Three Gravitational Lenses for the Price of One: Enhanced Strong Lensing through Galaxy Clustering

We report the serendipitous discovery of two strong gravitational lens candidates (ACS J160919+6532 and ACS J160910+6532) in deep images obtained with the Advanced Camera for Surveys on the Hubble Space Telescope, each less than 40 arcsec from the previously known gravitational lens system CLASS B1608+656. The redshifts of both lens galaxies have been measured with Keck and Gemini: one is a member of a small galaxy group at z~0.63, which also includes the lensing galaxy in the B1608+656 system, and the second is a member of a foreground group at z~0.43. By measuring the effective radii and surface brightnesses of the two lens galaxies, we infer their velocity dispersions based on the passively evolving Fundamental Plane (FP) relation. Elliptical isothermal lens mass models are able to explain their image configurations within the lens hypothesis, with a velocity dispersion compatible with that estimated from the FP for a reasonable source-redshift range. Based on the large number of massive early-type galaxies in the field and the number-density of faint blue galaxies, the presence of two additional lens systems around CLASS B1608+656 is not unlikely in hindsight. Gravitational lens galaxies are predominantly early-type galaxies, which are clustered, and the lensed quasar host galaxies are also clustered. Therefore, obtaining deep high-resolution images of the fields around known strong lens systems is an excellent method of enhancing the probability of finding additional strong gravitational lens systems.Comment: Submitted to ApJ. 8 pages, 6 figure

Strong gravitational lensing probes of the particle nature of dark matter

There is a vast menagerie of plausible candidates for the constituents of dark matter, both within and beyond extensions of the Standard Model of particle physics. Each of these candidates may have scattering (and other) cross section properties that are consistent with the dark matter abundance, BBN, and the most scales in the matter power spectrum; but which may have vastly different behavior at sub-galactic "cutoff" scales, below which dark matter density fluctuations are smoothed out. The only way to quantitatively measure the power spectrum behavior at sub-galactic scales at distances beyond the local universe, and indeed over cosmic time, is through probes available in multiply imaged strong gravitational lenses. Gravitational potential perturbations by dark matter substructure encode information in the observed relative magnifications, positions, and time delays in a strong lens. Each of these is sensitive to a different moment of the substructure mass function and to different effective mass ranges of the substructure. The time delay perturbations, in particular, are proving to be largely immune to the degeneracies and systematic uncertainties that have impacted exploitation of strong lenses for such studies. There is great potential for a coordinated theoretical and observational effort to enable a sophisticated exploitation of strong gravitational lenses as direct probes of dark matter properties. This opportunity motivates this white paper, and drives the need for: a) strong support of the theoretical work necessary to understand all astrophysical consequences for different dark matter candidates; and b) tailored observational campaigns, and even a fully dedicated mission, to obtain the requisite data.Comment: Science white paper submitted to the Astro2010 Decadal Cosmology & Fundamental Physics Science Frontier Pane

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

Comprehensive Pan-Genomic Characterization of Adrenocortical Carcinoma

SummaryWe describe a comprehensive genomic characterization of adrenocortical carcinoma (ACC). Using this dataset, we expand the catalogue of known ACC driver genes to include PRKAR1A, RPL22, TERF2, CCNE1, and NF1. Genome wide DNA copy-number analysis revealed frequent occurrence of massive DNA loss followed by whole-genome doubling (WGD), which was associated with aggressive clinical course, suggesting WGD is a hallmark of disease progression. Corroborating this hypothesis were increased TERT expression, decreased telomere length, and activation of cell-cycle programs. Integrated subtype analysis identified three ACC subtypes with distinct clinical outcome and molecular alterations which could be captured by a 68-CpG probe DNA-methylation signature, proposing a strategy for clinical stratification of patients based on molecular markers

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