Physical function assessment tools in pediatric rheumatology

Pediatric rheumatic diseases with predominant musculoskeletal involvement such as juvenile idiopathic arthritis (JIA) and juvenile dermatomyositis(JDM) can cause considerable physical functional impairment and significantly affect the children's quality of life (QOL). Physical function, QOL, health-related QOL (HRQOL) and health status are personal constructs used as outcomes to estimate the impact of these diseases and often used as proxies for each other. The chronic, fluctuating nature of these diseases differs within and between patients, and complicates the measurement of these outcomes. In children, their growing needs and expectations, limited use of age-specific questionnaires, and the use of proxy respondents further influences this evaluation. This article will briefly review the different constructs inclusive of and related to physical function, and the scales used for measuring them. An understanding of these instruments will enable assessment of functional outcome in clinical studies of children with rheumatic diseases, measure the impact of the disease and treatments on their lives, and guide us in formulating appropriate interventions

Transcriptomic analysis of mRNA expression and alternative splicing during mouse sex determination

Mammalian sex determination hinges on sexually dimorphic transcriptional programs in developing fetal gonads. A comprehensive view of these programs is crucial for understanding the normal development of fetal testes and ovaries and the etiology of human disorders of sex development (DSDs), many of which remain unexplained. Using strand-specific RNA-sequencing, we characterized the mouse fetal gonadal transcriptome from 10.5 to 13.5 days post coitum, a key time window in sex determination and gonad development. Our dataset benefits from a greater sensitivity, accuracy and dynamic range compared to microarray studies, allows global dynamics and sex-specificity of gene expression to be assessed, and provides a window to non-transcriptional events such as alternative splicing. Spliceomic analysis uncovered female-specific regulation of Lef1 splicing, which may contribute to the enhanced WNT signaling activity in XX gonads. We provide a user-friendly visualization tool for the complete transcriptomic and spliceomic dataset as a resource for the field

GWAS and transcriptional analysis prioritize ITPR1 and CNTN4 for a serum uric acid 3p26 QTL in Mexican Americans

Background: The variation in serum uric acid concentrations is under significant genetic influence. Elevated SUA concentrations have been linked to increased risk for gout, kidney stones, chronic kidney disease, and cardiovascular disease whereas reduced serum uric acid concentrations have been linked to multiple sclerosis, Parkinson’s disease and Alzheimer’s disease. Previously, we identified a novel locus on chromosome 3p26 affecting serum uric acid concentrations in Mexican Americans from San Antonio Family Heart Study. As a follow up, we examined genome-wide single nucleotide polymorphism data in an extended cohort of 1281 Mexican Americans from multigenerational families of the San Antonio Family Heart Study and the San Antonio Family Diabetes/ Gallbladder Study. We used a linear regression-based joint linkage/association test under an additive model of allelic effect, while accounting for non-independence among family members via a kinship variance component. Results:Univariate genetic analysis indicated serum uric acid concentrations to be significant heritable (h2 = 0.50 ± 0.05, p Conclusion: Our results confirm the importance of the chromosome 3p26 locus and genetic variants in this region in the regulation of serum uric acid concentrations

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