WO 2017/180909 Al 19 October 2017 (19.10.2017) P O P C T
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Supplementary Table 3 Complete List of RNA-Sequencing Analysis of Gene Expression Changed by ≥ Tenfold Between Xenograft and Cells Cultured in 10%O2
Supplementary Table 3 Complete list of RNA-Sequencing analysis of gene expression changed by ≥ tenfold between xenograft and cells cultured in 10%O2 Expr Log2 Ratio Symbol Entrez Gene Name (culture/xenograft) -7.182 PGM5 phosphoglucomutase 5 -6.883 GPBAR1 G protein-coupled bile acid receptor 1 -6.683 CPVL carboxypeptidase, vitellogenic like -6.398 MTMR9LP myotubularin related protein 9-like, pseudogene -6.131 SCN7A sodium voltage-gated channel alpha subunit 7 -6.115 POPDC2 popeye domain containing 2 -6.014 LGI1 leucine rich glioma inactivated 1 -5.86 SCN1A sodium voltage-gated channel alpha subunit 1 -5.713 C6 complement C6 -5.365 ANGPTL1 angiopoietin like 1 -5.327 TNN tenascin N -5.228 DHRS2 dehydrogenase/reductase 2 leucine rich repeat and fibronectin type III domain -5.115 LRFN2 containing 2 -5.076 FOXO6 forkhead box O6 -5.035 ETNPPL ethanolamine-phosphate phospho-lyase -4.993 MYO15A myosin XVA -4.972 IGF1 insulin like growth factor 1 -4.956 DLG2 discs large MAGUK scaffold protein 2 -4.86 SCML4 sex comb on midleg like 4 (Drosophila) Src homology 2 domain containing transforming -4.816 SHD protein D -4.764 PLP1 proteolipid protein 1 -4.764 TSPAN32 tetraspanin 32 -4.713 N4BP3 NEDD4 binding protein 3 -4.705 MYOC myocilin -4.646 CLEC3B C-type lectin domain family 3 member B -4.646 C7 complement C7 -4.62 TGM2 transglutaminase 2 -4.562 COL9A1 collagen type IX alpha 1 chain -4.55 SOSTDC1 sclerostin domain containing 1 -4.55 OGN osteoglycin -4.505 DAPL1 death associated protein like 1 -4.491 C10orf105 chromosome 10 open reading frame 105 -4.491 -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4). -
Targeting Lysophosphatidic Acid in Cancer: the Issues in Moving from Bench to Bedside
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by IUPUIScholarWorks cancers Review Targeting Lysophosphatidic Acid in Cancer: The Issues in Moving from Bench to Bedside Yan Xu Department of Obstetrics and Gynecology, Indiana University School of Medicine, 950 W. Walnut Street R2-E380, Indianapolis, IN 46202, USA; [email protected]; Tel.: +1-317-274-3972 Received: 28 August 2019; Accepted: 8 October 2019; Published: 10 October 2019 Abstract: Since the clear demonstration of lysophosphatidic acid (LPA)’s pathological roles in cancer in the mid-1990s, more than 1000 papers relating LPA to various types of cancer were published. Through these studies, LPA was established as a target for cancer. Although LPA-related inhibitors entered clinical trials for fibrosis, the concept of targeting LPA is yet to be moved to clinical cancer treatment. The major challenges that we are facing in moving LPA application from bench to bedside include the intrinsic and complicated metabolic, functional, and signaling properties of LPA, as well as technical issues, which are discussed in this review. Potential strategies and perspectives to improve the translational progress are suggested. Despite these challenges, we are optimistic that LPA blockage, particularly in combination with other agents, is on the horizon to be incorporated into clinical applications. Keywords: Autotaxin (ATX); ovarian cancer (OC); cancer stem cell (CSC); electrospray ionization tandem mass spectrometry (ESI-MS/MS); G-protein coupled receptor (GPCR); lipid phosphate phosphatase enzymes (LPPs); lysophosphatidic acid (LPA); phospholipase A2 enzymes (PLA2s); nuclear receptor peroxisome proliferator-activated receptor (PPAR); sphingosine-1 phosphate (S1P) 1. -
Investigation of Candidate Genes and Mechanisms Underlying Obesity
