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

Glastir Monitoring & Evaluation Programme. First year annual report

The Welsh Government has commissioned a comprehensive new ecosystem monitoring and evaluation programme to monitor the effects of Glastir, its new land management scheme, and to monitor progress towards a range of international biodiversity and environmental targets. A random sample of 1 km squares stratified by landcover types will be used both to monitor change at a national level in the wider countryside and to provide a backdrop against which intervention measures are assessed using a second sample of 1 km squares located in areas eligible for enhanced payments for advanced interventions. Modelling in the first year has forecast change based on current understanding, whilst a rolling national monitoring programme based on an ecosystem approach will provide an evidence-base for on-going, adaptive development of the scheme by Welsh Government. To our knowledge, this will constitute the largest and most in-depth ecosystem monitoring and evaluation programme of any member state of the European Union

Glastir Monitoring & Evaluation Programme. Second year annual report

What is the purpose of Glastir Monitoring and Evaluation Programme? Glastir is the main scheme by which the Welsh Government pays for environmental goods and services whilst the Glastir Monitoring and Evaluation Programme (GMEP) evaluates the scheme’s success. Commissioning of the monitoring programme in parallel with the launch of the Glastir scheme provides fast feedback and means payments can be modified to increase effectiveness. The Glastir scheme is jointly funded by the Welsh Government (through the Rural Development Plan) and the EU. GMEP will also support a wide range of other national and international reporting requirements. What is the GMEP approach? GMEP collects evidence for the 6 intended outcomes from the Glastir scheme which are focussed on climate change, water and soil quality, biodiversity, landscape, access and historic environment, woodland creation and management. Activities include; a national rolling monitoring programme of 1km squares; new analysis of long term data from other schemes combining with GMEP data where possible; modelling to estimate future outcomes so that adjustments can be made to maximise impact of payments; surveys to assess wider socio-economic benefits; and development of novel technologies to increase detection and efficiency of future assessments. How has GMEP progressed in this 2nd year? 90 GMEP squares were surveyed in Year 2 to add to the 60 completed in Year 1 resulting in 50% of the 300 GMEP survey squares now being completed. Squares will be revisited on a 4 year cycle providing evidence of change in response to Glastir and other pressures such as changing economics of the farm business, climate change and air pollution. This first survey cycle collects the baseline against which future changes will be assessed. This is important as GMEP work this year has demonstrated land coming into the scheme is different in some respects to land outside the scheme. Therefore, future analysis to detect impact of Glastir will be made both against the national backdrop from land outside the scheme and this baseline data from land in scheme. A wide range of analyses of longterm data has been completed for all Glastir Outcomes with the exception of landscape quality and historic features condition for which limited data is available. This has involved combining data with 2013/14 GMEP data when methods allow. Overall analysis of long term data indicates one of stability but with little evidence of improvement with the exception of headwater quality, greenhouse gas emissions and woodland area for which there has been improvement over the last 20 years. Some headline statistics include: 51% of historic features in excellent or sound condition; two thirds of public rights of way fully open and accessible; improvement in hedgerow management with 85% surveyed cut in the last 3 years but < 1% recently planted; 91% of streams had some level of modification but 60% retained good ecological quality; no change topsoil carbon content over last 25 years. What is innovative? GMEP has developed various new metrics to allow for more streamlined reporting in the future. For example a new Priority Bird species Index for Wales which combines data from 35 species indicates at least half have stable or increasing populations. The new GMEP Visual Quality Landscape Index has been tested involving over 2600 respondents. Results have demonstrated its value as an objective and repeatable method for quantifying change in visual landscape quality. A new unified peat map for Wales has been developed which has been passed to Glastir Contract Managers to improve targeting of payments when negotiating Glastir contracts. An estimate of peat soil contribution to current greenhouse gas emissions due to human modification has been calculated. Models have allowed quantification of land area helping to mitigate rainfall runoff. We are using new molecular tools to explore the effects of Glastir on soil organisms and satellite technologies to quantify e.g. small woody features and landcover change. Finally we are using a community approach to develop a consensus on how to define and report change in High Nature Value Farmland which will be reported in the Year 3 GMEP report

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies

Glastir Monitoring & Evaluation Programme. Final report

Final Report to Welsh Government, prepared by CEH on behalf of the Glastir Monitoring & Evaluation Programme Team. The Glastir Monitoring and Evaluation Programme (GMEP) provides a comprehensive programme to establish a baseline against which future assessments of Glastir can be made. GMEP also contributes national trend data which supports a range of national and international biodiversity and environmental targets. GMEP fulfils a commitment by the Welsh Government to establish a monitoring programme concurrently with the launch of the Glastir scheme. The use of models and farmer surveys provides early indicators of the likely direction, magnitude and timing of future outcomes. The programme ensures compliance with the rigorous requirements of the European Commission’s Common Monitoring and Evaluation Framework (CMEF) through the Rural Development Plan (RDP) for Wales. This report represents the final results of the GMEP programme which ran from 2012 to 2016

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation