DOCSLIB.ORG

The Mtor Substrate S6 Kinase 1 (S6K1) Is a Negative Regulator of Axon Regeneration and a Potential Drug Target for Central Nervous System Injury

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

This Accepted Manuscript has not been copyedited and formatted. The final version may differ from this version. Research Articles: Cellular/Molecular The mTOR substrate S6 Kinase 1 (S6K1) is a negative regulator of axon regeneration and a potential drug target for Central Nervous System injury Hassan Al-Ali1,2,3, Ying Ding5,6, Tatiana Slepak1, Wei Wu5, Yan Sun5,7, Yania Martinez1, Xiao-Ming Xu5, V.P. Lemmon1,3 and J.l. Bixby1,3,4 1The Miami Project to Cure Paralysis, University of Miami Miller School of Medicine, Miami, FL 33136, USA. 2Peggy and Harold Katz Family Drug Discovery Center, University of Miami Miller School of Medicine, Miami, FL, 33136, USA. 3Department of Neurological Surgery, University of Miami Miller School of Medicine, Miami, FL 33136, USA. 4Department of Molecular & Cellular Pharmacology, University of Miami Miller School of Medicine, Miami, FL 33136, USA. 5Spinal Cord and Brain Injury Research Group, Stark Neurosciences Research Institute, Department of Neurological Surgery, Indiana University School of Medicine, Indianapolis, IN 46202, USA. 6Department of Histology and Embryology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong 510080, China. 7Department of Anatomy, Histology and Embryology, School of Basic Medical Sciences, Fudan University, Shanghai, 200032, China. DOI: 10.1523/JNEUROSCI.0931-17.2017 Received: 4 April 2017 Revised: 18 May 2017 Accepted: 27 May 2017 Published: 16 June 2017 Author contributions: H.A.-A., Y.D., T.S., W.W., Y.S., X.-M.X., V.P.L., and J.B. designed research; H.A.-A., Y.D., T.S., W.W., Y.S., and Y.M. performed research; H.A.-A., Y.D., and T.S. analyzed data; T.S., X.-M.X., V.P.L., and J.B. wrote the paper. Conflict of Interest: The authors declare no competing financial interests. We thank Yan Shi for her help with cell imaging and high content analysis. This work was supported by grants from the Department of Defense (W81XWH-13-1-077) and the National Institutes of Health (HD057632) to JLB and VPL, and NIH NS059622, DOD CDMRP W81XWH-12-1-0562, Merit Review Award I01 BX002356 from the U.S. Department of Veterans Affairs, and Craig H Neilsen Foundation 296749 to XMX. VPL holds the Walter G. Ross Distinguished Chair in Developmental Neuroscience. XMX holds the Mari Hulman George Chair in Neurological Surgery. Corresponding Authors: John L. Bixby, PhD, University of Miami Miller School of Medicine, 1400 NW 10th Ave., DT 1205, Miami, FL-33136, Phone: 305-243-7587, Email: [email protected]; Vance P. Lemmon, PhD, University of Miami Miller School of Medicine, 1095 NW 15th Ter., LPLC 1205, Miami, FL-33136, Phone: 305-243-7587, Email: [email protected] Cite as: J. Neurosci ; 10.1523/JNEUROSCI.0931-17.2017 Alerts: Sign up at www.jneurosci.org/cgi/alerts to receive customized email alerts when the fully formatted version of this article is published. Accepted manuscripts are peer-reviewed but have not been through the copyediting, formatting, or proofreading process. Copyright © 2017 the authors 1 Title: The mTOR substrate S6 Kinase 1 (S6K1) is a negative regulator of axon regeneration 2 and a potential drug target for Central Nervous System injury 3 4 Abbreviated title: Inhibiting S6 Kinase 1 promotes axon regeneration 5 6 Authors and affiliations: Hassan Al-Ali1,2,3,&, Ying Ding5,6.&, Tatiana Slepak1,&, Wei Wu5, Yan 7 Sun5,7, Yania Martinez1, Xiao-Ming Xu5, V.P. Lemmon1,3, *, J.L. Bixby1,3,4,* 8 9 1The Miami Project to Cure Paralysis, University of Miami Miller School of Medicine, Miami, FL 33136, 10 USA. 2Peggy and Harold Katz Family Drug Discovery Center, University of Miami Miller School of 11 Medicine, Miami, FL, 33136, USA. 3Department of Neurological Surgery, University of Miami Miller School 12 of Medicine, Miami, FL 33136, USA. 4Department of Molecular & Cellular Pharmacology, University of 13 Miami Miller School of Medicine, Miami, FL 33136, USA. 5Spinal Cord and Brain Injury Research Group, 14 Stark Neurosciences Research Institute, Department of Neurological Surgery, Indiana University School 15 of Medicine, Indianapolis, IN 46202, USA. 6Department of Histology and Embryology, Zhongshan School 16 of Medicine, Sun Yat-sen University, Guangzhou, Guangdong 510080, China. 7Department of Anatomy, 17 Histology and Embryology, School of Basic Medical Sciences, Fudan University, Shanghai, 200032, 18 China. &Co-first author. *Co-corresponding author. 19 *Corresponding Authors: John L. Bixby, PhD Vance P. Lemmon, PhD University of Miami Miller School of Medicine University of Miami Miller School of Medicine 1400 NW 10th Ave., DT 1205 1095 NW 15th Ter., LPLC 1205 Miami, FL-33136 Miami, FL-33136 Phone: 305-243-7587 Phone: 305-243-7587 Email: [email protected] Email: [email protected] 20 21 Pages: 39, Figures: 11, Abstract: 204 words, Introduction: 495 words, Discussion: 1440 22 words 23 24 Conflict of Interest 25 The authors declare no competing financial interests. 