Infant High-Grade Gliomas Comprise Multiple Subgroups Characterized by Novel Targetable Gene Fusions and Favorable Outcomes
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Gpr161 Anchoring of PKA Consolidates GPCR and Camp Signaling
Gpr161 anchoring of PKA consolidates GPCR and cAMP signaling Verena A. Bachmanna,1, Johanna E. Mayrhofera,1, Ronit Ilouzb, Philipp Tschaiknerc, Philipp Raffeinera, Ruth Röcka, Mathieu Courcellesd,e, Federico Apeltf, Tsan-Wen Lub,g, George S. Baillieh, Pierre Thibaultd,i, Pia Aanstadc, Ulrich Stelzlf,j, Susan S. Taylorb,g,2, and Eduard Stefana,2 aInstitute of Biochemistry and Center for Molecular Biosciences, University of Innsbruck, 6020 Innsbruck, Austria; bDepartment of Chemistry and Biochemistry, University of California, San Diego, CA 92093; cInstitute of Molecular Biology, University of Innsbruck, 6020 Innsbruck, Austria; dInstitute for Research in Immunology and Cancer, Université de Montréal, Montreal, QC, Canada H3C 3J7; eDépartement de Biochimie, Université de Montréal, Montreal, QC, Canada H3C 3J7; fOtto-Warburg Laboratory, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany; gDepartment of Pharmacology, University of California, San Diego, CA 92093; hInstitute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, G12 8QQ, United Kingdom; iDepartment of Chemistry, Université de Montréal, Montreal, QC, Canada H3C 3J7; and jInstitute of Pharmaceutical Sciences, Pharmaceutical Chemistry, University of Graz, 8010 Graz, Austria Contributed by Susan S. Taylor, May 24, 2016 (sent for review February 18, 2016; reviewed by John J. G. Tesmer and Mark von Zastrow) Scaffolding proteins organize the information flow from activated G accounts for nanomolar binding affinities to PKA R subunit dimers protein-coupled receptors (GPCRs) to intracellular effector cascades (12, 13). Moreover, additional components of the cAMP signaling both spatially and temporally. By this means, signaling scaffolds, such machinery, such as GPCRs, adenylyl cyclases, and phosphodiester- as A-kinase anchoring proteins (AKAPs), compartmentalize kinase ases, physically interact with AKAPs (1, 5, 11, 14). -
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. -
Identification and Characterization of RHOA-Interacting Proteins in Bovine Spermatozoa1
BIOLOGY OF REPRODUCTION 78, 184–192 (2008) Published online before print 10 October 2007. DOI 10.1095/biolreprod.107.062943 Identification and Characterization of RHOA-Interacting Proteins in Bovine Spermatozoa1 Sarah E. Fiedler, Malini Bajpai, and Daniel W. Carr2 Department of Medicine, Oregon Health & Sciences University and Veterans Affairs Medical Center, Portland, Oregon 97239 ABSTRACT Guanine nucleotide exchange factors (GEFs) catalyze the GDP for GTP exchange [2]. Activation is negatively regulated by In somatic cells, RHOA mediates actin dynamics through a both guanine nucleotide dissociation inhibitors (RHO GDIs) GNA13-mediated signaling cascade involving RHO kinase and GTPase-activating proteins (GAPs) [1, 2]. Endogenous (ROCK), LIM kinase (LIMK), and cofilin. RHOA can be RHO can be inactivated via C3 exoenzyme ADP-ribosylation, negatively regulated by protein kinase A (PRKA), and it and studies have demonstrated RHO involvement in actin-based interacts with members of the A-kinase anchoring (AKAP) cytoskeletal response to extracellular signals, including lyso- family via intermediary proteins. In spermatozoa, actin poly- merization precedes the acrosome reaction, which is necessary phosphatidic acid (LPA) [2–4]. LPA is known to signal through for normal fertility. The present study was undertaken to G-protein-coupled receptors (GPCRs) [4, 5]; specifically, LPA- determine whether the GNA13-mediated RHOA signaling activated GNA13 (formerly Ga13) promotes RHO activation pathway may be involved in acrosome reaction in bovine through GEFs [4, 6]. Activated RHO-GTP then signals RHO caudal sperm, and whether AKAPs may be involved in its kinase (ROCK), resulting in the phosphorylation and activation targeting and regulation. GNA13, RHOA, ROCK2, LIMK2, and of LIM-kinase (LIMK), which in turn phosphorylates and cofilin were all detected by Western blot in bovine caudal inactivates cofilin, an actin depolymerizer, the end result being sperm. -
