivalent students for ranking in the Foundation Programme Application System (FPAS). Furthermore, these differences appear to directly correlate with performance in postgraduate examinations. Taken together, our findings highlight highly variable local assessment procedures that warrant further investigation to establish their potential impact on students

Large-scale functional inference for skin-expressing lncRNAs using expression and sequence information

Long noncoding RNAs (lncRNAs) regulate the expression of protein-coding genes and have been shown to play important roles in inflammatory skin diseases. However, we still have limited understanding of the functional impact of lncRNAs in skin, partly due to their tissue specificity and lower expression levels compared with protein-coding genes. We compiled a comprehensive list of 18,517 lncRNAs from different sources and studied their expression profiles in 834 RNA-Seq samples from multiple inflammatory skin conditions and cytokine-stimulated keratinocytes. Applying a balanced random forest to predict involvement in biological functions, we achieved a median AUROC of 0.79 in 10-fold cross-validation, identifying significant DNA binding domains (DBDs) for 39 lncRNAs. G18244, a skin-expressing lncRNA predicted for IL-4/IL-13 signaling in keratinocytes, was highly correlated in expression with F13A1, a protein-coding gene involved in macrophage regulation, and we further identified a significant DBD in F13A1 for G18244. Reflecting clinical implications, AC090198.1 (predicted for IL-17 pathway) and AC005332.6 (predicted for IFN-γ pathway) had significant negative correlation with the SCORAD metric for atopic dermatitis. We also utilized single-cell RNA and spatial sequencing data to validate cell type specificity. Our research demonstrates lncRNAs have important immunological roles and can help prioritize their impact on inflammatory skin diseases.</p

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