26 27 Acknowledgements 28 We thank Yan Shi for her help with cell imaging and high content analysis. This work was 29 supported by grants from the Department of Defense (W81XWH-13-1-077) and the National 30 Institutes of Health (HD057632) to JLB and VPL, and NIH NS059622, DOD CDMRP W81XWH- 31 12-1-0562, Merit Review Award I01 BX002356 from the U.S. Department of Veterans Affairs, 32 and Craig H Neilsen Foundation 296749 to XMX. VPL holds the Walter G. Ross Distinguished 33 Chair in Developmental Neuroscience. XMX holds the Mari Hulman George Chair in 34 Neurological Surgery. 35 36 37 38 1 39 Abstract 40 The mammalian target of Rapamycin (mTOR) positively regulates axon growth in the 41 mammalian central nervous system (CNS). Though axon regeneration and functional recovery 42 from CNS injuries are typically limited, knockdown or deletion of PTEN, a negative regulator of 43 mTOR, increases mTOR activity and induces robust axon growth and regeneration. It has been 44 suggested that inhibition of S6 Kinase 1 (S6K1, gene symbol: RPS6KB1), a prominent mTOR 45 target, would blunt mTOR’s positive effect on axon growth. In contrast to this expectation, we 46 demonstrate that inhibition of S6K1 in CNS neurons promotes neurite outgrowth in vitro by 2-3 47 fold. Biochemical analysis revealed that an mTOR-dependent induction of PI3K signaling is 48 involved in mediating this effect of S6K1 inhibition. Importantly, treating female mice in vivo with 49 PF-4708671, a selective S6K1 inhibitor, stimulated corticospinal tract (CST) regeneration across 50 a dorsal spinal hemisection between the cervical 5 and 6 cord segments (C5/C6), increasing 51 axon counts for at least 3 mm beyond the injury site at 8 weeks after injury. Concomitantly, 52 treatment with PF-4708671 produced significant locomotor recovery. Pharmacological targeting 53 of S6K1 may therefore constitute an attractive strategy for promoting axon regeneration 54 following CNS injury, especially given that S6K1 inhibitors are being assessed in clinical trials 55 for non-oncological indications. 56 Significance statement 57 Despite mTOR’s well-established function in promoting axon regeneration, the role of its 58 downstream target, S6K1, has been unclear. We used cellular assays with primary neurons to 59 demonstrate that S6K1 is a negative regulator of neurite outgrowth, and a spinal cord injury 60 model to show that it is a viable pharmacological target for inducing axon regeneration. We 61 provide mechanistic evidence that S6K1’s negative feedback to PI3K signaling is involved in 2 62 axon growth inhibition, and show that phosphorylation of S6K1 is a more appropriate 63 regeneration indicator than is S6 phosphorylation. 64 Introduction 65 The PI3K/mTOR pathway is a key regulator of axon growth and regeneration in the CNS (Park 66 et al., 2008). Typically, axons in the adult mammalian CNS have limited capacity for 67 regeneration following injury. Activating the PI3K/mTOR pathway by knockdown or genetic 68 deletion of its negative regulator, PTEN, results in a marked increase in regenerative capacity 69 (Zerhouni, 2004; Park et al., 2008, 2010; Zukor et al., 2013), and mTOR activity is critical for the 70 regeneration induced by loss of PTEN (Park et al., 2010). The mechanisms through which 71 mTOR promotes axon growth/regeneration are less clear; in particular, the role(s) of S6K1, a 72 downstream effector of mTOR, are incompletely understood (Hubert et al., 2014; Yang et al., 73 2014). 74 We previously screened a large number of kinase inhibitors in a neurite outgrowth assay 75 utilizing primary hippocampal neurons, and identified “hit” compounds that promote neurite 76 outgrowth (Al-Ali et al., 2013b). This phenotypic assay is reliable (Z’-factor > 0.7), and has 77 identified both chemical and genetic perturbagens that promote axon growth from a variety of 78 CNS neurons (Al-Ali et al., 2013a, 2017). In a followup study, we used machine learning to 79 relate data from the phenotypic screen of kinase inhibitors to kinase profiling data, which 80 allowed us to identify (and verify) “target” kinases whose inhibition induces neurite outgrowth 81 (Al-Ali et al., 2015). These target kinases included representatives of the family of ribosomal S6 82 protein kinases (RPS6Ks). 83 Two types of S6 kinases have been described based on their domain topology: the p70 84 ribosomal S6 kinases (S6K1 and S6K2, which phosphorylate S6 at S235/236/240/244/247) and the 85 p90 ribosomal S6 kinases (RSK1, RSK2, RSK3, and RSK4, which phosphorylate S6 at S235/236) 3 86 (Meyuhas, 2015). Two additional p90 kinases, MSK1 and MSK2, are included in the family by 87 virtue of sequence similarity (Pearce et al., 2010b), but don’t appear to have substantial activity 88 towards S6. Previous studies have shown that RSKs and MSKs negatively regulate neurite 89 outgrowth (Loh et al., 2008; Fischer et al., 2009; Buchser et al., 2010; Hubert et al., 2014).
Recommended publications
  • Gene Symbol Gene Description ACVR1B Activin a Receptor, Type IB