A SARS-Cov-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing
A SARS-CoV-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing Supplementary Information Supplementary Discussion All SARS-CoV-2 protein and gene functions described in the subnetwork appendices, including the text below and the text found in the individual bait subnetworks, are based on the functions of homologous genes from other coronavirus species. These are mainly from SARS-CoV and MERS-CoV, but when available and applicable other related viruses were used to provide insight into function. The SARS-CoV-2 proteins and genes listed here were designed and researched based on the gene alignments provided by Chan et. al. 1 2020 . Though we are reasonably sure the genes here are well annotated, we want to note that not every protein has been verified to be expressed or functional during SARS-CoV-2 infections, either in vitro or in vivo. In an effort to be as comprehensive and transparent as possible, we are reporting the sub-networks of these functionally unverified proteins along with the other SARS-CoV-2 proteins. In such cases, we have made notes within the text below, and on the corresponding subnetwork figures, and would advise that more caution be taken when examining these proteins and their molecular interactions. Due to practical limits in our sample preparation and data collection process, we were unable to generate data for proteins corresponding to Nsp3, Orf7b, and Nsp16. Therefore these three genes have been left out of the following literature review of the SARS-CoV-2 proteins and the protein-protein interactions (PPIs) identified in this study. -
(P -Value<0.05, Fold Change≥1.4), 4 Vs. 0 Gy Irradiation
Table S1: Significant differentially expressed genes (P -Value<0.05, Fold Change≥1.4), 4 vs. 0 Gy irradiation Genbank Fold Change P -Value Gene Symbol Description Accession Q9F8M7_CARHY (Q9F8M7) DTDP-glucose 4,6-dehydratase (Fragment), partial (9%) 6.70 0.017399678 THC2699065 [THC2719287] 5.53 0.003379195 BC013657 BC013657 Homo sapiens cDNA clone IMAGE:4152983, partial cds. [BC013657] 5.10 0.024641735 THC2750781 Ciliary dynein heavy chain 5 (Axonemal beta dynein heavy chain 5) (HL1). 4.07 0.04353262 DNAH5 [Source:Uniprot/SWISSPROT;Acc:Q8TE73] [ENST00000382416] 3.81 0.002855909 NM_145263 SPATA18 Homo sapiens spermatogenesis associated 18 homolog (rat) (SPATA18), mRNA [NM_145263] AA418814 zw01a02.s1 Soares_NhHMPu_S1 Homo sapiens cDNA clone IMAGE:767978 3', 3.69 0.03203913 AA418814 AA418814 mRNA sequence [AA418814] AL356953 leucine-rich repeat-containing G protein-coupled receptor 6 {Homo sapiens} (exp=0; 3.63 0.0277936 THC2705989 wgp=1; cg=0), partial (4%) [THC2752981] AA484677 ne64a07.s1 NCI_CGAP_Alv1 Homo sapiens cDNA clone IMAGE:909012, mRNA 3.63 0.027098073 AA484677 AA484677 sequence [AA484677] oe06h09.s1 NCI_CGAP_Ov2 Homo sapiens cDNA clone IMAGE:1385153, mRNA sequence 3.48 0.04468495 AA837799 AA837799 [AA837799] Homo sapiens hypothetical protein LOC340109, mRNA (cDNA clone IMAGE:5578073), partial 3.27 0.031178378 BC039509 LOC643401 cds. [BC039509] Homo sapiens Fas (TNF receptor superfamily, member 6) (FAS), transcript variant 1, mRNA 3.24 0.022156298 NM_000043 FAS [NM_000043] 3.20 0.021043295 A_32_P125056 BF803942 CM2-CI0135-021100-477-g08 CI0135 Homo sapiens cDNA, mRNA sequence 3.04 0.043389246 BF803942 BF803942 [BF803942] 3.03 0.002430239 NM_015920 RPS27L Homo sapiens ribosomal protein S27-like (RPS27L), mRNA [NM_015920] Homo sapiens tumor necrosis factor receptor superfamily, member 10c, decoy without an 2.98 0.021202829 NM_003841 TNFRSF10C intracellular domain (TNFRSF10C), mRNA [NM_003841] 2.97 0.03243901 AB002384 C6orf32 Homo sapiens mRNA for KIAA0386 gene, partial cds. -
Biological Models of Colorectal Cancer Metastasis and Tumor Suppression
