Complete Multiwavelength Characterization of Faint Chandra X-ray Sources Seen in the Spitzer Wide-Area IR Extragalactic (SWIRE) Survey

We exploit deep combined observations with Spitzer and Chandra of the SWIRE survey in the ELAIS-N1 region, to investigate the nature of the faint X-ray and IR sources in common, to identify AGN/starburst diagnostics, and to study the sources of the X-ray and IR cosmic backgrounds. In the 17'x17' area of the Chandra ACIS-I image there are 3400 SWIRE near-IR sources with 4 sigma detections in at least 2 IRAC bands and 988 sources detected at 24micron with MIPS brighter than 0.1 mJy. Of these, 102 IRAC and 59 MIPS sources have Chandra counterparts, out of a total of 122 X-ray sources present in the area with S(0.5-8 kev)>10^(-15) erg/cm^2/s. We have constructed SEDs for each source using data from the 4 IRAC wavebands, Chandra fluxes, and optical follow-up data in the wavebands U, g', r', i', Z, and H. We fit a number of spectral templates to the SEDs at optical and infrared wavelengths to determine photometric redshifts and spectral categories, and also make use of diagnostics based on the X-ray luminosities, hardness ratios, X-ray to infrared spectral slopes and optical morphologies. Although we have spectroscopic redshifts for only a minority of the Chandra sources, the available SEDs constrain the redshifts for most of the sample sources, which turn out to be typically at 0.5<z<2. We find that 39% of the Chandra sources are dominated by type-1 AGN emission, 23% display optical/IR spectra typical of type-2 AGNs, while the remaining 38% fraction show starburst-like or even normal galaxy spectra. Since we prove that all these galaxies are dominated by AGN emission in X-rays this brings the fraction of type-1 AGNs to be 80% of the type-2: even assuming that all the Chandra sources undetected by Spitzer are type-2 AGNs, the type-1 fraction would exceed 1/3 of the total population (abridged).Comment: Accepted for publication in AJ, March 2005 issu

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

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

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

Genetically predicted cortisol levels and risk of venous thromboembolism

Introduction - In observational studies, venous thromboembolism (VTE) has been associated with Cushing’s syndrome and with persistent mental stress, two conditions associated with higher cortisol levels. However, it remains unknown whether high cortisol levels within the usual range are causally associated with VTE risk. We aimed to assess the association between plasma cortisol levels and VTE risk using Mendelian randomization. Methods - Three genetic variants in the SERPINA1/SERPINA6 locus (rs12589136, rs11621961 and rs2749527) were used to proxy plasma cortisol. The associations of the cortisol-associated genetic variants with VTE were acquired from the INVENT (28 907 cases and 157 243 non-cases) and FinnGen (6913 cases and 169 986 non-cases) consortia. Corresponding data for VTE subtypes were available from the FinnGen consortium and UK Biobank. Two-sample Mendelian randomization analyses (inverse-variance weighted method) were performed. Results - Genetic predisposition to higher plasma cortisol levels was associated with a reduced risk of VTE (odds ratio [OR] per one standard deviation increment 0.73, 95% confidence interval [CI] 0.62–0.87, p Conclusions - This study provides evidence that genetically predicted plasma cortisol levels in the high end of the normal range are associated with a decreased risk of VTE and that this association may be mediated by blood pressure. This study has implications for the planning of observational studies of cortisol and VTE, suggesting that blood pressure traits should be measured and accounted for

