Registration of ‘Purple Bounty’ and ‘Purple Prosperity’ hairy vetch

The hairy vetch (Vicia villosa Roth) cultivars ‘Purple Bounty’ (Reg. no. CV-12, PI 648342) and ‘Purple Prosperity’ (Reg. no. CV-11, PI 654047) were released in 2007 and 2008, respectively, by the USDA–ARS in collaboration with the Rodale Institute and the agricultural experiment stations of Pennsylvania State University and Cornell University. Hairy vetch is a commonly used annual legume cover crop grown for its cold tolerance, fast growth, large biomass production, and ability to fix N2. However, this species has not been selected for the traits needed to optimize its use as a cover crop. Our breeding program focused on developing a cultivar that was both early flowering and had adequate winter survival and therefore adapted to mechanical termination in organic no-till production in the U.S. Northeast and Mid-Atlantic. Purple Bounty and Purple Prosperity were developed between 1998 and 2005 using recurrent selection at nurseries in Beltsville and Keedysville, MD. In 2005–2006, selections were evaluated against commercial checks for flowering time in Maryland and Pennsylvania, and in the 2006–2007 and 2007–2008 seasons they were evaluated in 10 locations (12 total site-years) across the United States for winter survival. Purple Bounty and Purple Prosperity both flowered earlier than the commercial material against which they were tested (significance depended on the date and site); Purple Bounty was the earlier flowering of the two cultivars. Purple Bounty and Purple Prosperity also had equivalent or improved winter survival compared with ‘AU Early Cover’, an early-maturing cultivar developed in the southern United States, at all test locations. Purple Prosperity is no longer commercially available, but Purple Bounty is currently licensed and distributed by Allied Seed (Nampa, ID)

Quality assessment of cellular therapies: the emerging role of molecular assays

Cellular therapies are becoming increasingly important in treating cancer, hematologic malignancies, autoimmune disorders, and damaged tissue. These therapies are becoming more effective and are being used more frequently, but they are also becoming more complex. As a result, quality testing is becoming an increasingly important part of cellular therapy. Cellular therapies should be tested at several points during their production. The starting material, intermediate products and the final product are usually analyzed. Products are evaluated at critical steps in the manufacturing process and at the end of production prior to the release of the product for clinical use. In addition, the donor of the starting biologic material is usually evaluated. The testing of cellular therapies for stability, consistency, comparability and potency is especially challenging. We and others have found that global gene and microRNA expression analysis is useful for comparability testing and will likely be useful for potency, stability and consistency testing. Several examples of the use of gene expression analysis for assessing cellular therapies are presented

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

Sensitivity of the Advanced LIGO detectors at the beginning of gravitational wave astronomy

The Laser Interferometer Gravitational Wave Observatory (LIGO) consists of two widely separated 4 km laser interferometers designed to detect gravitational waves from distant astrophysical sources in the frequency range from 10 Hz to 10 kHz. The first observation run of the Advanced LIGO detectors started in September 2015 and ended in January 2016. A strain sensitivity of better than 10−23/Hz−−−√ was achieved around 100 Hz. Understanding both the fundamental and the technical noise sources was critical for increasing the astrophysical strain sensitivity. The average distance at which coalescing binary black hole systems with individual masses of 30  M⊙ could be detected above a signal-to-noise ratio (SNR) of 8 was 1.3 Gpc, and the range for binary neutron star inspirals was about 75 Mpc. With respect to the initial detectors, the observable volume of the Universe increased by a factor 69 and 43, respectively. These improvements helped Advanced LIGO to detect the gravitational wave signal from the binary black hole coalescence, known as GW150914

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