BIOLOGICAL MODELS OF COLORECTAL CANCER METASTASIS AND TUMOR SUPPRESSION PROVIDE MECHANISTIC INSIGHTS TO GUIDE PERSONALIZED CARE OF THE COLORECTAL CANCER PATIENT By Jesse Joshua Smith Dissertation Submitted to the Faculty of the Graduate School of Vanderbilt University In partial fulfillment of the requirements For the degree of DOCTOR OF PHILOSOPHY In Cell and Developmental Biology May, 2010 Nashville, Tennessee Approved: Professor R. Daniel Beauchamp Professor Robert J. Coffey Professor Mark deCaestecker Professor Ethan Lee Professor Steven K. Hanks Copyright 2010 by Jesse Joshua Smith All Rights Reserved To my grandparents, Gladys and A.L. Lyth and Juanda Ruth and J.E. Smith, fully supportive and never in doubt. To my amazing and enduring parents, Rebecca Lyth and Jesse E. Smith, Jr., always there for me. .my sure foundation. To Jeannine, Bill and Reagan for encouragement, patience, love, trust and a solid backing. To Granny George and Shawn for loving support and care. And To my beautiful wife, Kelly, My heart, soul and great love, Infinitely supportive, patient and graceful. ii ACKNOWLEDGEMENTS This work would not have been possible without the financial support of the Vanderbilt Medical Scientist Training Program through the Clinical and Translational Science Award (Clinical Investigator Track), the Society of University Surgeons-Ethicon Scholarship Fund and the Surgical Oncology T32 grant and the Vanderbilt Medical Center Section of Surgical Sciences and the Department of Surgical Oncology. I am especially indebted to Drs. R. Daniel Beauchamp, Chairman of the Section of Surgical Sciences, Dr. James R. Goldenring, Vice Chairman of Research of the Department of Surgery, Dr. Naji N. -
"The Genecards Suite: from Gene Data Mining to Disease Genome Sequence Analyses". In: Current Protocols in Bioinformat
The GeneCards Suite: From Gene Data UNIT 1.30 Mining to Disease Genome Sequence Analyses Gil Stelzer,1,5 Naomi Rosen,1,5 Inbar Plaschkes,1,2 Shahar Zimmerman,1 Michal Twik,1 Simon Fishilevich,1 Tsippi Iny Stein,1 Ron Nudel,1 Iris Lieder,2 Yaron Mazor,2 Sergey Kaplan,2 Dvir Dahary,2,4 David Warshawsky,3 Yaron Guan-Golan,3 Asher Kohn,3 Noa Rappaport,1 Marilyn Safran,1 and Doron Lancet1,6 1Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel 2LifeMap Sciences Ltd., Tel Aviv, Israel 3LifeMap Sciences Inc., Marshfield, Massachusetts 4Toldot Genetics Ltd., Hod Hasharon, Israel 5These authors contributed equally to the paper 6Corresponding author GeneCards, the human gene compendium, enables researchers to effectively navigate and inter-relate the wide universe of human genes, diseases, variants, proteins, cells, and biological pathways. Our recently launched Version 4 has a revamped infrastructure facilitating faster data updates, better-targeted data queries, and friendlier user experience. It also provides a stronger foundation for the GeneCards suite of companion databases and analysis tools. Improved data unification includes gene-disease links via MalaCards and merged biological pathways via PathCards, as well as drug information and proteome expression. VarElect, another suite member, is a phenotype prioritizer for next-generation sequencing, leveraging the GeneCards and MalaCards knowledgebase. It au- tomatically infers direct and indirect scored associations between hundreds or even thousands of variant-containing genes and disease phenotype terms. Var- Elect’s capabilities, either independently or within TGex, our comprehensive variant analysis pipeline, help prepare for the challenge of clinical projects that involve thousands of exome/genome NGS analyses. -
S41467-019-10037-Y.Pdf
ARTICLE https://doi.org/10.1038/s41467-019-10037-y OPEN Feedback inhibition of cAMP effector signaling by a chaperone-assisted ubiquitin system Laura Rinaldi1, Rossella Delle Donne1, Bruno Catalanotti 2, Omar Torres-Quesada3, Florian Enzler3, Federica Moraca 4, Robert Nisticò5, Francesco Chiuso1, Sonia Piccinin5, Verena Bachmann3, Herbert H Lindner6, Corrado Garbi1, Antonella Scorziello7, Nicola Antonino Russo8, Matthis Synofzik9, Ulrich Stelzl 10, Lucio Annunziato11, Eduard Stefan 3 & Antonio Feliciello1 1234567890():,; Activation of G-protein coupled receptors elevates cAMP levels promoting dissociation of protein kinase A (PKA) holoenzymes and release of catalytic subunits (PKAc). This results in PKAc-mediated phosphorylation of compartmentalized substrates that control central aspects of cell physiology. The mechanism of PKAc activation and signaling have been largely characterized. However, the modes of PKAc inactivation by regulated proteolysis were unknown. Here, we identify a regulatory mechanism that precisely tunes