Prashanth et al. BMC Endocrine Disorders (2021) 21:80 https://doi.org/10.1186/s12902-021-00718-5 RESEARCH ARTICLE Open Access Investigation of candidate genes and mechanisms underlying obesity associated type 2 diabetes mellitus using bioinformatics analysis and screening of small drug molecules G. Prashanth1 , Basavaraj Vastrad2 , Anandkumar Tengli3 , Chanabasayya Vastrad4* and Iranna Kotturshetti5 Abstract Background: Obesity associated type 2 diabetes mellitus is a metabolic disorder ; however, the etiology of obesity associated type 2 diabetes mellitus remains largely unknown. There is an urgent need to further broaden the understanding of the molecular mechanism associated in obesity associated type 2 diabetes mellitus. Methods: To screen the differentially expressed genes (DEGs) that might play essential roles in obesity associated type 2 diabetes mellitus, the publicly available expression profiling by high throughput sequencing data (GSE143319) was downloaded and screened for DEGs. Then, Gene Ontology (GO) and REACTOME pathway enrichment analysis were performed. The protein - protein interaction network, miRNA - target genes regulatory network and TF-target gene regulatory network were constructed and analyzed for identification of hub and target genes. The hub genes were validated by receiver operating characteristic (ROC) curve analysis and RT- PCR analysis. Finally, a molecular docking study was performed on over expressed proteins to predict the target small drug molecules. Results: A total of 820 DEGs were identified between -
Supplementary Material
Supplementary Material Table S1: Significant downregulated KEGGs pathways identified by DAVID following exposure to five cinnamon- based phenylpropanoids (p < 0.05). p-value Term: Genes (Benjamini) Cytokine-cytokine receptor interaction: FASLG, TNFSF14, CXCL11, IL11, FLT3LG, CCL3L1, CCL3L3, CXCR6, XCR1, 2.43 × 105 RTEL1, CSF2RA, TNFRSF17, TNFRSF14, CCNL2, VEGFB, AMH, TNFRSF10B, INHBE, IFNB1, CCR3, VEGFA, CCR2, IL12A, CCL1, CCL3, CXCL5, TNFRSF25, CCR1, CSF1, CX3CL1, CCL7, CCL24, TNFRSF1B, IL12RB1, CCL21, FIGF, EPO, IL4, IL18R1, FLT1, TGFBR1, EDA2R, HGF, TNFSF8, KDR, LEP, GH2, CCL13, EPOR, XCL1, IFNA16, XCL2 Neuroactive ligand-receptor interaction: OPRM1, THRA, GRIK1, DRD2, GRIK2, TACR2, TACR1, GABRB1, LPAR4, 9.68 × 105 GRIK5, FPR1, PRSS1, GNRHR, FPR2, EDNRA, AGTR2, LTB4R, PRSS2, CNR1, S1PR4, CALCRL, TAAR5, GABRE, PTGER1, GABRG3, C5AR1, PTGER3, PTGER4, GABRA6, GABRA5, GRM1, PLG, LEP, CRHR1, GH2, GRM3, SSTR2, Chlorogenic acid Chlorogenic CHRM3, GRIA1, MC2R, P2RX2, TBXA2R, GHSR, HTR2C, TSHR, LHB, GLP1R, OPRD1 Hematopoietic cell lineage: IL4, CR1, CD8B, CSF1, FCER2, GYPA, ITGA2, IL11, GP9, FLT3LG, CD38, CD19, DNTT, 9.29 × 104 GP1BB, CD22, EPOR, CSF2RA, CD14, THPO, EPO, HLA-DRA, ITGA2B Cytokine-cytokine receptor interaction: IL6ST, IL21R, IL19, TNFSF15, CXCR3, IL15, CXCL11, TGFB1, IL11, FLT3LG, CXCL10, CCR10, XCR1, RTEL1, CSF2RA, IL21, CCNL2, VEGFB, CCR8, AMH, TNFRSF10C, IFNB1, PDGFRA, EDA, CXCL5, TNFRSF25, CSF1, IFNW1, CNTFR, CX3CL1, CCL5, TNFRSF4, CCL4, CCL27, CCL24, CCL25, CCL23, IFNA6, IFNA5, FIGF, EPO, AMHR2, IL2RA, FLT4, TGFBR2, EDA2R, -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Identification of Potential Key Genes and Pathway Linked with Sporadic Creutzfeldt-Jakob Disease Based on Integrated Bioinformatics Analyses
medRxiv preprint doi: https://doi.org/10.1101/2020.12.21.20248688; this version posted December 24, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Identification of potential key genes and pathway linked with sporadic Creutzfeldt-Jakob disease based on integrated bioinformatics analyses Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. medRxiv preprint doi: https://doi.org/10.1101/2020.12.21.20248688; this version posted December 24, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Abstract Sporadic Creutzfeldt-Jakob disease (sCJD) is neurodegenerative disease also called prion disease linked with poor prognosis. The aim of the current study was to illuminate the underlying molecular mechanisms of sCJD. The mRNA microarray dataset GSE124571 was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened. -
Dissertation Submitted to the Combined Faculties for the Natural Sciences and for Mathematics of the Ruperto-Carola University O