    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
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus

    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 Data

    Profiling Data

    Compound Name DiscoveRx Gene Symbol Entrez Gene Percent Compound Symbol Control Concentration (nM) JNK-IN-8 AAK1 AAK1 69 1000 JNK-IN-8 ABL1(E255K)-phosphorylated ABL1 100 1000 JNK-IN-8 ABL1(F317I)-nonphosphorylated ABL1 87 1000 JNK-IN-8 ABL1(F317I)-phosphorylated ABL1 100 1000 JNK-IN-8 ABL1(F317L)-nonphosphorylated ABL1 65 1000 JNK-IN-8 ABL1(F317L)-phosphorylated ABL1 61 1000 JNK-IN-8 ABL1(H396P)-nonphosphorylated ABL1 42 1000 JNK-IN-8 ABL1(H396P)-phosphorylated ABL1 60 1000 JNK-IN-8 ABL1(M351T)-phosphorylated ABL1 81 1000 JNK-IN-8 ABL1(Q252H)-nonphosphorylated ABL1 100 1000 JNK-IN-8 ABL1(Q252H)-phosphorylated ABL1 56 1000 JNK-IN-8 ABL1(T315I)-nonphosphorylated ABL1 100 1000 JNK-IN-8 ABL1(T315I)-phosphorylated ABL1 92 1000 JNK-IN-8 ABL1(Y253F)-phosphorylated ABL1 71 1000 JNK-IN-8 ABL1-nonphosphorylated ABL1 97 1000 JNK-IN-8 ABL1-phosphorylated ABL1 100 1000 JNK-IN-8 ABL2 ABL2 97 1000 JNK-IN-8 ACVR1 ACVR1 100 1000 JNK-IN-8 ACVR1B ACVR1B 88 1000 JNK-IN-8 ACVR2A ACVR2A 100 1000 JNK-IN-8 ACVR2B ACVR2B 100 1000 JNK-IN-8 ACVRL1 ACVRL1 96 1000 JNK-IN-8 ADCK3 CABC1 100 1000 JNK-IN-8 ADCK4 ADCK4 93 1000 JNK-IN-8 AKT1 AKT1 100 1000 JNK-IN-8 AKT2 AKT2 100 1000 JNK-IN-8 AKT3 AKT3 100 1000 JNK-IN-8 ALK ALK 85 1000 JNK-IN-8 AMPK-alpha1 PRKAA1 100 1000 JNK-IN-8 AMPK-alpha2 PRKAA2 84 1000 JNK-IN-8 ANKK1 ANKK1 75 1000 JNK-IN-8 ARK5 NUAK1 100 1000 JNK-IN-8 ASK1 MAP3K5 100 1000 JNK-IN-8 ASK2 MAP3K6 93 1000 JNK-IN-8 AURKA AURKA 100 1000 JNK-IN-8 AURKA AURKA 84 1000 JNK-IN-8 AURKB AURKB 83 1000 JNK-IN-8 AURKB AURKB 96 1000 JNK-IN-8 AURKC AURKC 95 1000 JNK-IN-8
  • In Vitro Pharmacological Profiling of R406 Identifies Molecular Targets

