LSST Science Book, Version 2.0

A survey that can cover the sky in optical bands over wide fields to faint magnitudes with a fast cadence will enable many of the exciting science opportunities of the next decade. The Large Synoptic Survey Telescope (LSST) will have an effective aperture of 6.7 meters and an imaging camera with field of view of 9.6 deg^2, and will be devoted to a ten-year imaging survey over 20,000 deg^2 south of +15 deg. Each pointing will be imaged 2000 times with fifteen second exposures in six broad bands from 0.35 to 1.1 microns, to a total point-source depth of r~27.5. The LSST Science Book describes the basic parameters of the LSST hardware, software, and observing plans. The book discusses educational and outreach opportunities, then goes on to describe a broad range of science that LSST will revolutionize: mapping the inner and outer Solar System, stellar populations in the Milky Way and nearby galaxies, the structure of the Milky Way disk and halo and other objects in the Local Volume, transient and variable objects both at low and high redshift, and the properties of normal and active galaxies at low and high redshift. It then turns to far-field cosmological topics, exploring properties of supernovae to z~1, strong and weak lensing, the large-scale distribution of galaxies and baryon oscillations, and how these different probes may be combined to constrain cosmological models and the physics of dark energy.Comment: 596 pages. Also available at full resolution at http://www.lsst.org/lsst/sciboo

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

Quantitative Magnetic Resonance Imaging in Perianal Crohn’s Disease at 1.5 and 3.0 T: A Feasibility Study

From MDPI via Jisc Publications RouterHistory: accepted 2021-11-12, pub-electronic 2021-11-17Publication status: PublishedFunder: Medical Research Council; Grant(s): MC_PC_15033Perianal Crohn’s Disease (pCD) is a common manifestation of Crohn’s Disease. Absence of reliable disease measures makes disease monitoring unreliable. Qualitative MRI has been increasingly used for diagnosing and monitoring pCD and has shown potential for assessing response to treatment. Quantitative MRI sequences, such as diffusion-weighted imaging (DWI), dynamic contrast enhancement (DCE) and magnetisation transfer (MT), along with T2 relaxometry, offer opportunities to improve diagnostic capability. Quantitative MRI sequences (DWI, DCE, MT and T2) were used in a cohort of 25 pCD patients before and 12 weeks after biological therapy at two different field strengths (1.5 and 3 T). Disease activity was measured with the Perianal Crohn’s Disease Activity index (PDAI) and serum C-reactive protein (CRP). Diseased tissue areas on MRI were defined by a radiologist. A baseline model to predict outcome at 12 weeks was developed. No differences were seen in the quantitative MR measured in the diseased tissue regions from baseline to 12 weeks; however, PDAI and CRP decreased. Baseline PDAI, CRP, T2 relaxometry and surgical history were found to have a moderate ability to predict response after 12 weeks of biological treatment. Validation in larger cohorts with MRI and clinical measures are needed in order to further develop the model

Quantitative Magnetic Resonance Imaging in Perianal Crohn’s Disease at 1.5 and 3.0 T: A Feasibility Study

Perianal Crohn’s Disease (pCD) is a common manifestation of Crohn’s Disease. Absence of reliable disease measures makes disease monitoring unreliable. Qualitative MRI has been increasingly used for diagnosing and monitoring pCD and has shown potential for assessing response to treatment. Quantitative MRI sequences, such as diffusion-weighted imaging (DWI), dynamic contrast enhancement (DCE) and magnetisation transfer (MT), along with T2 relaxometry, offer opportunities to improve diagnostic capability. Quantitative MRI sequences (DWI, DCE, MT and T2) were used in a cohort of 25 pCD patients before and 12 weeks after biological therapy at two different field strengths (1.5 and 3 T). Disease activity was measured with the Perianal Crohn’s Disease Activity index (PDAI) and serum C-reactive protein (CRP). Diseased tissue areas on MRI were defined by a radiologist. A baseline model to predict outcome at 12 weeks was developed. No differences were seen in the quantitative MR measured in the diseased tissue regions from baseline to 12 weeks; however, PDAI and CRP decreased. Baseline PDAI, CRP, T2 relaxometry and surgical history were found to have a moderate ability to predict response after 12 weeks of biological treatment. Validation in larger cohorts with MRI and clinical measures are needed in order to further develop the model