PKAc stability and downstream signaling. Following agonist stimulation, the recruitment of the chaperone- bound E3 ligase CHIP promotes ubiquitylation and proteolysis of PKAc, thus attenuating cAMP signaling. Genetic inactivation of CHIP or pharmacological inhibition of HSP70 enhances PKAc signaling and sustains hippocampal long-term potentiation. Interestingly, primary fibroblasts from autosomal recessive spinocerebellar ataxia 16 (SCAR16) patients carrying germline inactivating mutations of CHIP show a dramatic dysregulation of PKA signaling. This suggests the existence of a negative feedback mechanism for restricting hormonally controlled PKA activities. 1 Department of Molecular Medicine and Medical Biotechnologies, University Federico II, 80131 Naples, Italy. 2 Department of Pharmacy, University Federico II, 80131 Naples, Italy. 3 Institute of Biochemistry and Center for Molecular Biosciences, University of Innsbruck, A-6020 Innsbruck, Austria. -
ALK Gene ALK Receptor Tyrosine Kinase
ALK gene ALK receptor tyrosine kinase Normal Function The ALK gene provides instructions for making a protein called ALK receptor tyrosine kinase, which is part of a family of proteins called receptor tyrosine kinases (RTKs). Receptor tyrosine kinases transmit signals from the cell surface into the cell through a process called signal transduction. The process begins when the kinase is stimulated at the cell surface and then attaches to a similar kinase (dimerizes). After dimerization, the kinase is tagged with a marker called a phosphate group (a cluster of oxygen and phosphorus atoms) in a process called phosphorylation. Phosphorylation turns on ( activates) the kinase. The activated kinase is able to transfer a phosphate group to another protein inside the cell, which is activated as a result. The activation continues through a series of proteins in a signaling pathway. These signaling pathways are important in many cellular processes such as cell growth and division (proliferation) or maturation (differentiation). Although the specific function of ALK receptor tyrosine kinase is unknown, it is thought to act early in development to help regulate the proliferation of nerve cells. Health Conditions Related to Genetic Changes Neuroblastoma At least 16 mutations in the ALK gene have been identified in some people with neuroblastoma, a type of cancerous tumor composed of immature nerve cells ( neuroblasts). Neuroblastoma and other cancers occur when a buildup of genetic mutations in critical genes—those that control cell proliferation or differentiation—allows cells to grow and divide uncontrollably to form a tumor. In most cases, these genetic changes are acquired during a person's lifetime and are called somatic mutations. -
Whole Transcriptomic Expression Differences in EBV Immortalized Versus Primary B-Cells
W&M ScholarWorks Undergraduate Honors Theses Theses, Dissertations, & Master Projects 12-2010 Whole Transcriptomic Expression Differences in EBV Immortalized versus Primary B-Cells Dolores Huberts College of William and Mary Follow this and additional works at: https://scholarworks.wm.edu/honorstheses Part of the Biology Commons Recommended Citation Huberts, Dolores, "Whole Transcriptomic Expression Differences in EBV Immortalized versus Primary B- Cells" (2010). Undergraduate Honors Theses. Paper 347. https://scholarworks.wm.edu/honorstheses/347 This Honors Thesis is brought to you for free and open access by the Theses, Dissertations, & Master Projects at W&M ScholarWorks. It has been accepted for inclusion in Undergraduate Honors Theses by an authorized administrator of W&M ScholarWorks. For more information, please contact [email protected]. Whole Transcriptomic Expression Differences in EBV Immortalized versus Primary B-Cells A thesis submitted in partial fulfillment of the requirement for the degree of Bachelor of Science with Honors in Biology from the College of William and Mary in Virginia By Dolores Huberts Accepted for Honors ________________________________________ Lizabeth A. Allison, Director ________________________________________ Matthew Wawersik ________________________________________ Drew LaMar ________________________________________ Beverly Sher Williamsburg, Virginia December 17, 2010 ABSTRACT The Epstein–Barr Virus (EBV) is a human gamma herpes virus that infects more than 90% of the human population worldwide. It is commonly known in the US as the cause of Infectious Mononucleosis, and around the world as the cause of nasopharyngeal carcinoma and malignant lymphomas such as non-Hodgkin lymphoma, endemic Burkett’s lymphoma and Hodgkin lymphoma. Additionally, the EBV is used to immortalize cells to create cell lines for in-vitro studies. -