    In Vitro Pharmacological Profiling of R406 Identifies Molecular Targets

    ORIGINAL ARTICLE In vitro pharmacological profiling of R406 identifies molecular targets underlying the clinical effects of fostamatinib Michael G. Rolf, Jon O. Curwen, Margaret Veldman-Jones, Cath Eberlein, Jianyan Wang, Alex Harmer, Caroline J. Hellawell & Martin Braddock AstraZeneca R&D Alderley Park, Macclesfield, Cheshire SK10 4TG, United Kingdom Keywords Abstract Blood pressure elevation, fostamatinib, in vitro pharmacological profiling, R406, SYK Off-target pharmacology may contribute to both adverse and beneficial effects of a new drug. In vitro pharmacological profiling is often applied early in drug Correspondence discovery; there are fewer reports addressing the relevance of broad profiles to Michael G. Rolf, AstraZeneca R&D Molndal,€ clinical adverse effects. Here, we have characterized the pharmacological profile Pepparedsleden 1, 431 83 Mo¨ lndal, Sweden. of the active metabolite of fostamatinib, R406, linking an understanding of drug Tel: +46 31 776 60 40; Fax: +46 31 776 37 selectivity to the increase in blood pressure observed in clinical studies. R406 60; E-mail: [email protected] was profiled in a broad range of in vitro assays to generate a comprehensive Funding Information pharmacological profile and key targets were further investigated using func- No funding information provided. tional and cellular assay systems. A combination of traditional literature searches and text-mining approaches established potential mechanistic links Received: 9 April 2015; Accepted: 14 July between the profile of R406 and clinical side effects. R406 was selective outside 2015 the kinase domain, with only antagonist activity at the adenosine A3 receptor in the range relevant to clinical effects. R406 was less selective in the kinase Pharma Res Per, 3(5), 2015, e00175, doi: 10.1002/prp2.175 domain, having activity at many protein kinases at therapeutically relevant con- centrations when tested in multiple in vitro systems.
  • Genome-Wide DNA Methylation Analysis of KRAS Mutant Cell Lines Ben Yi Tew1,5, Joel K

    Genome-Wide DNA Methylation Analysis of KRAS Mutant Cell Lines Ben Yi Tew1,5, Joel K

