TREM-2 (triggering receptor expressed on myeloid cells 2) is a phagocytic receptor for bacteria

Phagocytosis, which is essential for the immune response to pathogens, is initiated by specific interactions between pathogens and cell surface receptors expressed by phagocytes. This study identifies triggering receptor expressed on myeloid cells 2 (TREM-2) and its signaling counterpart DAP12 as a molecular complex that promotes phagocytosis of bacteria. Expression of TREM-2–DAP12 enables nonphagocytic Chinese hamster ovary cells to internalize bacteria. This function depends on actin cytoskeleton dynamics and the activity of the small guanosine triphosphatases Rac and Cdc42. Internalization also requires src kinase activity and tyrosine phosphorylation. In bone marrow–derived macrophages, phagocytosis is decreased in the absence of DAP12 and can be restored by expression of TREM-2–DAP12. Depletion of TREM-2 inhibits both binding and uptake of bacteria. Finally, TREM-2–dependent phagocytosis is impaired in Syk-deficient macrophages. This study highlights a novel role for TREM-2–DAP12 in the immune response to bacterial pathogens

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

Analysis of NAMCS data for multiple sclerosis, 1998–2004

BACKGROUND: To our knowledge, no study to date has investigated the prescribing patterns of immunomodulatory agents (IMAs) in an outpatient setting in the United States. To address this issue, we performed retrospective data analyses on National Ambulatory Medical Care Survey (NAMCS) data for MS patient visits between 1998 and 2004. METHODS: NAMCS data are a weighted estimate of the nationwide frequency of patients' outpatient clinic visits. We analyzed NAMCS data in the following categories: (1) the proportion of MS patient visits to neurologists, family practitioners or internists, (2) age/gender/race/geographical distribution patterns in patient visits, and (3) the proportion of patients on IMA treatment among established MS patients. RESULTS: There were an estimated 6.7 million multiple sclerosis (MS) patient visits to the clinics between 1998–2004. Neurologists recorded the most patient visits, 50.7%. Patient visits were mostly in the fourth and fifth decade age group (57.9%). The male to female ratio was 1:4. No statistical evidence was observed for a decline or increase in IMA usage. About 62% patients visiting neurologists and 92% seen by family practitioners/internists were not using IMAs. Our results suggest that between the years 1998–2003, the use of interferon-1a tended to decline while the use of interferon-1b and glatiramer acetate, increased. CONCLUSION: Strategies that lead to improved use of IMAs in the management of MS in the outpatient setting are needed

Identification and Characterization of a Leucine-Rich Repeat Kinase 2 (LRRK2) Consensus Phosphorylation Motif

Mutations in LRRK2 (leucine-rich repeat kinase 2) have been identified as major genetic determinants of Parkinson's disease (PD). The most prevalent mutation, G2019S, increases LRRK2's kinase activity, therefore understanding the sites and substrates that LRRK2 phosphorylates is critical to understanding its role in disease aetiology. Since the physiological substrates of this kinase are unknown, we set out to reveal potential targets of LRRK2 G2019S by identifying its favored phosphorylation motif. A non-biased screen of an oriented peptide library elucidated F/Y-x-T-x-R/K as the core dependent substrate sequence. Bioinformatic analysis of the consensus phosphorylation motif identified several novel candidate substrates that potentially function in neuronal pathophysiology. Peptides corresponding to the most PD relevant proteins were efficiently phosphorylated by LRRK2 in vitro. Interestingly, the phosphomotif was also identified within LRRK2 itself. Autophosphorylation was detected by mass spectrometry and biochemical means at the only F-x-T-x-R site (Thr 1410) within LRRK2. The relevance of this site was assessed by measuring effects of mutations on autophosphorylation, kinase activity, GTP binding, GTP hydrolysis, and LRRK2 multimerization. These studies indicate that modification of Thr1410 subtly regulates GTP hydrolysis by LRRK2, but with minimal effects on other parameters measured. Together the identification of LRRK2's phosphorylation consensus motif, and the functional consequences of its phosphorylation, provide insights into downstream LRRK2-signaling pathways

Multi-Platform Next-Generation Sequencing of the Domestic Turkey (Meleagris gallopavo): Genome Assembly and Analysis

The combined application of next-generation sequencing platforms has provided an economical approach to unlocking the potential of the turkey genome

Integrated Molecular Characterization of Uterine Carcinosarcoma

SummaryWe performed genomic, epigenomic, transcriptomic, and proteomic characterizations of uterine carcinosarcomas (UCSs). Cohort samples had extensive copy-number alterations and highly recurrent somatic mutations. Frequent mutations were found in TP53, PTEN, PIK3CA, PPP2R1A, FBXW7, and KRAS, similar to endometrioid and serous uterine carcinomas. Transcriptome sequencing identified a strong epithelial-to-mesenchymal transition (EMT) gene signature in a subset of cases that was attributable to epigenetic alterations at microRNA promoters. The range of EMT scores in UCS was the largest among all tumor types studied via The Cancer Genome Atlas. UCSs shared proteomic features with gynecologic carcinomas and sarcomas with intermediate EMT features. Multiple somatic mutations and copy-number alterations in genes that are therapeutic targets were identified

Computational Identification of Transcriptional Regulators in Human Endotoxemia

One of the great challenges in the post-genomic era is to decipher the underlying principles governing the dynamics of biological responses. As modulating gene expression levels is among the key regulatory responses of an organism to changes in its environment, identifying biologically relevant transcriptional regulators and their putative regulatory interactions with target genes is an essential step towards studying the complex dynamics of transcriptional regulation. We present an analysis that integrates various computational and biological aspects to explore the transcriptional regulation of systemic inflammatory responses through a human endotoxemia model. Given a high-dimensional transcriptional profiling dataset from human blood leukocytes, an elementary set of temporal dynamic responses which capture the essence of a pro-inflammatory phase, a counter-regulatory response and a dysregulation in leukocyte bioenergetics has been extracted. Upon identification of these expression patterns, fourteen inflammation-specific gene batteries that represent groups of hypothetically ‘coregulated’ genes are proposed. Subsequently, statistically significant cis-regulatory modules (CRMs) are identified and decomposed into a list of critical transcription factors (34) that are validated largely on primary literature. Finally, our analysis further allows for the construction of a dynamic representation of the temporal transcriptional regulatory program across the host, deciphering possible combinatorial interactions among factors under which they might be active. Although much remains to be explored, this study has computationally identified key transcription factors and proposed a putative time-dependent transcriptional regulatory program associated with critical transcriptional inflammatory responses. These results provide a solid foundation for future investigations to elucidate the underlying transcriptional regulatory mechanisms under the host inflammatory response. Also, the assumption that coexpressed genes that are functionally relevant are more likely to share some common transcriptional regulatory mechanism seems to be promising, making the proposed framework become essential in unravelling context-specific transcriptional regulatory interactions underlying diverse mammalian biological processes