Crystal Structure of EML1 Reveals the Basis for Hsp90 Dependence of Oncogenic EML4-ALK by Disruption of an Atypical Β-Propeller Domain
Crystal structure of EML1 reveals the basis for Hsp90 dependence of oncogenic EML4-ALK by disruption of an atypical β-propeller domain Mark W. Richardsa, Edward W. P. Lawb,La’Verne P. Rennallsc, Sara Busaccab, Laura O’Regana, Andrew M. Frya, Dean A. Fennellb, and Richard Baylissa,1 aDepartment of Biochemistry, University of Leicester, Leicester LE1 9HN, United Kingdom; bDepartment of Cancer Studies and Molecular Medicine, University of Leicester, Leicester LE1 9HN, United Kingdom; and cSection of Structural Biology, Institute of Cancer Research, London SW3 6JB, United Kingdom Edited by Charles David Stout, The Scripps Research Institute, La Jolla, CA, and accepted by the Editorial Board February 24, 2014 (received for review December 9, 2013) Proteins of the echinoderm microtubule-associated protein (EMAP)- variant 1 and regression in some EML4-ALK–positive tumor like (EML) family contribute to formation of the mitotic spindle and models (7, 9, 10). Furthermore, clinical efficacy of an Hsp90 in- interphase microtubule network. They contain a unique hydropho- hibitor in EML4-ALK NSCLC has been confirmed (11), and bic EML protein (HELP) motif and a variable number of WD40 clinical trials are ongoing. However, because neither ALK nor repeats. Recurrent gene rearrangements in nonsmall cell lung cancer EML4 are native Hsp90 clients, it was proposed that Hsp90 sen- fuse EML4 to anaplastic lymphoma kinase (ALK), causing expression sitivity of EML4-ALK fusions was due to their protein-folding of several fusion oncoprotein variants. We have determined a 2.6-Å properties, which might expose hydrophobic residues that lead to crystal structure of the representative ∼70-kDa core of EML1, re- Hsp90 recruitment (12). -
S12967-021-02982-4.Pdf
Xia et al. J Transl Med (2021) 19:308 https://doi.org/10.1186/s12967-021-02982-4 Journal of Translational Medicine RESEARCH Open Access Molecular characteristics and clinical outcomes of complex ALK rearrangements identifed by next-generation sequencing in non-small cell lung cancers Peiyi Xia1†, Lan Zhang1†, Pan Li1†, Enjie Liu1, Wencai Li1, Jianying Zhang2, Hui Li3, Xiaoxing Su3 and Guozhong Jiang1* Abstract Background: Complex kinase rearrangement, a mutational process involving one or two chromosomes with clustered rearrangement breakpoints, interferes with the accurate detection of kinase fusions by DNA-based next- generation sequencing (NGS). We investigated the characteristics of complex ALK rearrangements in non-small cell lung cancers using multiple molecular tests. Methods: Samples of non-small cell lung cancer patients were analyzed by targeted-capture DNA-based NGS with probes tilling the selected intronic regions of fusion partner genes, RNA-based NGS, RT-PCR, immunohistochemistry (IHC) and fuorescence in situ hybridization (FISH). Results: In a large cohort of 6576 non-small cell lung cancer patients, 343 (5.2%) cases harboring ALK rearrange- ments were identifed. Fourteen cases with complex ALK rearrangements were identifed by DNA-based NGS and classifed into three types by integrating various genomic features, including intergenic (n 3), intragenic (n 5) and “bridge joint” rearrangements (n 6). All thirteen cases with sufcient samples actually expressed= canonical EML4-ALK= fusion transcripts confrmed by RNA-based= NGS. Besides, positive ALK IHC was detected in 13 of 13 cases, and 9 of 11 cases were positive in FISH testing. Patients with complex ALK rearrangements who received ALK inhibitors treatment (n 6), showed no diference in progression-free survival (PFS) compared with patients with canonical ALK fusions n = 36, P 0.9291).