GAK and PRKCD Are Positive Regulators of PRKN-Independent
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Gene Symbol Gene Description ACVR1B Activin a Receptor, Type IB
Table S1. Kinase clones included in human kinase cDNA library for yeast two-hybrid screening Gene Symbol Gene Description ACVR1B activin A receptor, type IB ADCK2 aarF domain containing kinase 2 ADCK4 aarF domain containing kinase 4 AGK multiple substrate lipid kinase;MULK AK1 adenylate kinase 1 AK3 adenylate kinase 3 like 1 AK3L1 adenylate kinase 3 ALDH18A1 aldehyde dehydrogenase 18 family, member A1;ALDH18A1 ALK anaplastic lymphoma kinase (Ki-1) ALPK1 alpha-kinase 1 ALPK2 alpha-kinase 2 AMHR2 anti-Mullerian hormone receptor, type II ARAF v-raf murine sarcoma 3611 viral oncogene homolog 1 ARSG arylsulfatase G;ARSG AURKB aurora kinase B AURKC aurora kinase C BCKDK branched chain alpha-ketoacid dehydrogenase kinase BMPR1A bone morphogenetic protein receptor, type IA BMPR2 bone morphogenetic protein receptor, type II (serine/threonine kinase) BRAF v-raf murine sarcoma viral oncogene homolog B1 BRD3 bromodomain containing 3 BRD4 bromodomain containing 4 BTK Bruton agammaglobulinemia tyrosine kinase BUB1 BUB1 budding uninhibited by benzimidazoles 1 homolog (yeast) BUB1B BUB1 budding uninhibited by benzimidazoles 1 homolog beta (yeast) C9orf98 chromosome 9 open reading frame 98;C9orf98 CABC1 chaperone, ABC1 activity of bc1 complex like (S. pombe) CALM1 calmodulin 1 (phosphorylase kinase, delta) CALM2 calmodulin 2 (phosphorylase kinase, delta) CALM3 calmodulin 3 (phosphorylase kinase, delta) CAMK1 calcium/calmodulin-dependent protein kinase I CAMK2A calcium/calmodulin-dependent protein kinase (CaM kinase) II alpha CAMK2B calcium/calmodulin-dependent -
Core Lab Brochure
CHOOSE THE MOST TRUSTED LONG-READ TECHNOLOGY FOR YOUR CORE Sequence with Confidence The Sequel® II and IIe Systems are powered by Single Molecule, Real-Time (SMRT®) Sequencing, a technology proven to produce highly accurate long reads, known as HiFi reads, for sequencing data you and your customers can trust. SMRT SEQUENCING IS SMART BUSINESS HiFi Reads: PacBio is the only sequencing technology to offer highly accurate long reads. Because HiFi reads are extremely accurate, downstream analysis is simplified and streamlined, requiring less compute time than the error-prone long reads of other technologies. High Throughput: The Sequel II and IIe Systems have high data yields on robust, highly automated platforms to increase productivity and reduce project costs. Efficient and Easy-To-Use Workflows: Our end-to-end solutions feature library preparation in <3 hours and many push- button analysis workflows, so you can run projects quickly and easily. Support: All of our products are backed by a global team of scientists, bioinformaticians, and engineers who stand ready to provide you with outstanding service. OUTSTANDING PERFORMANCE AND RELIABILITY 99% of runs on the Sequel II System completed successfully Sequel II Systems provide reliable performance with the total bases produced by the PacBio fleet steadily increasing, and 99% of runs completed successfully. “In our experience, the Sequel II System was essentially production-ready right out of the box. We have used it for a range of applications and sample types — from human genome sequencing to metagenome and microbiome profiling to non-model plant and animal genomes — and results have been very good.” — Luke Tallon, Director of the Genomics Resource Center at Maryland Genomics pacb.com/Sequel SMRT SEQUENCING APPLICATIONS – EFFICIENT AND COST EFFECTIVE The Sequel II and IIe Systems support a wide range of applications, each adding unique value to a sequencing study. -