    www.nature.com/scientificreports OPEN Genome-wide DNA methylation analysis of KRAS mutant cell lines Ben Yi Tew1,5, Joel K. Durand2,5, Kirsten L. Bryant2, Tikvah K. Hayes2, Sen Peng3, Nhan L. Tran4, Gerald C. Gooden1, David N. Buckley1, Channing J. Der2, Albert S. Baldwin2 ✉ & Bodour Salhia1 ✉ Oncogenic RAS mutations are associated with DNA methylation changes that alter gene expression to drive cancer. Recent studies suggest that DNA methylation changes may be stochastic in nature, while other groups propose distinct signaling pathways responsible for aberrant methylation. Better understanding of DNA methylation events associated with oncogenic KRAS expression could enhance therapeutic approaches. Here we analyzed the basal CpG methylation of 11 KRAS-mutant and dependent pancreatic cancer cell lines and observed strikingly similar methylation patterns. KRAS knockdown resulted in unique methylation changes with limited overlap between each cell line. In KRAS-mutant Pa16C pancreatic cancer cells, while KRAS knockdown resulted in over 8,000 diferentially methylated (DM) CpGs, treatment with the ERK1/2-selective inhibitor SCH772984 showed less than 40 DM CpGs, suggesting that ERK is not a broadly active driver of KRAS-associated DNA methylation. KRAS G12V overexpression in an isogenic lung model reveals >50,600 DM CpGs compared to non-transformed controls. In lung and pancreatic cells, gene ontology analyses of DM promoters show an enrichment for genes involved in diferentiation and development. Taken all together, KRAS-mediated DNA methylation are stochastic and independent of canonical downstream efector signaling. These epigenetically altered genes associated with KRAS expression could represent potential therapeutic targets in KRAS-driven cancer. Activating KRAS mutations can be found in nearly 25 percent of all cancers1.
  • WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT

    WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT

    (12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization I International Bureau (10) International Publication Number (43) International Publication Date WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT (51) International Patent Classification: CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, C12Q 1/68 (2018.01) A61P 31/18 (2006.01) DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, C12Q 1/70 (2006.01) HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, (21) International Application Number: MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, PCT/US2018/056167 OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, (22) International Filing Date: SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, 16 October 2018 (16. 10.2018) TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (25) Filing Language: English (84) Designated States (unless otherwise indicated, for every kind of regional protection available): ARIPO (BW, GH, (26) Publication Language: English GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, (30) Priority Data: UG, ZM, ZW), Eurasian (AM, AZ, BY, KG, KZ, RU, TJ, 62/573,025 16 October 2017 (16. 10.2017) US TM), European (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, ΓΕ , IS, IT, LT, LU, LV, (71) Applicant: MASSACHUSETTS INSTITUTE OF MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TECHNOLOGY [US/US]; 77 Massachusetts Avenue, TR), OAPI (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, Cambridge, Massachusetts 02139 (US).
  • Phospho-RPS6KA1(T359) Antibody Peptide Affinity Purified Rabbit Polyclonal Antibody (Pab) Catalog # Ap3497a

    Phospho-RPS6KA1(T359) Antibody Peptide Affinity Purified Rabbit Polyclonal Antibody (Pab) Catalog # Ap3497a

    9765 Clairemont Mesa Blvd, Suite C San Diego, CA 92124 Tel: 858.875.1900 Fax: 858.622.0609 Phospho-RPS6KA1(T359) Antibody Peptide Affinity Purified Rabbit Polyclonal Antibody (Pab) Catalog # AP3497a Specification Phospho-RPS6KA1(T359) Antibody - Product Information Application WB, DB,E Primary Accession Q15418 Other Accession P10666, P10665, P18652 Reactivity Human Predicted Chicken, Xenopus Host Rabbit Clonality Polyclonal Isotype Rabbit Ig Calculated MW 82723 Phospho-RPS6KA1(T359) Antibody - Additional Information Gene ID 6195 Other Names Western blot analysis of extracts from Hela Ribosomal protein S6 kinase alpha-1, cells,untreated or treated with S6K-alpha-1, 90 kDa ribosomal protein S6 TPA,200nM，using phospho RPS6KA1-T359 (left) kinase 1, p90-RSK 1, p90RSK1, p90S6K, MAP or RPS6KA1 antibody(right) kinase-activated protein kinase 1a, MAPK-activated protein kinase 1a, MAPKAP kinase 1a, MAPKAPK-1a, Ribosomal S6 kinase 1, RSK-1, RPS6KA1, MAPKAPK1A, RSK1 Target/Specificity This RPS6KA1 Antibody is generated from rabbits immunized with a KLH conjugated synthetic phosphopeptide corresponding to amino acid residues surrounding T359 of human RPS6KA1. Dilution WB~~1:2000 DB~~1:500 Format Purified polyclonal antibody supplied in PBS with 0.09% (W/V) sodium azide. This antibody is purified through a protein A column, followed by peptide affinity purification. Dot blot analysis of anti-RPS6KA1-pT359 Pab (RB13385) on nitrocellulose membrane. 50ng Storage of Phospho-peptide or Non Phospho-peptide per Maintain refrigerated at 2-8°C for up to 6 dot were adsorbed. Antibody working months. For long term storage store at -20°C concentrations are 0.5ug per ml. in small aliquots to prevent freeze-thaw cycles.
  • Supplementary Material DNA Methylation in Inflammatory Pathways Modifies the Association Between BMI and Adult-Onset Non- Atopic

