Identification of new DNA i-motif binding ligands through a fluorescent intercalator displacement assay

i-Motifs are quadruplex DNA structures formed from sequences rich in cytosine and held together by intercalated, hemi-protonated cytosine–cytosine base pairs. These sequences are prevalent in gene promoter regions and may play a role in gene transcription. Targeting these structures with ligands could provide a novel way to target genetic disease but there are very few ligands which have been shown to interact with i-motif DNA. Fluorescent intercalator displacement (FID) assays are a simple way to screen ligands against DNA secondary structures. Here we characterise how thiazole orange interacts with i-motif DNA and assess its ability for use in a FID assay. Additionally, we report FID-based ligand screening using thiazole orange against the i-motif forming sequence from the human telomere to reveal new i-motif binding compounds which have the potential for further development

Quantifying Microstructural Evolution in Moving Magma

Many of the grand challenges in volcanic and magmatic research are focused on understanding the dynamics of highly heterogeneous systems and the critical conditions that enable magmas to move or eruptions to initiate. From the formation and development of magma reservoirs, through propagation and arrest of magma, to the conditions in the conduit, gas escape, eruption dynamics, and beyond into the environmental impacts of that eruption, we are trying to define how processes occur, their rates and timings, and their causes and consequences. However, we are usually unable to observe the processes directly. Here we give a short synopsis of the new capabilities and highlight the potential insights that in situ observation can provide. We present the XRheo and Pele furnace experimental apparatus and analytical toolkit for the in situ X-ray tomography-based quantification of magmatic microstructural evolution during rheological testing. We present the first 3D data showing the evolving textural heterogeneity within a shearing magma, highlighting the dynamic changes to microstructure that occur from the initiation of shear, and the variability of the microstructural response to that shear as deformation progresses. The particular shear experiments highlighted here focus on the effect of shear on bubble coalescence with a view to shedding light on both magma transport and fragmentation processes. The XRheo system is intended to help us understand the microstructural controls on the complex and non-Newtonian evolution of magma rheology, and is therefore used to elucidate the many mobilization, transport, and eruption phenomena controlled by the rheological evolution of a multi-phase magmatic flows. The detailed, in situ characterization of sample textures presented here therefore represents the opening of a new field for the accurate parameterization of dynamic microstructural control on rheological behavior

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

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

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

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

Making sense of the evolving nature of depression narratives and their inherent conflicts

Originally a psychiatric diagnosis fashioned by Western psychiatry in the 20th Century, depression evolved to encompass varying lineages of discourse and care. This article elucidates some of the current challenges – as well as emerging discourses – influencing the category of depression. Depression-like experiences are shaped by (at times conflicting) subjectivities, claims to knowledge, material realities, social contexts and access to resources. With no unified understanding of the category of ‘depression’ available, lay people, social and neuro scientists, GPs, psychiatrists, talking therapists and pharmaceutical companies all attempt to shape narratives of depression. The current paper focuses on patient narratives about depression – in the context of these wider debates – to better elucidate the ways in which depression discourses are publically developing along varying lines. In conclusion, the paper suggests that we could better conceptualise the resulting ‘depression(s)’ with concepts such as ‘society of mind’ and notions of subjectivity unbounded by individuals

Selective Serotonin Reuptake Inhibitor (SSRI) Antidepressants in Pregnancy and Congenital Anomalies: Analysis of Linked Databases in Wales, Norway and Funen, Denmark

Background: Hypothesised associations between in utero exposure to selective serotonin reuptake inhibitors (SSRIs) and congenital anomalies, particularly congenital heart defects (CHD), remain controversial. We investigated the putative teratogenicity of SSRI prescription in the 91 days either side of first day of last menstrual period (LMP). Methods and Findings: Three population-based EUROCAT congenital anomaly registries- Norway (2004–2010), Wales (2000–2010) and Funen, Denmark (2000–2010)—were linked to the electronic healthcare databases holding prospectively collected prescription information for all pregnancies in the timeframes available. We included 519,117 deliveries, including foetuses terminated for congenital anomalies, with data covering pregnancy and the preceding quarter, including 462,641 with data covering pregnancy and one year either side. For SSRI exposures 91 days either side of LMP, separately and together, odds ratios with 95% confidence intervals (ORs, 95%CI) for all major anomalies were estimated. We also explored: pausing or discontinuing SSRIs preconception, confounding, high dose regimens, and, in Wales, diagnosis of depression. Results were combined in meta-analyses. SSRI prescription 91 days either side of LMP was associated with increased prevalence of severe congenital heart defects (CHD) (as defined by EUROCAT guide 1.3, 2005) (34/12,962 [0.26%] vs. 865/506,155 [0.17%] OR 1.50, 1.06–2.11), and the composite adverse outcome of 'anomaly or stillbirth' (473/12962, 3.65% vs. 15829/506,155, 3.13%, OR 1.13, 1.03–1.24). The increased prevalence of all major anomalies combined did not reach statistical significance (3.09% [400/12,962] vs. 2.67% [13,536/506,155] OR 1.09, 0.99–1.21). Adjusting for socio-economic status left ORs largely unchanged. The prevalence of anomalies and severe CHD was reduced when SSRI prescriptions were stopped or paused preconception, and increased when >1 prescription was recorded, but differences were not statistically significant. The dose-response relationship between severe CHD and SSRI dose (meta-regression OR 1.49, 1.12–1.97) was consistent with SSRI-exposure related risk. Analyses in Wales suggested no associations between anomalies and diagnosed depression. Conclusion: The additional absolute risk of teratogenesis associated with SSRIs, if causal, is small. However, the high prevalence of SSRI use augments its public health importance, justifying modifications to preconception care