Commercially Available Outbred Mice for Genome-Wide Association Studies

Genome-wide association studies using commercially available outbred mice can detect genes involved in phenotypes of biomedical interest. Useful populations need high-frequency alleles to ensure high power to detect quantitative trait loci (QTLs), low linkage disequilibrium between markers to obtain accurate mapping resolution, and an absence of population structure to prevent false positive associations. We surveyed 66 colonies for inbreeding, genetic diversity, and linkage disequilibrium, and we demonstrate that some have haplotype blocks of less than 100 Kb, enabling gene-level mapping resolution. The same alleles contribute to variation in different colonies, so that when mapping progress stalls in one, another can be used in its stead. Colonies are genetically diverse: 45% of the total genetic variation is attributable to differences between colonies. However, quantitative differences in allele frequencies, rather than the existence of private alleles, are responsible for these population differences. The colonies derive from a limited pool of ancestral haplotypes resembling those found in inbred strains: over 95% of sequence variants segregating in outbred populations are found in inbred strains. Consequently it is possible to impute the sequence of any mouse from a dense SNP map combined with inbred strain sequence data, which opens up the possibility of cataloguing and testing all variants for association, a situation that has so far eluded studies in completely outbred populations. We demonstrate the colonies' potential by identifying a deletion in the promoter of H2-Ea as the molecular change that strongly contributes to setting the ratio of CD4+ and CD8+ lymphocytes

A Conserved Stem Loop Motif in the 5′Untranslated Region Regulates Transforming Growth Factor-β1 Translation

Transforming growth factor-β1 (TGF-β1) regulates cellular proliferation, differentiation, migration, and survival. The human TGF-β1 transcript is inherently poorly translated, and translational activation has been documented in relation to several stimuli. In this paper, we have sought to identify in cis regulatory elements within the TGF-β1 5′Untranslated Region (5′UTR). In silico analysis predicted formation of stable secondary structure in a G/C-rich element between nucleotides +77 to +106, and demonstrated that this element is highly conserved across species. Circular dichroism spectroscopy confirmed the presence of secondary structure in this region. The proximal 5′UTR was inhibitory to translation in reporter gene experiments, and mutation of the secondary structure motif increased translational efficiency. Translational regulation of TGF-β1 mRNA is linked to altered binding of YB-1 protein to its 5′UTR. Immunoprecipitation-RT-qPCR demonstrated a high basal association of YB-1 with TGF-β1 mRNA. However, mutation of the secondary structure motif did not prevent interaction of YB-1 with the 5′UTR, suggesting that YB-1 binds to this region due to its G/C-rich composition, rather than a specific, sequence-dependent, binding site. These data identify a highly conserved element within the TGF-β1 5′UTR that forms stable secondary structure, and is responsible for the inherent low translation efficiency of this cytokine

Comprehensive molecular characterization of gastric adenocarcinoma

Gastric cancer is a leading cause of cancer deaths, but analysis of its molecular and clinical characteristics has been complicated by histological and aetiological heterogeneity. Here we describe a comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project. We propose a molecular classification dividing gastric cancer into four subtypes: tumours positive for Epstein–Barr virus, which display recurrent PIK3CA mutations, extreme DNA hypermethylation, and amplification of JAK2, CD274 (also known as PD-L1) and PDCD1LG2 (also knownasPD-L2); microsatellite unstable tumours, which show elevated mutation rates, including mutations of genes encoding targetable oncogenic signalling proteins; genomically stable tumours, which are enriched for the diffuse histological variant and mutations of RHOA or fusions involving RHO-family GTPase-activating proteins; and tumours with chromosomal instability, which show marked aneuploidy and focal amplification of receptor tyrosine kinases. Identification of these subtypes provides a roadmap for patient stratification and trials of targeted therapies

Comprehensive Molecular Characterization of Pheochromocytoma and Paraganglioma

SummaryWe report a comprehensive molecular characterization of pheochromocytomas and paragangliomas (PCCs/PGLs), a rare tumor type. Multi-platform integration revealed that PCCs/PGLs are driven by diverse alterations affecting multiple genes and pathways. Pathogenic germline mutations occurred in eight PCC/PGL susceptibility genes. We identified CSDE1 as a somatically mutated driver gene, complementing four known drivers (HRAS, RET, EPAS1, and NF1). We also discovered fusion genes in PCCs/PGLs, involving MAML3, BRAF, NGFR, and NF1. Integrated analysis classified PCCs/PGLs into four molecularly defined groups: a kinase signaling subtype, a pseudohypoxia subtype, a Wnt-altered subtype, driven by MAML3 and CSDE1, and a cortical admixture subtype. Correlates of metastatic PCCs/PGLs included the MAML3 fusion gene. This integrated molecular characterization provides a comprehensive foundation for developing PCC/PGL precision medicine