Direct Visualization of Camp Signaling in Primary Cilia Reveals Up-Regulation of Ciliary GPCR Activity Following Hedgehog Activation
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Mir-338-3P Is Regulated by Estrogens Through GPER in Breast Cancer Cells and Cancer-Associated Fibroblasts (Cafs)
cells Article miR-338-3p Is Regulated by Estrogens through GPER in Breast Cancer Cells and Cancer-Associated Fibroblasts (CAFs) Adele Vivacqua 1,*, Anna Sebastiani 1, Anna Maria Miglietta 2, Damiano Cosimo Rigiracciolo 1, Francesca Cirillo 1, Giulia Raffaella Galli 1, Marianna Talia 1, Maria Francesca Santolla 1, Rosamaria Lappano 1, Francesca Giordano 1, Maria Luisa Panno 1 and Marcello Maggiolini 1,* 1 Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, 87036 Rende, Italy; [email protected] (A.S.); [email protected] (D.C.R.); [email protected] (F.C.); [email protected] (G.R.G.); [email protected] (M.T.); [email protected] (M.F.S.); [email protected] (R.L.); [email protected] (F.G.); [email protected] (M.L.P.) 2 Regional HospitalCosenza, 87100 Cosenza, Italy; [email protected] * Correspondence: [email protected] (A.V.); [email protected] (M.M.); Tel.: +39-0984-493-048 (A.V.); +39-0984-493-076 (M.M.) Received: 12 October 2018; Accepted: 7 November 2018; Published: 9 November 2018 Abstract: Estrogens acting through the classic estrogen receptors (ERs) and the G protein estrogen receptor (GPER) regulate the expression of diverse miRNAs, small sequences of non-coding RNA involved in several pathophysiological conditions, including breast cancer. In order to provide novel insights on miRNAs regulation by estrogens in breast tumor, we evaluated the expression of 754 miRNAs by TaqMan Array in ER-negative and GPER-positive SkBr3 breast cancer cells and cancer-associated fibroblasts (CAFs) upon 17β-estradiol (E2) treatment. Various miRNAs were regulated by E2 in a peculiar manner in SkBr3 cancer cells and CAFs, while miR-338-3p displayed a similar regulation in both cell types. -
Genome-Wide Prediction of Small Molecule Binding to Remote
bioRxiv preprint doi: https://doi.org/10.1101/2020.08.04.236729; this version posted August 5, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 Genome-wide Prediction of Small Molecule Binding 2 to Remote Orphan Proteins Using Distilled Sequence 3 Alignment Embedding 1 2 3 4 4 Tian Cai , Hansaim Lim , Kyra Alyssa Abbu , Yue Qiu , 5,6 1,2,3,4,7,* 5 Ruth Nussinov , and Lei Xie 1 6 Ph.D. Program in Computer Science, The Graduate Center, The City University of New York, New York, 10016, USA 2 7 Ph.D. Program in Biochemistry, The Graduate Center, The City University of New York, New York, 10016, USA 3 8 Department of Computer Science, Hunter College, The City University of New York, New York, 10065, USA 4 9 Ph.D. Program in Biology, The Graduate Center, The City University of New York, New York, 10016, USA 5 10 Computational Structural Biology Section, Basic Science Program, Frederick National Laboratory for Cancer Research, 11 Frederick, MD 21702, USA 6 12 Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel 13 Aviv, Israel 7 14 Helen and Robert Appel Alzheimer’s Disease Research Institute, Feil Family Brain & Mind Research Institute, Weill 15 Cornell Medicine, Cornell University, New York, 10021, USA * 16 [email protected] 17 July 27, 2020 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.08.04.236729; this version posted August 5, 2020. -
Edinburgh Research Explorer
Edinburgh Research Explorer International Union of Basic and Clinical Pharmacology. LXXXVIII. G protein-coupled receptor list Citation for published version: Davenport, AP, Alexander, SPH, Sharman, JL, Pawson, AJ, Benson, HE, Monaghan, AE, Liew, WC, Mpamhanga, CP, Bonner, TI, Neubig, RR, Pin, JP, Spedding, M & Harmar, AJ 2013, 'International Union of Basic and Clinical Pharmacology. LXXXVIII. G protein-coupled receptor list: recommendations for new pairings with cognate ligands', Pharmacological reviews, vol. 65, no. 3, pp. 967-86. https://doi.org/10.1124/pr.112.007179 Digital Object Identifier (DOI): 10.1124/pr.112.007179 Link: Link to publication record in Edinburgh Research Explorer Document Version: Publisher's PDF, also known as Version of record Published In: Pharmacological reviews Publisher Rights Statement: U.S. Government work not protected by U.S. copyright General rights Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer content complies with UK legislation. If you believe that the public display of this file breaches copyright please contact [email protected] providing details, and we will remove access to the work immediately and investigate your claim. Download date: 02. Oct. 2021 1521-0081/65/3/967–986$25.00 http://dx.doi.org/10.1124/pr.112.007179 PHARMACOLOGICAL REVIEWS Pharmacol Rev 65:967–986, July 2013 U.S. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