    Supplementary Material DNA Methylation in Inflammatory Pathways Modifies the Association Between BMI and Adult-Onset Non- Atopic

    Supplementary Material DNA Methylation in Inflammatory Pathways Modifies the Association between BMI and Adult-Onset Non- Atopic Asthma Ayoung Jeong 1,2, Medea Imboden 1,2, Akram Ghantous 3, Alexei Novoloaca 3, Anne-Elie Carsin 4,5,6, Manolis Kogevinas 4,5,6, Christian Schindler 1,2, Gianfranco Lovison 7, Zdenko Herceg 3, Cyrille Cuenin 3, Roel Vermeulen 8, Deborah Jarvis 9, André F. S. Amaral 9, Florian Kronenberg 10, Paolo Vineis 11,12 and Nicole Probst-Hensch 1,2,* 1 Swiss Tropical and Public Health Institute, 4051 Basel, Switzerland; [email protected] (A.J.); [email protected] (M.I.); [email protected] (C.S.) 2 Department of Public Health, University of Basel, 4001 Basel, Switzerland 3 International Agency for Research on Cancer, 69372 Lyon, France; [email protected] (A.G.); [email protected] (A.N.); [email protected] (Z.H.); [email protected] (C.C.) 4 ISGlobal, Barcelona Institute for Global Health, 08003 Barcelona, Spain; [email protected] (A.-E.C.); [email protected] (M.K.) 5 Universitat Pompeu Fabra (UPF), 08002 Barcelona, Spain 6 CIBER Epidemiología y Salud Pública (CIBERESP), 08005 Barcelona, Spain 7 Department of Economics, Business and Statistics, University of Palermo, 90128 Palermo, Italy; [email protected] 8 Environmental Epidemiology Division, Utrecht University, Institute for Risk Assessment Sciences, 3584CM Utrecht, Netherlands; [email protected] 9 Population Health and Occupational Disease, National Heart and Lung Institute, Imperial College, SW3 6LR London, UK; [email protected] (D.J.); [email protected] (A.F.S.A.) 10 Division of Genetic Epidemiology, Medical University of Innsbruck, 6020 Innsbruck, Austria; [email protected] 11 MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, W2 1PG London, UK; [email protected] 12 Italian Institute for Genomic Medicine (IIGM), 10126 Turin, Italy * Correspondence: [email protected]; Tel.: +41-61-284-8378 Int.
  • R Graphics Output

    R Graphics Output

    TNF signaling pathway all genes sink node genes ● ●● ●● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ●● ●●● ● ●● ● ● ● ● ● ● ●● ●● ● ● ● ● ●● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ●● ● ● ●● ●●● ●●● ●●● ● ● ● ●●● ● ●●● ● maximum = 3 maximum = 2 2 1 s> 10 0 <log −1 −2 2 1 x a m s 0 10 log −1 −2 group 1 group 2 group 3 group 4 group 5 group 6 group 7 group 8 TNF_signaling_pathway genes with data CASP10 CCL2 CCL5 CCL20 CASP7 FADD CXCL1 CXCL1 CXCL1 CASP3 CASP8 CXCL5 CXCL10 CX3CL1 CSF1 CSF2 BIRC2 ITCH CFLAR FAS IL18R1 JAG1 MAP3K5 IL1B IL6 IL15 LIF LTA TAB1 MAP2K7 MAPK8 FOS BCL3 NFKBIA SOCS3 TNFAIP3 TRAF1 TRAF2 MAP3K7 TNF TNFRSF1A TRADD RIPK1 MAP2K3 MAPK14 CEBPB MAP3K8 NFKB1 RPS6KA4 CREB3 BAG4 MAP3K14 MAP2K1 MAPK1 FOS JUN JUNB MMP3 MMP9 MMP14 IKBKB NFKBIA CHUK EDN1 VEGFC IKBKG NFKB1 NOD2 RIPK1 RIPK3 MLKL PGAM5 ICAM1 SELE VCAM1 DNM1L PGAM5 PTGS2 PIK3CA AKT3 NFKB1 MAP3K14 CHUK NFKBIA TRAF1 LTA TNFRSF1B TRAF2 BIRC2 RIPK1 MAP2K3 MAPK14 TRAF3 DAB2IP MAPK8 JUN IRF1 IFNB1 TNF_signaling_pathway sink nodes CASP10 CCL2 CCL5 CCL20 CASP7 FADD CXCL1 CXCL1 CXCL1 CASP3 CASP8 CXCL5 CXCL10 CX3CL1 CSF1 CSF2 BIRC2 ITCH CFLAR FAS IL18R1 JAG1 MAP3K5 IL1B IL6 IL15 LIF LTA TAB1 MAP2K7 MAPK8 FOS BCL3 NFKBIA SOCS3 TNFAIP3 TRAF1 TRAF2 MAP3K7 TNF TNFRSF1A TRADD
  • Personalized Prediction of Acquired Resistance to EGFR-Targeted Inhibitors Using a Pathway-Based Machine Learning Approach

