858 research outputs found

    TOI-2015b: A Warm Neptune with Transit Timing Variations Orbiting an Active mid M Dwarf

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    We report the discovery of a close-in (Porb=3.349daysP_{\mathrm{orb}} = 3.349\:\mathrm{days}) warm Neptune with clear transit timing variations (TTVs) orbiting the nearby (d=47.3pcd=47.3\:\mathrm{pc}) active M4 star, TOI-2015. We characterize the planet's properties using TESS photometry, precise near-infrared radial velocities (RV) with the Habitable-zone Planet Finder (HP) Spectrograph, ground-based photometry, and high-contrast imaging. A joint photometry and RV fit yields a radius Rp = 3.370.20+0.15RR_p~=~3.37_{-0.20}^{+0.15} \:\mathrm{R_\oplus}, mass mp = 16.44.1+4.1Mm_p~=~16.4_{-4.1}^{+4.1}\:\mathrm{M_\oplus}, and density ρp = 2.320.37+0.38gcm3\rho_p~=~2.32_{-0.37}^{+0.38} \:\mathrm{g cm^{-3}} for TOI-2015b, suggesting a likely volatile-rich planet. The young, active host star has a rotation period of Prot = 8.7± 0.9 daysP_{\mathrm{rot}}~=~8.7 \pm~0.9~\mathrm{days} and associated rotation-based age estimate of 1.1 ± 0.1Gyr1.1~\pm~0.1\:\mathrm{Gyr}. Though no other transiting planets are seen in the TESS data, the system shows clear TTVs of super period Psup  430daysP_{\mathrm{sup}}~\approx~430\:\mathrm{days} and amplitude \sim100minutes100\:\mathrm{minutes}. After considering multiple likely period ratio models, we show an outer planet candidate near a 2:1 resonance can explain the observed TTVs while offering a dynamically stable solution. However, other possible two-planet solutions -- including 3:2 and 4:3 resonance -- cannot be conclusively excluded without further observations. Assuming a 2:1 resonance in the joint TTV-RV modeling suggests a mass of mb = 13.34.5+4.7Mm_b~=~13.3_{-4.5}^{+4.7}\:\mathrm{M_\oplus} for TOI-2015b and mc = 6.82.3+3.5Mm_c~=~6.8_{-2.3}^{+3.5}\:\mathrm{M_\oplus} for the outer candidate. Additional transit and RV observations will be beneficial to explicitly identify the resonance and further characterize the properties of the system.Comment: 28 pages, 15 figures, 6 tables. As submitted to AAS Journal

    Two Dot1 isoforms in Saccharomyces cerevisiae as a result of leaky scanning by the ribosome

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    Dot1 is a conserved histone methyltransferase that methylates histone H3 on lysine 79. We previously observed that in Saccharomyces cerevisiae, a single DOT1 gene encodes two Dot1 protein species. Here, we show that the relative abundance of the two isoforms changed under nutrient-limiting conditions. A mutagenesis approach showed that the two Dot1 isoforms are produced from two alternative translation start sites as a result of leaky scanning by the ribosome. The leaky scanning was not affected by the 5′- or 3′-untranslated regions of DOT1, indicating that translation initiation is determined by the DOT1 coding sequence. Construction of yeast strains expressing either one of the isoforms showed that both were sufficient for Dot1’s role in global H3K79 methylation and telomeric gene silencing. However, the absence of the long isoform of Dot1 altered the resistance of yeast cells to the chitin-binding drug Calcofluor White, suggesting that the two Dot1 isoforms have a differential function in cell wall biogenesis

    Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

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    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

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    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

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    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

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    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
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