Dissertation submitted to the Combined Faculties for the Natural Sciences and for Mathematics of the Ruperto-Carola University of Heidelberg, Germany for the degree of Doctor of Natural Sciences presented by Master of Information Technology Anna-Lena Kranz born in: Bielefeld Oral-examination: 28.03.2011 Analyzing combinatorial regulation of transcription in mammalian cells Referees: PD Dr. Rainer K¨onig PD Dr. Stefan Wiemann Abstract Analyzing combinatorial regulation of transcription in mammalian cells During development and differentiation of an organism, accurate gene regulation is central for cells to maintain and balance their differentiation processes. Tran- scriptional interactions between cis-acting DNA-elements such as promoters and enhancers are the basis for precise and balanced transcriptional regulation. In this thesis, proximal and distal regulatory regions upstream of all transcription start sites were considered in silico to identify regulatory modules consisting of combina- tions of transcription factors (TFs) with binding sites at promoters and enhancers. Applying these modules to a broad variety of gene expression profiles demonstrated that the identified modules regulate gene expression during mouse embryonic de- velopment and human stem cell differentiation in a tissue- and temporal-specific manner. Whereas tissue-specific regulation is mainly controlled by combinations of TFs binding at promoters, the combination of TFs binding at promoters together with TFs binding at the respective enhancers determines the regulation of tem- poral progression during development. The identified regulatory modules showed considerably good predictive power to discriminate genes being differentially reg- ulated at a specific time interval. In addition, TF binding sites are immanently different for promoter and enhancer regions. -
G Protein-Coupled Receptors
S.P.H. Alexander et al. The Concise Guide to PHARMACOLOGY 2015/16: G protein-coupled receptors. British Journal of Pharmacology (2015) 172, 5744–5869 THE CONCISE GUIDE TO PHARMACOLOGY 2015/16: G protein-coupled receptors Stephen PH Alexander1, Anthony P Davenport2, Eamonn Kelly3, Neil Marrion3, John A Peters4, Helen E Benson5, Elena Faccenda5, Adam J Pawson5, Joanna L Sharman5, Christopher Southan5, Jamie A Davies5 and CGTP Collaborators 1School of Biomedical Sciences, University of Nottingham Medical School, Nottingham, NG7 2UH, UK, 2Clinical Pharmacology Unit, University of Cambridge, Cambridge, CB2 0QQ, UK, 3School of Physiology and Pharmacology, University of Bristol, Bristol, BS8 1TD, UK, 4Neuroscience Division, Medical Education Institute, Ninewells Hospital and Medical School, University of Dundee, Dundee, DD1 9SY, UK, 5Centre for Integrative Physiology, University of Edinburgh, Edinburgh, EH8 9XD, UK Abstract The Concise Guide to PHARMACOLOGY 2015/16 provides concise overviews of the key properties of over 1750 human drug targets with their pharmacology, plus links to an open access knowledgebase of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. The full contents can be found at http://onlinelibrary.wiley.com/doi/ 10.1111/bph.13348/full. G protein-coupled receptors are one of the eight major pharmacological targets into which the Guide is divided, with the others being: ligand-gated ion channels, voltage-gated ion channels, other ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. -
G Protein‐Coupled Receptors
S.P.H. Alexander et al. The Concise Guide to PHARMACOLOGY 2019/20: G protein-coupled receptors. British Journal of Pharmacology (2019) 176, S21–S141 THE CONCISE GUIDE TO PHARMACOLOGY 2019/20: G protein-coupled receptors Stephen PH Alexander1 , Arthur Christopoulos2 , Anthony P Davenport3 , Eamonn Kelly4, Alistair Mathie5 , John A Peters6 , Emma L Veale5 ,JaneFArmstrong7 , Elena Faccenda7 ,SimonDHarding7 ,AdamJPawson7 , Joanna L Sharman7 , Christopher Southan7 , Jamie A Davies7 and CGTP Collaborators 1School of Life Sciences, University of Nottingham Medical School, Nottingham, NG7 2UH, UK 2Monash Institute of Pharmaceutical Sciences and Department of Pharmacology, Monash University, Parkville, Victoria 3052, Australia 3Clinical Pharmacology Unit, University of Cambridge, Cambridge, CB2 0QQ, UK 4School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, BS8 1TD, UK 5Medway School of Pharmacy, The Universities of Greenwich and Kent at Medway, Anson Building, Central Avenue, Chatham Maritime, Chatham, Kent, ME4 4TB, UK 6Neuroscience Division, Medical Education Institute, Ninewells Hospital and Medical School, University of Dundee, Dundee, DD1 9SY, UK 7Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, EH8 9XD, UK Abstract The Concise Guide to PHARMACOLOGY 2019/20 is the fourth in this series of biennial publications. The Concise Guide provides concise overviews of the key properties of nearly 1800 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. Although the Concise Guide represents approximately 400 pages, the material presented is substantially reduced compared to information and links presented on the website. -
