A review of assistive technology and writing skills for students with physical and educational disabilities

In recent years effective instruction in reading for learners with physicaland educational disabilities has received great attention in the schools.However, instruction in the corollary skill of writing has received considerably less emphasis. This review paper notes that through the use of assistive technology, students with a variety of physical and educationaldisabilities can learn to effectively (a) plan and organize their writing,(b) draft and transcribe their work, and (c) edit and revise their narrativeand expository writing.With teachers increasingly being held accountable for the development ofliteracy skills in all students, including those students with physical and educational disabilities, schools are paying substantial and growing attention to reading. The expressive side of the literacy coin, writing skills, is arguably equally significant and worthy of instructional emphasis. However, there are growing indicators that writing has not received enough attention in the national educational reform debate (National Commission on Writing, 2003, 2006; National Writing Project & Nagin, 2006). Along with reading comprehension, writing skill is a powerful predictor of academic success (Graham & Perin, 2007), and is an effective means of developing higher-order thinking skills (National Writing Project & Nagin, 2006). Writing helps learners make sense of the world (e.g., “Letters from Ground Zero,” cited in National Commission on Writing, 2006). Yet to date the teaching of writing skills to students with disabilities, including physical disabilities, has not received the level of curricular emphasis that teaching reading skills has (Graham & Perin, 2007). For students with physical and educational disabilities, stronger writing skills offer a variety of benefits. These include (a) more successful academic inclusion outcomes, (b) transfer of improved literacy skills to reading, and (c) greater pass rates on high stakes academic testing. As more and more careers require greater levels of literacy skills, students with disabilities who are unable to write effectively may find themselves increasingly minimized in these adult roles. Writing is considered to be an essential “threshold skill” for hiring and promotion (National Commission on Writing, 2003), and is a basic requirement for participation in civic life and the global economy (Graham & Perin, 2007; National Commission on Writing, 2003). This paper reviews the use of a variety of assistive technologies in enhancing writing skills in students with physical and educational disabilities

Social Structure, Reasonable Gain, and Entrepreneurship in Africa

EPSRC and DFI

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

ABCA transporter gene expression and poor outcome in epithelial ovarian cancer

Background ATP-binding cassette (ABC) transporters play various roles in cancer biology and drug resistance, but their association with outcomes in serous epithelial ovarian cancer (EOC) is unknown. Methods The relationship between clinical outcomes and ABC transporter gene expression in two independent cohorts of high-grade serous EOC tumors was assessed with real-time quantitative polymerase chain reaction, analysis of expression microarray data, and immunohistochemistry. Associations between clinical outcomes and ABCA transporter gene single nucleotide polymorphisms were tested in a genome-wide association study. Impact of short interfering RNA-mediated gene suppression was determined by colony forming and migration assays. Association with survival was assessed with Kaplan-Meier analysis and log-rank tests. All statistical tests were two-sided. Results Associations with outcome were observed with ABC transporters of the A subfamily, but not with multidrug transporters. High-level expression of ABCA1, ABCA6, ABCA8, and ABCA9 in primary tumors was statistically significantly associated with reduced survival in serous ovarian cancer patients. Low levels of ABCA5 and the C-allele of rs536009 were associated with shorter overall survival (hazard ratio for death = 1.50; 95% confidence interval [CI] =1.26 to 1.79; P = 6.5e-6). The combined expression pattern of ABCA1, ABCA5, and either ABCA8 or ABCA9 was associated with particularly poor outcome (mean overall survival in group with adverse ABCA1, ABCA5 and ABCA9 gene expression = 33.2 months, 95% CI = 26.4 to 40.1; vs 55.3 months in the group with favorable ABCA gene expression, 95% CI = 49.8 to 60.8; P =. 001), independently of tumor stage or surgical debulking status. Suppression of cholesterol transporter ABCA1 inhibited ovarian cancer cell growth and migration in vitro, and statin treatment reduced ovarian cancer cell migration. Conclusions Expression of ABCA transporters was associated with poor outcome in serous ovarian cancer, implicating lipid trafficking as a potentially important process in EOC. © 2014 The Author 2014. Published by Oxford University Press. All rights reserved

Pleiotropy-guided transcriptome imputation from normal and tumor tissues identifies candidate susceptibility genes for breast and ovarian cancer.

Familial, sequencing, and genome-wide association studies (GWASs) and genetic correlation analyses have progressively unraveled the shared or pleiotropic germline genetics of breast and ovarian cancer. In this study, we aimed to leverage this shared germline genetics to improve the power of transcriptome-wide association studies (TWASs) to identify candidate breast cancer and ovarian cancer susceptibility genes. We built gene expression prediction models using the PrediXcan method in 681 breast and 295 ovarian tumors from The Cancer Genome Atlas and 211 breast and 99 ovarian normal tissue samples from the Genotype-Tissue Expression project and integrated these with GWAS meta-analysis data from the Breast Cancer Association Consortium (122,977 cases/105,974 controls) and the Ovarian Cancer Association Consortium (22,406 cases/40,941 controls). The integration was achieved through application of a pleiotropy-guided conditional/conjunction false discovery rate (FDR) approach in the setting of a TWASs. This identified 14 candidate breast cancer susceptibility genes spanning 11 genomic regions and 8 candidate ovarian cancer susceptibility genes spanning 5 genomic regions at conjunction FDR 1 Mb away from known breast and/or ovarian cancer susceptibility loci. We also identified 38 candidate breast cancer susceptibility genes and 17 candidate ovarian cancer susceptibility genes at conjunction FDR < 0.05 at known breast and/or ovarian susceptibility loci. The 22 genes identified by our cross-cancer analysis represent promising candidates that further elucidate the role of the transcriptome in mediating germline breast and ovarian cancer risk