The Drug Sensitivity and Resistance Testing (DSRT) Approach
A phenotypic screening and machine learning platform eciently identifies triple negative breast cancer-selective and readily druggable targets Prson Gautam 1 Alok Jaiswal 1 Tero Aittokallio 1, 2 Hassan Al Ali 3 Krister Wennerberg 1,4 Identifying eective oncogenic targets is challenged by the complexity of genetic alterations in 1Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Finland cancer and their poorly understood relation to cell function and survival. There is a need for meth- Current kinome coverage of kinase inhibitors in TNBC exhibit diverse kinase dependencies MFM-223 is selectively addicted to FGFR2 2Department of Mathematics and Statistics, University of Turku, Finland 3The Miami Project to Cure Paralysis, Peggy and Harold Katz Family Drug Discovery Center, A A Sylvester Comprehensive Cancer Center, and Department of Neurological Surgery and Medicine ods that rapidly and accurately identify “pharmacologically eective” targets without the require- clinical evaluation TN Kinases MFM-223 CAL-120 MDA-MB-231 TNBC TNBC TNBC TNBC TNBC TNBC HER2+ 100 University of Miami Miller School of Medicine, Miami, FL 33136, USA. non- HER2+ FGFR1 0.97 0.00 0.00 MFM-223 BL1 BL2 M MSL IM LAR ER+, PR+ 50 ment for priori knowledge of complex signaling networks. We developed an approach that uses ma- cancerous FGFR2 56.46 0.00 0.00 CAL-120 25 4 MDA-MB-231 Biotech Research & Innovation Centre (BRIC) and Novo Nordisk Foundation Center HCC1937 CAL-85-1 CAL-120 MDA-MB-231 DU4475 CAL-148 MCF-10A SK-BR-3 BT-474 FGFR3 25.10 0.00 0.00 0 chine learning to relate results from unbiased phenotypic screening of kinase inhibitors to their bio- for Stem Cell Biology (DanStem), University of Copenhagen, Denmark HCC1599 HDQ-P1 BT-549 MDA-MB-436 MFM-223 FGFR4 0.00 0.00 0.00 MAXIS*Bk Clinical status MDA-MB-468 CAL-51 Hs578T MDA-MB-453 score chemical activity data. -
Protein Kinase D1 Regulates Hypoxic Metabolism Through HIF-1Α and Glycolytic Enzymes Incancer Cells
ONCOLOGY REPORTS 40: 1073-1082, 2018 Protein kinase D1 regulates hypoxic metabolism through HIF-1α and glycolytic enzymes incancer cells JIAO CHEN*, BOMIAO CUI*, YAPING FAN*, XIAOYING LI, QIAN LI, YUE DU, YUN FENG and PING ZHANG State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan 610041, P.R. China Received October 7, 2017; Accepted April 3, 2018 DOI: 10.3892/or.2018.6479 Abstract. Protein kinase D1 (PKD1), one of the protein Introduction kinase D (PKD) family members, plays a prominent role in multiple bio-behaviors of cancer cells. Low pH and hypoxia Oral cancer is a major public health issue and a social chal- are unique characteristics of the tumor microenvironment. lenge. Tongue squamous cell carcinoma (TSCC) is the most The aim of this study was to investigate the role and mecha- aggressive type of oral cancer. Environmental factors, genetics nism of PKD1 in regulating metabolism in the human tongue and immune status have been confirmed to be related to the squamous cell carcinoma (TSCC) cell line SCC25 under a tumorigenesis of tongue cancer (1). The tumor microenviron- hypoxic condition, as well as growth and apoptosis. Here, we ment, which is composed of complex components including found that hypoxia not only induced the expression of HIF-1α, stem cells, fibroblasts, immune cells and their secreted factors, but also induced the expression and activation of PKD1. is critical to the initiation, development and maintenance of Moreover, we inhibited the expression of PKD1 by shRNA tumorigenesis (1). As the ‘residence niche’ of cancer cells, the interference, and the growth of SCC25 cells under hypoxia was composition and structure of the tumor microenvironment significantly decreased, as well as the expression of HIF-1α, not only affects the bio-behavior, but also determines the while the percentage of apoptotic SCC25 cells was increased. -