Initial, Transient, and Specific Interaction Between G Protein
Sato T. et al. Medical Research Archives, vol. 6, issue 9, September 2018 Page 1 of 25 ARTICLE Initial, transient, and specific interaction between G protein-coupled receptor and target G protein in parallel signal processing: a case of olfactory discrimination of cancer-induced odors Takaaki Sato1, Mutsumi Matsukawa2, Yoichi Mizutani3, Toshio Iijima4, Hiroyoshi Matsumura5 Authors’ affiliations: 1 Biomedical Research Institute, National Institute of Advanced Industrial Science and Technology, Osaka, Japan 2 Division of Anatomical Science, Department of Functional Morphology, Nihon University School of Medicine, Tokyo, Japan 3 Department of Medical Engineering, Faculty of Health Science, Aino University, Osaka, Japan 4 Graduate School of Life Sciences, Tohoku University, Sendai, Japan 5 College of Life Sciences, Ritsumeikan University, Kusatsu, Japan * Corresponding author: Takaaki Sato, Biomedical Research Institute, National Institute of Ad- vanced Industrial Science and Technology, 1-8-31 Midorioka, Ikeda, Osaka 563-8577, Japan, E-mail: [email protected] Abstract: G protein-coupled receptors (GPCRs) detect and distinguish between various subtypes of extracellular sig- nals, such as neurotransmitters, hormones, light, and odorous chemicals. As determinants for robust and appropriate cellular responses, common and unique features of interactions between GPCRs and their target G proteins provide insights into structure-based drug design for treatment of GPCR-related diseases. Re- cently, we found that the hydrophobic core buried between GPCR helix 8 and TM1–2 is essential for acti- vation of both specific and nonspecific G proteins. Furthermore, the 2nd residue of helix 8 is responsible for initial, transient, and specific interaction with a target G protein. Analysis of human and murine olfactory receptors (ORs) and other class-A GPCRs revealed that several amino acids, such as Glu, Gln, and Asp, are conserved at this position. -
S1PR1-Mediated IFNAR1 Degradation Modulates Plasmacytoid Dendritic Cell Interferon-Α Autoamplification
S1PR1-mediated IFNAR1 degradation modulates plasmacytoid dendritic cell interferon-α autoamplification John R. Teijaroa,b,1,2, Sean Studerb,1, Nora Leafb, William B. Kiossesc, Nhan Nguyenb, Kosuke Matsukid, Hideo Negishid, Tadatsugu Taniguchid, Michael B. A. Oldstonea,2, and Hugh Rosenb,2 aDepartment of Immunology and Microbial Science, The Scripps Research Institute, La Jolla, CA 92037; bDepartment of Chemical Physiology, The Scripps Research Institute, La Jolla, CA 92037; cCore Microscopy Facility, The Scripps Research Institute, La Jolla, CA 92037; and dDepartment of Molecular Immunology, Institute of Industrial Science, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan Contributed by Michael B. A. Oldstone, December 23, 2015 (sent for review November 16, 2015; reviewed by Arturo Casadevall and Herbert W. Virgin) Blunting immunopathology without abolishing host defense is the curb resulting immune pathology during both infectious and foundation for safe and effective modulation of infectious and autoimmune disease states. autoimmune diseases. Sphingosine 1-phosphate receptor 1 (S1PR1) The goal of the current study was to generate a detailed mech- agonists are effective in treating infectious and multiple autoimmune anistic understanding of how S1PR1 selectively suppresses type I pathologies; however, mechanisms underlying their clinical efficacy IFN and cytokine amplification. Within this study, we demonstrate are yet to be fully elucidated. Here, we uncover an unexpected that S1PR1 signaling limits the IFN-α autoamplification loop in mechanism of convergence between S1PR1 and interferon alpha pDCs. S1PR1 agonist suppression is pertussis toxin (PT)-resistant, receptor 1 (IFNAR1) signaling pathways. Activation of S1PR1 signaling but it is inhibited by an S1PR1 C-terminal–derived transactivating by pharmacological tools or endogenous ligand sphingosine-1 phos- transcriptional activator (Tat)-fusion peptide that blocks receptor phate (S1P) inhibits type 1 IFN responses that exacerbate numerous internalization.