Profiling G Protein-Coupled Receptors of Fasciola Hepatica Identifies Orphan Rhodopsins Unique to Phylum Platyhelminthes
bioRxiv preprint doi: https://doi.org/10.1101/207316; this version posted October 23, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 1 Profiling G protein-coupled receptors of Fasciola hepatica 2 identifies orphan rhodopsins unique to phylum 3 Platyhelminthes 4 5 Short title: Profiling G protein-coupled receptors (GPCRs) in Fasciola hepatica 6 7 Paul McVeigh1*, Erin McCammick1, Paul McCusker1, Duncan Wells1, Jane 8 Hodgkinson2, Steve Paterson3, Angela Mousley1, Nikki J. Marks1, Aaron G. Maule1 9 10 11 1Parasitology & Pathogen Biology, The Institute for Global Food Security, School of 12 Biological Sciences, Queen’s University Belfast, Medical Biology Centre, 97 Lisburn 13 Road, Belfast, BT9 7BL, UK 14 15 2 Institute of Infection and Global Health, University of Liverpool, Liverpool, UK 16 17 3 Institute of Integrative Biology, University of Liverpool, Liverpool, UK 18 19 * Corresponding author 20 Email: [email protected] 21 1 bioRxiv preprint doi: https://doi.org/10.1101/207316; this version posted October 23, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. 22 Abstract 23 G protein-coupled receptors (GPCRs) are established drug targets. Despite their 24 considerable appeal as targets for next-generation anthelmintics, poor understanding 25 of their diversity and function in parasitic helminths has thwarted progress towards 26 GPCR-targeted anti-parasite drugs. -
Smoothened Variants Explain the Majority of Drug Resistance in Basal Cell Carcinoma
Article Smoothened Variants Explain the Majority of Drug Resistance in Basal Cell Carcinoma Graphical Abstract Authors Scott X. Atwood, Kavita Y. Sarin, ..., Anthony E. Oro, Jean Y. Tang Correspondence [email protected] (A.E.O.), [email protected] (J.Y.T.) In Brief Atwood et al. identify key SMO mutations that confer resistance to SMO inhibitors in basal cell carcinomas (BCC) and show that these mutants respond to aPKC-i/l or GLI2 inhibitors, providing potential approaches for treating BCCs resistant to SMO inhibitors. Highlights Accession Numbers d Functional SMO mutations are detected in the majority of GSE58377 SMO inhibitor-resistant BCCs d Resistance occurs by suppressing drug responsiveness and SMO autoinhibition d SMO mutants explain both intrinsic and acquired tumor resistance d Inhibition of aPKC-i/l or GLI2 bypasses SMO variants to suppress Hedgehog signaling Atwood et al., 2015, Cancer Cell 27, 342–353 March 9, 2015 ª2015 Elsevier Inc. http://dx.doi.org/10.1016/j.ccell.2015.02.002 Cancer Cell Article Smoothened Variants Explain the Majority of Drug Resistance in Basal Cell Carcinoma Scott X. Atwood,1,2 Kavita Y. Sarin,1,2 Ramon J. Whitson,1 Jiang R. Li,1 Geurim Kim,1 Melika Rezaee,1 Mina S. Ally,1 Jinah Kim,1 Catherine Yao,1 Anne Lynn S. Chang,1,3 Anthony E. Oro,1,3,* and Jean Y. Tang1,3,* 1Program in Epithelial Biology and Department of Dermatology, Stanford University School of Medicine, Stanford, CA 94305, USA 2Co-first author 3Co-senior author *Correspondence: [email protected] (A.E.O.), [email protected] (J.Y.T.) http://dx.doi.org/10.1016/j.ccell.2015.02.002 SUMMARY Advanced basal cell carcinomas (BCCs) frequently acquire resistance to Smoothened (SMO) inhibitors through unknown mechanisms. -
System, Method and Software for Calculation of a Cannabis Drug Efficiency Index for the Reduction of Inflammation