Identifying Novel Actionable Targets in Colon Cancer
biomedicines Review Identifying Novel Actionable Targets in Colon Cancer Maria Grazia Cerrito and Emanuela Grassilli * Department of Medicine and Surgery, University of Milano-Bicocca, Via Cadore 48, 20900 Monza, Italy; [email protected] * Correspondence: [email protected] Abstract: Colorectal cancer is the fourth cause of death from cancer worldwide, mainly due to the high incidence of drug-resistance toward classic chemotherapeutic and newly targeted drugs. In the last decade or so, the development of novel high-throughput approaches, both genome-wide and chemical, allowed the identification of novel actionable targets and the development of the relative specific inhibitors to be used either to re-sensitize drug-resistant tumors (in combination with chemotherapy) or to be synthetic lethal for tumors with specific oncogenic mutations. Finally, high- throughput screening using FDA-approved libraries of “known” drugs uncovered new therapeutic applications of drugs (used alone or in combination) that have been in the clinic for decades for treating non-cancerous diseases (re-positioning or re-purposing approach). Thus, several novel actionable targets have been identified and some of them are already being tested in clinical trials, indicating that high-throughput approaches, especially those involving drug re-positioning, may lead in a near future to significant improvement of the therapy for colon cancer patients, especially in the context of a personalized approach, i.e., in defined subgroups of patients whose tumors carry certain mutations. Keywords: colon cancer; drug resistance; target therapy; high-throughput screen; si/sh-RNA screen; CRISPR/Cas9 knockout screen; drug re-purposing; drug re-positioning Citation: Cerrito, M.G.; Grassilli, E. -
A Novel Kinase Inhibitor Establishes a Predominant Role for Protein Kinase D As a Cardiac Class Iia Histone Deacetylase Kinase
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector FEBS Letters 584 (2010) 631–637 journal homepage: www.FEBSLetters.org A novel kinase inhibitor establishes a predominant role for protein kinase D as a cardiac class IIa histone deacetylase kinase Lauren Monovich a,*, Richard B. Vega a, Erik Meredith a, Karl Miranda a, Chang Rao a, Michael Capparelli a, Douglas D. Lemon b, Dillon Phan b, Keith A. Koch b, Joseph A. Chapo b, David B. Hood b, Timothy A. McKinsey b,* a Novartis Institutes for Biomedical Research, 3333 Walnut Street, Boulder, CO 80301, United States b Gilead Colorado, Inc., 3333 Walnut Street, Boulder, CO 80301, United States article info abstract Article history: Class IIa histone deacetylases (HDACs) repress genes involved in pathological cardiac hypertrophy. Received 13 November 2009 The anti-hypertrophic action of class IIa HDACs is overcome by signals that promote their phosphor- Revised 8 December 2009 ylation-dependent nuclear export. Several kinases have been shown to phosphorylate class IIa Accepted 11 December 2009 HDACs, including calcium/calmodulin-dependent protein kinase (CaMK), protein kinase D (PKD) Available online 14 December 2009 and G protein-coupled receptor kinase (GRK). However, the identity of the kinase(s) responsible Edited by Ivan Sadowski for phosphorylating class IIa HDACs during cardiac hypertrophy has remained controversial. We describe a novel and selective small molecule inhibitor of PKD, bipyridyl PKD inhibitor (BPKDi). BPKDi blocks signal-dependent phosphorylation and nuclear export of class IIa HDACs in cardio- Keywords: Kinase myocytes and concomitantly suppresses hypertrophy of these cells. -
