Growth of [lambda] variants with added or altered promoters in N-limiting bacterial mutants: Evidence that an N recognition site lies in the PR promoter

Transcription of the [lambda] genome, initiating at the early rightward promoter (PR), traverses the cII-O-P operon and extends through the Q gene. In the absence of the [lambda] N function, this transcription is prematurely terminated at either of two termination sites, tR1 and tR2. The cII-O-P operon lies distal to tR1, but proximal to tR2. A number of mutations resulting in new promoter activities (e.g., c17 and ric5b) mapping distal to tR1, but proximal to tR2, have been isolated.Although phages carrying the c17 mutation grow in a normal Escherichia coli host, we find that [lambda] derivatives carrying this mutation will not grow in mutant E. coli K12 hosts, Nus-, which limit [lambda] growth by inhibiting the expression of N function. However, under the same conditions, a [lambda] phage containing only the normal [lambda] promoters grows significantly better in the Nus- hosts. Our studies demonstrate that under conditions of limited N expression, phage carrying the c17 mutation can express functions coded for by genes in the cII-O-P operon, but not endolysin, a function coded for by a gene distal to tR2. Thus, under conditions of low N activity, functions whose genes lie downstream from the c17 promoter without any intervening termination signals are expressed. On the other hand, functions whose genes lie downstream from this promoter with an intervening termination signal are not expressed.These results are consistent with a model of N action, which has N acting only with transcription initiating at a specific class of promoters (e.g., PR), c17 not being a member of this class. Although previous studies (Friedman and Ponce-Campos, 1975) have shown that the ric5b promoter is also not a member of the N-utilizing class of promoters, we find that [lambda]ric5b grows on Nus- hosts. This suggests that whereas c17 interferes with transcription from PR, ric5b does not show such an interference.We also find that [lambda] variants carrying two mutations v3 and vs326, which map in the OR - PR region, exhibit the same growth characteristics in Nus- hosts as phages carrying the c17 mutation. These observations imply that the combination of v3 and vs326 interfere with N-modification of transcription initiating at PR, and lead us to conclude that one site for N recognition is located within the PR promoter.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/21867/1/0000271.pd

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

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

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

DW4TR: A Data Warehouse for Translational Research

AbstractThe linkage between the clinical and laboratory research domains is a key issue in translational research. Integration of clinicopathologic data alone is a major task given the number of data elements involved. For a translational research environment, it is critical to make these data usable at the point-of-need. Individual systems have been developed to meet the needs of particular projects though the need for a generalizable system has been recognized. Increased use of Electronic Medical Record data in translational research will demand generalizing the system for integrating clinical data to support the study of a broad range of human diseases. To ultimately satisfy these needs, we have developed a system to support multiple translational research projects. This system, the Data Warehouse for Translational Research (DW4TR), is based on a light-weight, patient-centric modularly-structured clinical data model and a specimen-centric molecular data model. The temporal relationships of the data are also part of the model. The data are accessed through an interface composed of an Aggregated Biomedical-Information Browser (ABB) and an Individual Subject Information Viewer (ISIV) which target general users. The system was developed to support a breast cancer translational research program and has been extended to support a gynecological disease program. Further extensions of the DW4TR are underway. We believe that the DW4TR will play an important role in translational research across multiple disease types

Tandemly repeated DNA families in the mouse genome

<p>Abstract</p> <p>Background</p> <p>Functional and morphological studies of tandem DNA repeats, that combine high portion of most genomes, are mostly limited due to the incomplete characterization of these genome elements. We report here a genome wide analysis of the large tandem repeats (TR) found in the mouse genome assemblies.</p> <p>Results</p> <p>Using a bioinformatics approach, we identified large TR with array size more than 3 kb in two mouse whole genome shotgun (WGS) assemblies. Large TR were classified based on sequence similarity, chromosome position, monomer length, array variability, and GC content; we identified four superfamilies, eight families, and 62 subfamilies - including 60 not previously described. 1) The superfamily of centromeric minor satellite is only found in the unassembled part of the reference genome. 2) The pericentromeric major satellite is the most abundant superfamily and reveals high order repeat structure. 3) Transposable elements related superfamily contains two families. 4) The superfamily of heterogeneous tandem repeats includes four families. One family is found only in the WGS, while two families represent tandem repeats with either single or multi locus location. Despite multi locus location, TRPC-21A-MM is placed into a separated family due to its abundance, strictly pericentromeric location, and resemblance to big human satellites.</p> <p>To confirm our data, we next performed <it>in situ </it>hybridization with three repeats from distinct families. TRPC-21A-MM probe hybridized to chromosomes 3 and 17, multi locus TR-22A-MM probe hybridized to ten chromosomes, and single locus TR-54B-MM probe hybridized with the long loops that emerge from chromosome ends. In addition to <it>in silico </it>predicted several extra-chromosomes were positive for TR by <it>in situ </it>analysis, potentially indicating inaccurate genome assembly of the heterochromatic genome regions.</p> <p>Conclusions</p> <p>Chromosome-specific TR had been predicted for mouse but no reliable cytogenetic probes were available before. We report new analysis that identified <it>in silico </it>and confirmed <it>in situ </it>3/17 chromosome-specific probe TRPC-21-MM. Thus, the new classification had proven to be useful tool for continuation of genome study, while annotated TR can be the valuable source of cytogenetic probes for chromosome recognition.</p

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

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation

The Immune Landscape of Cancer

We performed an extensive immunogenomic anal-ysis of more than 10,000 tumors comprising 33diverse cancer types by utilizing data compiled byTCGA. Across cancer types, we identified six im-mune subtypes\u2014wound healing, IFN-gdominant,inflammatory, lymphocyte depleted, immunologi-cally quiet, and TGF-bdominant\u2014characterized bydifferences in macrophage or lymphocyte signa-tures, Th1:Th2 cell ratio, extent of intratumoral het-erogeneity, aneuploidy, extent of neoantigen load,overall cell proliferation, expression of immunomod-ulatory genes, and prognosis. Specific drivermutations correlated with lower (CTNNB1,NRAS,orIDH1) or higher (BRAF,TP53,orCASP8) leukocytelevels across all cancers. Multiple control modalitiesof the intracellular and extracellular networks (tran-scription, microRNAs, copy number, and epigeneticprocesses) were involved in tumor-immune cell inter-actions, both across and within immune subtypes.Our immunogenomics pipeline to characterize theseheterogeneous tumors and the resulting data areintended to serve as a resource for future targetedstudies to further advance the field