TeV Particle Astrophysics II: Summary comments

A unifying theme of this conference was the use of different approaches to understand astrophysical sources of energetic particles in the TeV range and above. In this summary I review how gamma-ray astronomy, neutrino astronomy and (to some extent) gravitational wave astronomy provide complementary avenues to understanding the origin and role of high-energy particles in energetic astrophysical sources.Comment: 6 pages, 4 figures; Conference summary talk for "TeV Particle Astrophysics II" at University of Wisconsin, Madison, 28-31 August 200

Strong interface-induced spin-orbit coupling in graphene on WS2

Interfacial interactions allow the electronic properties of graphene to be modified, as recently demonstrated by the appearance of satellite Dirac cones in the band structure of graphene on hexagonal boron nitride (hBN) substrates. Ongoing research strives to explore interfacial interactions in a broader class of materials in order to engineer targeted electronic properties. Here we show that at an interface with a tungsten disulfide (WS2) substrate, the strength of the spin-orbit interaction (SOI) in graphene is very strongly enhanced. The induced SOI leads to a pronounced low-temperature weak anti-localization (WAL) effect, from which we determine the spin-relaxation time. We find that spin-relaxation time in graphene is two-to-three orders of magnitude smaller on WS2 than on SiO2 or hBN, and that it is comparable to the intervalley scattering time. To interpret our findings we have performed first-principle electronic structure calculations, which both confirm that carriers in graphene-on-WS2 experience a strong SOI and allow us to extract a spin-dependent low-energy effective Hamiltonian. Our analysis further shows that the use of WS2 substrates opens a possible new route to access topological states of matter in graphene-based systems.Comment: Originally submitted version in compliance with editorial guidelines. Final version with expanded discussion of the relation between theory and experiments to be published in Nature Communication

VERITAS Discovery of VHE Emission from the Radio Galaxy 3C 264: A Multi-Wavelength Study

The radio source 3C 264, hosted by the giant elliptical galaxy NGC 3862, was observed with VERITAS between February 2017 and May 2019. These deep observations resulted in the discovery of very-high-energy (VHE; E $>100$ GeV) $\gamma$-ray emission from this active galaxy. An analysis of $\sim$57 hours of quality-selected live time yields a detection at the position of the source, corresponding to a statistical significance of 7.8 standard deviations above background. The observed VHE flux is variable on monthly time scales, with an elevated flux seen in 2018 observations. The VHE emission during this elevated state is well-characterized by a power-law spectrum with a photon index $\Gamma = 2.20 \pm 0.27$ and flux F($>315$ GeV) = ($7.6\pm 1.2_{\mathrm stat} \pm 2.3_{\mathrm syst})\times 10^{-13}$ cm$^{-2}$ s$^{-1}$, or approximately 0.7% of the Crab Nebula flux above the same threshold. 3C 264 ($z = 0.0217$) is the most distant radio galaxy detected at VHE, and the elevated state is thought to be similar to that of the famously outbursting jet in M 87. Consequently, extensive contemporaneous multi-wavelength data were acquired in 2018 at the time of the VHE high state. An analysis of these data, including VLBA, VLA, HST, Chandra and Swift observations in addition to the VERITAS data, is presented, along with a discussion of the resulting spectral energy distribution.Comment: 19 pages, 11 figures, Accepted for publication in Astrophysical Journa

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