We undertook a comprehensive proteogenomic characterization of 95 prospectively collected endometrial carcinomas, comprising 83 endometrioid and 12 serous tumors. This analysis revealed possible new consequences of perturbations to the p53 and Wnt/β-catenin pathways, identified a potential role for circRNAs in the epithelial-mesenchymal transition, and provided new information about proteomic markers of clinical and genomic tumor subgroups, including relationships to known druggable pathways. An extensive genome-wide acetylation survey yielded insights into regulatory mechanisms linking Wnt signaling and histone acetylation. We also characterized aspects of the tumor immune landscape, including immunogenic alterations, neoantigens, common cancer/testis antigens, and the immune microenvironment, all of which can inform immunotherapy decisions. Collectively, our multi-omic analyses provide a valuable resource for researchers and clinicians, identify new molecular associations of potential mechanistic significance in the development of endometrial cancers, and suggest novel approaches for identifying potential therapeutic targets.
RCy3 is an R package in Bioconductor that communicates with Cytoscape via its REST API, providing access to the full feature set of Cytoscape from within the R programming environment. RCy3 has been redesigned to streamline its usage and future development as part of a broader Cytoscape Automation effort. Over 100 new functions have been added, including dozens of helper functions specifically for intuitive data overlay operations. Over 40 Cytoscape apps have implemented automation support so far, making hundreds of additional operations accessible via RCy3. Two-way conversion with networks from \textit{igraph} and \textit{graph} ensures interoperability with existing network biology workflows and dozens of other Bioconductor packages. These capabilities are demonstrated in a series of use cases involving public databases, enrichment analysis pipelines, shortest path algorithms and more. With RCy3, bioinformaticians will be able to quickly deliver reproducible network biology workflows as integrations of Cytoscape functions, complex custom analyses and other R packages.
Huntington’s disease (HD) is a monogenic disorder that is caused by a CAG repeat expansion in the HTT gene. However, beyond the CAG repeat size other genes also contribute to variations in neurodegeneration of the cortex and striatum as well as the timing of disease onset1,2. The standard method to find genetic modifiers of HD has been the use of genome-wide association studies (GWAS) of large numbers of unrelated patients1,3-5. Previous efforts in this vein have identified single nucleotide variants (SNVs) significantly associated with pathways involved in DNA damage and handling that modify HD age of onset (AO)1,3-8. However, many of these associations have small effect sizes, and typically it is not known whether the SNVs identified with GWAS are the basis for the modifying effect. Here, to augment modifier GWAS, we set out to identify variants that may modify AO in HD by performing family-based studies. We performed whole genome sequencing in families with HD in which individuals with similar CAG expansions showed variation in AO (ranging from a 3- to 20-year difference). We examined the segregation of every variant in the genome and associated the occurrence of those variants with AO. Focusing on rare and uncommon variants, we used a priori knowledge to examine the proximity of our top variants to previously reported GWAS loci. Further, we developed an HD impact scoring system to rank each variant and highlight those most likely to be impactful in the context of influencing the pathology associated with the CAG repeat expansion mutation. Pathway enrichment analysis of these genes revealed numerous pathways previously implicated in HD, as well as novel pathways that may be important in disease onset. Finally, we showed that a putative AO modifier in the ovarian-tumor-domain-containing deubiquitinase 3 (OTUD3) gene correlated with an altered rate of degeneration in patient-derived neurons, and that knockdown of OTUD3 accelerated degeneration in a human cell model of HD, validating our approach. This family-based strategy creates a novel resource for the HD community and establishes a framework that could be applied to study genetic modifiers of many other rare familial diseases.
Cytoscape is the premiere platform for interactive analysis, integration and visualization of network data. While Cytoscape itself delivers much basic functionality, it relies on community-written apps to deliver specialized functions and analyses. To date, Cytoscape's CyREST feature has allowed researchers to write workflows that call basic Cytoscape functions, but provides no access to its high value app-based functions. With Cytoscape Automation, workflows can now call apps that have been upgraded to expose their functionality. This article collection is a resource to assist readers in quickly and economically leveraging such apps in reproducible workflows that scale independently to large data sets and production runs.