International Journal of Molecular Sciences Article System, Method and Software for Calculation of a Cannabis Drug Efficiency Index for the Reduction of Inflammation Nicolas Borisov 1,† , Yaroslav Ilnytskyy 2,3,†, Boseon Byeon 2,3,4,†, Olga Kovalchuk 2,3 and Igor Kovalchuk 2,3,* 1 Moscow Institute of Physics and Technology, 9 Institutsky lane, Dolgoprudny, Moscow Region 141701, Russia; [email protected] 2 Department of Biological Sciences, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada; [email protected] (Y.I.); [email protected] (B.B.); [email protected] (O.K.) 3 Pathway Rx., 16 Sandstone Rd. S., Lethbridge, AB T1K 7X8, Canada 4 Biomedical and Health Informatics, Computer Science Department, State University of New York, 2 S Clinton St, Syracuse, NY 13202, USA * Correspondence: [email protected] † First three authors contributed equally to this research. Abstract: There are many varieties of Cannabis sativa that differ from each other by composition of cannabinoids, terpenes and other molecules. The medicinal properties of these cultivars are often very different, with some being more efficient than others. This report describes the development of a method and software for the analysis of the efficiency of various cannabis extracts to detect the anti-inflammatory properties of the various cannabis extracts. The method uses high-throughput gene expression profiling data but can potentially use other omics data as well. According to the signaling pathway topology, the gene expression profiles are convoluted into the signaling pathway activities using a signaling pathway impact analysis (SPIA) method. The method was tested by inducing inflammation in human 3D epithelial tissues, including intestine, oral and skin, and then exposing these tissues to various extracts and then performing transcriptome analysis. -
Tamoxifen Resistance: Emerging Molecular Targets
International Journal of Molecular Sciences Review Tamoxifen Resistance: Emerging Molecular Targets Milena Rondón-Lagos 1,*,†, Victoria E. Villegas 2,3,*,†, Nelson Rangel 1,2,3, Magda Carolina Sánchez 2 and Peter G. Zaphiropoulos 4 1 Department of Medical Sciences, University of Turin, Turin 10126, Italy; [email protected] 2 Faculty of Natural Sciences and Mathematics, Universidad del Rosario, Bogotá 11001000, Colombia; [email protected] 3 Doctoral Program in Biomedical Sciences, Universidad del Rosario, Bogotá 11001000, Colombia 4 Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge 14183, Sweden; [email protected] * Correspondence: [email protected] (M.R.-L.); [email protected] (V.E.V.); Tel.: +39-01-1633-4127 (ext. 4388) (M.R.-L.); +57-1-297-0200 (ext. 4029) (V.E.V.); Fax: +39-01-1663-5267 (M.R.-L.); +57-1-297-0200 (V.E.V.) † These authors contributed equally to this work. Academic Editor: William Chi-shing Cho Received: 5 July 2016; Accepted: 16 August 2016; Published: 19 August 2016 Abstract: 17β-Estradiol (E2) plays a pivotal role in the development and progression of breast cancer. As a result, blockade of the E2 signal through either tamoxifen (TAM) or aromatase inhibitors is an important therapeutic strategy to treat or prevent estrogen receptor (ER) positive breast cancer. However, resistance to TAM is the major obstacle in endocrine therapy. This resistance occurs either de novo or is acquired after an initial beneficial response. The underlying mechanisms for TAM resistance are probably multifactorial and remain largely unknown. Considering that breast cancer is a very heterogeneous disease and patients respond differently to treatment, the molecular analysis of TAM’s biological activity could provide the necessary framework to understand the complex effects of this drug in target cells. -
Saikat Mukhopadhyay
Updated June 2021 SAIKAT MUKHOPADHYAY Assistant Professor, Cell Biology, UT Southwestern Medical Center, Dallas. W.W. Caruth, Jr. Scholar in Biomedical Research, CPRIT Scholar in Cancer Research. UT Southwestern Medical Center, Email: [email protected] 5323 Harry Hines Boulevard Ph: 214-648-3853 Dallas, Texas, 75390. Lab url: http://www.utsouthwestern.edu/labs/mukhopadhyay/ Google Scholar url: http://scholar.google.com/citations?hl=en&user=PUKbgQ0AAAAJ EDUCATION 2008-2012 Postdoctoral Fellow, Genentech, South San Francisco, CA. 2002-2008 PhD, Biology, Brandeis University, Waltham, MA. 1999-2002 MD, Biochemistry, Banaras Hindu University, Varanasi, India. 1992-1998 MBBS, Medical College, Calcutta, India. POSITIONS AND EMPLOYMENT 2013- Assistant Professor, Department of Cell Biology, UT Southwestern Medical Center, Dallas. 