Application of a MYC Degradation
SCIENCE SIGNALING | RESEARCH ARTICLE CANCER Copyright © 2019 The Authors, some rights reserved; Application of a MYC degradation screen identifies exclusive licensee American Association sensitivity to CDK9 inhibitors in KRAS-mutant for the Advancement of Science. No claim pancreatic cancer to original U.S. Devon R. Blake1, Angelina V. Vaseva2, Richard G. Hodge2, McKenzie P. Kline3, Thomas S. K. Gilbert1,4, Government Works Vikas Tyagi5, Daowei Huang5, Gabrielle C. Whiten5, Jacob E. Larson5, Xiaodong Wang2,5, Kenneth H. Pearce5, Laura E. Herring1,4, Lee M. Graves1,2,4, Stephen V. Frye2,5, Michael J. Emanuele1,2, Adrienne D. Cox1,2,6, Channing J. Der1,2* Stabilization of the MYC oncoprotein by KRAS signaling critically promotes the growth of pancreatic ductal adeno- carcinoma (PDAC). Thus, understanding how MYC protein stability is regulated may lead to effective therapies. Here, we used a previously developed, flow cytometry–based assay that screened a library of >800 protein kinase inhibitors and identified compounds that promoted either the stability or degradation of MYC in a KRAS-mutant PDAC cell line. We validated compounds that stabilized or destabilized MYC and then focused on one compound, Downloaded from UNC10112785, that induced the substantial loss of MYC protein in both two-dimensional (2D) and 3D cell cultures. We determined that this compound is a potent CDK9 inhibitor with a previously uncharacterized scaffold, caused MYC loss through both transcriptional and posttranslational mechanisms, and suppresses PDAC anchorage- dependent and anchorage-independent growth. We discovered that CDK9 enhanced MYC protein stability 62 through a previously unknown, KRAS-independent mechanism involving direct phosphorylation of MYC at Ser . -
Supplementary Information Method CLEAR-CLIP. Mouse Keratinocytes
Supplementary Information Method CLEAR-CLIP. Mouse keratinocytes of the designated genotype were maintained in E-low calcium medium. Inducible cells were treated with 3 ug/ml final concentration doxycycline for 24 hours before performing CLEAR-CLIP. One 15cm dish of confluent cells was used per sample. Cells were washed once with cold PBS. 10mls of cold PBS was then added and cells were irradiated with 300mJ/cm2 UVC (254nM wavelength). Cells were then scraped from the plates in cold PBS and pelleted by centrifugation at 1,000g for 2 minutes. Pellets were frozen at -80oC until needed. Cells were then lysed on ice with occasional vortexing in 1ml of lysis buffer (50mM Tris-HCl pH 7.4, 100mM NaCl, 1mM MgCl2, 0.1 mM CaCl2, 1% NP-40, 0.5% Sodium Deoxycholate, 0.1% SDS) containing 1X protease inhibitors (Roche #88665) and RNaseOUT (Invitrogen #10777019) at 4ul/ml final concentration. Next, TurboDNase (Invitrogen #AM2238, 10U), RNase A (0.13ug) and RNase T1 (0.13U) were added and samples were incubated at 37oC for 5 minutes with occasional mixing. Samples were immediately placed on ice and then centrifuged at 16,160g at 4oC for 20 minutes to clear lysate. 25ul of Protein-G Dynabeads (Invitrogen #10004D) were used per IP. Dynabeads were pre-washed with lysis buffer and pre- incubated with 3ul of Wako Anti-Mouse-Ago2 (2D4) antibody. The dynabead/antibody mixture was added to the lysate and rocked for 2 hours at 4oC. All steps after the IP were done on bead until samples were loaded into the polyacrylamide gel. -