Mortality is high among patients heart failure (HF) who are receiving treatment, and therefore identifying new pathways rooted in preclinical cardiac remodeling phenotypes may afford novel biomarkers and therapeutic avenues. Circulating extracellular RNAs (ex-RNAs) are an emerging class of biomarkers with target-organ epigenetic effects relevant to myocardial biology, although large human investigations remain limited.To measure the association of highly expressed circulating ex-RNAs with left ventricular remodeling and incident HF in a community-based cohort.This is a prospective observational cohort study of individuals who were included in the eighth examination of the Framingham Offspring Cohort (2005-2008). Collected data include measurements of the left ventricle via electrocardiography, determination of circulating ex-RNAs in plasma, and incidence of heart failure. Data analysis was completed from December 2016 to June 2018.A total of 398 circulating ex-RNA molecules in plasma were measured by reverse transcription polymerase chain reaction; disease ontology analysis was also performed.Echocardiographic indices of left ventricular (LV) remodeling and incident heart failure.A total of 2763 participants of the Framingham Heart Study with measured ex-RNAs (mean [SD] age, 66.3 [9.0] years; 1499 [54.3%] female) were included in this study. Of this sample, 2429 to 2432 individuals had echocardiographic measures recorded (depending on the measurement). A total of 2681 individuals had HF status determined, of whom 116 (4.3%) experienced HF (median [interquartile range] follow-up, 7.7 [6.6-8.6] years). We identified 12 ex-RNAs associated with LV mass and at least 1 other echocardiographic phenotype (LV end-diastolic volume or left atrial dimension). Of these 12 ex-RNAs, 3 micro RNAs (miR-17, miR-20a, and miR-106b) were associated with a 15% reduction in long-term incident HF per 2-fold increase in circulating level during the follow-up period, after adjustments for age, sex, established HF risk factors, and prevalent or interim myocardial infarction. These 3 RNAs shared sequence homology and targeted a shared group of messenger RNAs that specified pathways relevant to HF (eg, transforming growth factor-β signaling, growth/cell cycle, and apoptosis), and shared a disease association with hypertension in disease ontology analysis.This study identifies a group of circulating, noncoding RNAs associated with echocardiographic phenotypes, long-term incident HF, and pathways relevant to myocardial remodeling in a large community-based sample. Further investigations into the functional biology of these ex-RNAs are warranted for surveillance for HF prevention.
Abstract Glioma is a complex disease that is unlikely to result from the effect of a single gene. Genetic analysis at the pathway level involving multiple genes may be more likely to capture gene-disease associations than analyzing genes one at a time. The current pilot study included 112 Caucasians with glioblastoma multiforme and 112 Caucasian healthy controls frequency matched to cases by age and gender. Subjects were genotyped using a commercially available (ParAllele/Affymetrix) assay panel of 10,177 nonsynonymous coding single-nucleotide polymorphisms (SNP) spanning the genome known at the time the panel was constructed. For this analysis, we selected 10 pathways potentially involved in gliomagenesis that had SNPs represented on the panel. We performed random forests (RF) analyses of SNPs within each pathway group and logistic regression to assess interaction among genes in the one pathway for which the RF prediction error was better than chance and the permutation P < 0.10. Only the DNA repair pathway had a better than chance classification of case-control status with a prediction error of 45.5% and P = 0.09. Three SNPs (rs1047840 of EXO1, rs12450550 of EME1, and rs799917 of BRCA1) of the DNA repair pathway were identified as promising candidates for further replication. In addition, statistically significant interactions (P < 0.05) between rs1047840 of EXO1 and rs799917 or rs1799966 of BRCA1 were observed. Despite less than complete inclusion of genes and SNPs relevant to glioma and a small sample size, RF analysis identified one important biological pathway and several SNPs potentially associated with the development of glioblastoma. (Cancer Epidemiol Biomarkers Prev 2008;17(6):1368–73)