2013- Member, Harold C. Simmons Comprehensive Cancer Center, UT Southwestern 2013- Member, Development track, Kidney cancer program, UT Southwestern PUBLICATIONS (#corresponding or ##co-corresponding author) 1. Palicharla, V., Hwang, S., Somatilaka, B., Badgandi, H. B., Legue, E, Shimada, I, Tran, V., Woodruff, J., Liem, K, and Mukhopadhyay, S#. (2021). Interactions between TULP3 tubby domain cargo site and ARL13B amphipathic helix promote lipidated protein transport to cilia. bioRxiv. doi: https://doi.org/10.1101/2021.05.25.445488 2. Hwang, S., Somatilaka, B., White, K., and Mukhopadhyay, S#. (2021). Gpr161 ciliary pools prevent hedgehog pathway hyperactivation phenotypes specifically from lack of Gli transcriptional repression. bioRxiv (in revison, eLife). doi: https://doi.org/10.1101/2021.01.07.425654. 1 Updated June 2021 3. Constable, S and Mukhopadhyay, S## (2020). Ubiquitin tunes hedgehog in matters of the heart. Developmental Cell, 55, 385-386. PMID. 33232673. 4. -
Coexpression of Human Somatostatin Receptor-2 (SSTR2) and SSTR3 Modulates Antiproliferative Signaling and Apoptosis Sajad a War and Ujendra Kumar*
War and Kumar Journal of Molecular Signaling 2012, 7:5 http://www.thrombosisjournal.com/7/1/5 RESEARCH ARTICLE Open Access Coexpression of human somatostatin receptor-2 (SSTR2) and SSTR3 modulates antiproliferative signaling and apoptosis Sajad A War and Ujendra Kumar* Abstract Background: Somatostatin (SST) via five Gi coupled receptors namely SSTR1-5 is known to inhibit cell proliferation by cytostatic and cytotoxic mechanisms. Heterodimerization plays a crucial role in modulating the signal transduction pathways of SSTR subtypes. In the present study, we investigated human SSTR2/SSTR3 heterodimerization, internalization, MAPK signaling, cell proliferation and apoptosis in HEK-293 cells in response to SST and specific agonists for SSTR2 and SSTR3. Results: Although in basal conditions, SSTR2 and SSTR3 colocalize at the plasma membrane and exhibit heterodimerization, the cell surface distribution of both receptors decreased upon agonist activation and was accompanied by a parallel increase in intracellular colocalization. Receptors activation by SST and specific agonists significantly decreased cAMP levels in cotransfected cells in comparison to control. Agonist-mediated modulation of pERK1/2 was time and concentration-dependent, and pronounced in serum-deprived conditions. pERK1/2 was inhibited in response to SST; conversely receptor-specific agonist treatment caused inhibition at lower concentration and activation at higher concentration. Strikingly, ERK1/2 phosphorylation was sustained upon prolonged treatment with SST but not with receptor-specific agonists. On the other hand, SST and receptor-specific agonists modulated p38 phosphorylation time-dependently. The receptor activation in cotransfected cells exhibits Gi-dependent inhibition of cell proliferation attributed to increased PARP-1 expression and TUNEL staining, whereas induction of p21 and p27Kip1 suggests a cytostatic effect. -
1 Supplemental Material Maresin 1 Activates LGR6 Receptor
Supplemental Material Maresin 1 Activates LGR6 Receptor Promoting Phagocyte Immunoresolvent Functions Nan Chiang, Stephania Libreros, Paul C. Norris, Xavier de la Rosa, Charles N. Serhan Center for Experimental Therapeutics and Reperfusion Injury, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA. 1 Supplemental Table 1. Screening of orphan GPCRs with MaR1 Vehicle Vehicle MaR1 MaR1 mean RLU > GPCR ID SD % Activity Mean RLU Mean RLU + 2 SD Mean RLU Vehicle mean RLU+2 SD? ADMR 930920 33283 997486.5381 863760 -7% BAI1 172580 18362 209304.1828 176160 2% BAI2 26390 1354 29097.71737 26240 -1% BAI3 18040 758 19555.07976 18460 2% CCRL2 15090 402 15893.6583 13840 -8% CMKLR2 30080 1744 33568.954 28240 -6% DARC 119110 4817 128743.8016 126260 6% EBI2 101200 6004 113207.8197 105640 4% GHSR1B 3940 203 4345.298244 3700 -6% GPR101 41740 1593 44926.97349 41580 0% GPR103 21413 1484 24381.25067 23920 12% NO GPR107 366800 11007 388814.4922 360020 -2% GPR12 77980 1563 81105.4653 76260 -2% GPR123 1485190 46446 1578081.986 1342640 -10% GPR132 860940 17473 895885.901 826560 -4% GPR135 18720 1656 22032.6827 17540 -6% GPR137 40973 2285 45544.0809 39140 -4% GPR139 438280 16736 471751.0542 413120 -6% GPR141 30180 2080 34339.2307 29020 -4% GPR142 105250 12089 129427.069 101020 -4% GPR143 89390 5260 99910.40557 89380 0% GPR146 16860 551 17961.75617 16240 -4% GPR148 6160 484 7128.848113 7520 22% YES GPR149 50140 934 52008.76073 49720 -1% GPR15 10110 1086 12282.67884 -
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.