The PRKCI and SOX2 Oncogenes Are Coamplified and Cooperate to Activate Hedgehog Signaling in Lung Squamous Cell Carcinoma
Cancer Cell Article The PRKCI and SOX2 Oncogenes Are Coamplified and Cooperate to Activate Hedgehog Signaling in Lung Squamous Cell Carcinoma Verline Justilien,1 Michael P. Walsh,1 Syed A. Ali,1 E. Aubrey Thompson,1 Nicole R. Murray,1 and Alan P. Fields1,* 1Department of Cancer Biology, Mayo Clinic Cancer Center, Jacksonville, FL 32224, USA *Correspondence: fi[email protected] http://dx.doi.org/10.1016/j.ccr.2014.01.008 SUMMARY We report that two oncogenes coamplified on chromosome 3q26, PRKCI and SOX2, cooperate to drive a stem-like phenotype in lung squamous cell carcinoma (LSCC). Protein kinase Ci (PKCi) phosphorylates SOX2, a master transcriptional regulator of stemness, and recruits it to the promoter of Hedgehog (Hh) acyltransferase (HHAT) that catalyzes the rate-limiting step in Hh ligand production. PKCi-mediated SOX2 phosphorylation is required for HHAT promoter occupancy, HHAT expression, and maintenance of a stem-like phenotype. Primary LSCC tumors coordinately overexpress PKCi, SOX2, and HHAT and require PKCi-SOX2-HHAT signaling to maintain a stem-like phenotype. Thus, PKCi and SOX2 are genetically, biochemically, and functionally linked in LSCC, and together they drive tumorigenesis by establishing a cell-autonomous Hh signaling axis. INTRODUCTION Similar cell populations exist in several cancer types (Chen et al., 2012; Driessens et al., 2012; Schepers et al., 2012). Line- Lung cancer is the major cause of cancer death, with a 5-year- age tracing reveals these cells clonally expand to give rise to survival rate of 16% (Siegel et al., 2012). Non-small cell lung malignant and nonmalignant, differentiated cell types. -
Supplementary Table 1. in Vitro Side Effect Profiling Study for LDN/OSU-0212320. Neurotransmitter Related Steroids
Supplementary Table 1. In vitro side effect profiling study for LDN/OSU-0212320. Percent Inhibition Receptor 10 µM Neurotransmitter Related Adenosine, Non-selective 7.29% Adrenergic, Alpha 1, Non-selective 24.98% Adrenergic, Alpha 2, Non-selective 27.18% Adrenergic, Beta, Non-selective -20.94% Dopamine Transporter 8.69% Dopamine, D1 (h) 8.48% Dopamine, D2s (h) 4.06% GABA A, Agonist Site -16.15% GABA A, BDZ, alpha 1 site 12.73% GABA-B 13.60% Glutamate, AMPA Site (Ionotropic) 12.06% Glutamate, Kainate Site (Ionotropic) -1.03% Glutamate, NMDA Agonist Site (Ionotropic) 0.12% Glutamate, NMDA, Glycine (Stry-insens Site) 9.84% (Ionotropic) Glycine, Strychnine-sensitive 0.99% Histamine, H1 -5.54% Histamine, H2 16.54% Histamine, H3 4.80% Melatonin, Non-selective -5.54% Muscarinic, M1 (hr) -1.88% Muscarinic, M2 (h) 0.82% Muscarinic, Non-selective, Central 29.04% Muscarinic, Non-selective, Peripheral 0.29% Nicotinic, Neuronal (-BnTx insensitive) 7.85% Norepinephrine Transporter 2.87% Opioid, Non-selective -0.09% Opioid, Orphanin, ORL1 (h) 11.55% Serotonin Transporter -3.02% Serotonin, Non-selective 26.33% Sigma, Non-Selective 10.19% Steroids Estrogen 11.16% 1 Percent Inhibition Receptor 10 µM Testosterone (cytosolic) (h) 12.50% Ion Channels Calcium Channel, Type L (Dihydropyridine Site) 43.18% Calcium Channel, Type N 4.15% Potassium Channel, ATP-Sensitive -4.05% Potassium Channel, Ca2+ Act., VI 17.80% Potassium Channel, I(Kr) (hERG) (h) -6.44% Sodium, Site 2 -0.39% Second Messengers Nitric Oxide, NOS (Neuronal-Binding) -17.09% Prostaglandins Leukotriene, -
CDK5 Functions As a Tumor Promoter in Human Lung Cancer Jie Zeng1#, Shuanshuan Xie1#, Yang Liu1, Changxing Shen1, Xiaolian Song1, Guo-Lei Zhou2, 3, Changhui Wang1
Journal of Cancer 2018, Vol. 9 3950 Ivyspring International Publisher Journal of Cancer 2018; 9(21): 3950-3961. doi: 10.7150/jca.25967 Research Paper CDK5 Functions as a Tumor Promoter in Human Lung Cancer Jie Zeng1#, Shuanshuan Xie1#, Yang Liu1, Changxing Shen1, Xiaolian Song1, Guo-Lei Zhou2, 3, Changhui Wang1 1. Department of Respiratory Medicine, Shanghai Tenth People’s Hospital, Tongji University, Shanghai 200072, PR China; 2. Department of Biological Sciences, Arkansas State University, State University, AR 72467, USA; 3. Molecular Biosciences Program, Arkansas State University, State University, AR 72467, USA. # These authors have contributed equally to this work. Corresponding author: Changhui Wang, No.301, Mid Yanchang Rd, Department of Respiratory Medicine, Shanghai Tenth People’s Hospital, Tongji University, Shanghai, China, 200072. Email: [email protected], Fax number: 86-021-66301685, Telephone: 86-021-66301685 © Ivyspring International Publisher. This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY-NC) license (https://creativecommons.org/licenses/by-nc/4.0/). See http://ivyspring.com/terms for full terms and conditions. Received: 2018.03.09; Accepted: 2018.08.19; Published: 2018.10.10 Abstract Cyclin-dependent kinase 5 (CDK5), an atypical member of the cyclin-dependent kinase family, plays an important role in the nervous system. Recent studies have shown that CDK5 is also associated with tumors. However, few studies have been done to investigate the mechanism underlying the connection between CDK5 and cancers. To explore the role of CDK5 in cancers by using an extensive bioinformatics data mining process. We mined the transcriptional, survival, functions and structure of CDK5 gene through databases and in vitro experiments. -
Development and Validation of a Protein-Based Risk Score for Cardiovascular Outcomes Among Patients with Stable Coronary Heart Disease
Supplementary Online Content Ganz P, Heidecker B, Hveem K, et al. Development and validation of a protein-based risk score for cardiovascular outcomes among patients with stable coronary heart disease. JAMA. doi: 10.1001/jama.2016.5951 eTable 1. List of 1130 Proteins Measured by Somalogic’s Modified Aptamer-Based Proteomic Assay eTable 2. Coefficients for Weibull Recalibration Model Applied to 9-Protein Model eFigure 1. Median Protein Levels in Derivation and Validation Cohort eTable 3. Coefficients for the Recalibration Model Applied to Refit Framingham eFigure 2. Calibration Plots for the Refit Framingham Model eTable 4. List of 200 Proteins Associated With the Risk of MI, Stroke, Heart Failure, and Death eFigure 3. Hazard Ratios of Lasso Selected Proteins for Primary End Point of MI, Stroke, Heart Failure, and Death eFigure 4. 9-Protein Prognostic Model Hazard Ratios Adjusted for Framingham Variables eFigure 5. 9-Protein Risk Scores by Event Type This supplementary material has been provided by the authors to give readers additional information about their work. Downloaded From: https://jamanetwork.com/ on 10/02/2021 Supplemental Material Table of Contents 1 Study Design and Data Processing ......................................................................................................... 3 2 Table of 1130 Proteins Measured .......................................................................................................... 4 3 Variable Selection and Statistical Modeling ........................................................................................