    Personalized Prediction of Acquired Resistance to EGFR-Targeted Inhibitors Using a Pathway-Based Machine Learning Approach

    Cancers 2019, 11, x S1 of S9 Supplementary Materials: Personalized Prediction of Acquired Resistance to EGFR-Targeted Inhibitors Using a Pathway-Based Machine Learning Approach Young Rae Kim, Yong Wan Kim, Suh Eun Lee, Hye Won Yang and Sung Young Kim Table S1. Characteristics of individual studies. Sample Size Origin of Cancer Drug Dataset Platform S AR (Cell Lines) Lung cancer Agilent-014850 Whole Human GSE34228 26 26 (PC9) Genome Microarray 4x44K Gefitinib Epidermoid carcinoma Affymetrix Human Genome U133 GSE10696 3 3 (A431) Plus 2.0 Head and neck cancer Illumina HumanHT-12 V4.0 GSE62061 12 12 (Cal-27, SSC-25, FaDu, expression beadchip SQ20B) Erlotinib Head and neck cancer Illumina HumanHT-12 V4.0 GSE49135 3 3 (HN5) expression beadchip Lung cancer (HCC827, Illumina HumanHT-12 V3.0 GSE38310 3 6 ER3, T15-2) expression beadchip Lung cancer Illumina HumanHT-12 V3.0 GSE62504 1 2 (HCC827) expression beadchip Afatinib Lung cancer * Illumina HumanHT-12 V4.0 GSE75468 1 3 (HCC827) expression beadchip Head and neck cancer Affymetrix Human Genome U133 Cetuximab GSE21483 3 3 (SCC1) Plus 2.0 Array GEO, gene expression omnibus; GSE, gene expression series; S, sensitive; AR, acquired EGFR-TKI resistant; * Lung Cancer Cells Derived from Tumor Xenograft Model. Table S2. The performances of four penalized regression models. Model ACC precision recall F1 MCC AUROC BRIER Ridge 0.889 0.852 0.958 0.902 0.782 0.964 0.129 Lasso 0.944 0.957 0.938 0.947 0.889 0.991 0.042 Elastic Net 0.978 0.979 0.979 0.979 0.955 0.999 0.023 EPSGO Elastic Net 0.989 1.000 0.979 0.989 0.978 1.000 0.018 AUROC, area under curve of receiver operating characteristic; ACC, accuracy; MCC, Matthews correlation coefficient; EPSGO, Efficient Parameter Selection via Global Optimization algorithm.
  • X-Linked Diseases: Susceptible Females

    X-Linked Diseases: Susceptible Females

    REVIEW ARTICLE X-linked diseases: susceptible females Barbara R. Migeon, MD 1 The role of X-inactivation is often ignored as a prime cause of sex data include reasons why women are often protected from the differences in disease. Yet, the way males and females express their deleterious variants carried on their X chromosome, and the factors X-linked genes has a major role in the dissimilar phenotypes that that render women susceptible in some instances. underlie many rare and common disorders, such as intellectual deficiency, epilepsy, congenital abnormalities, and diseases of the Genetics in Medicine (2020) 22:1156–1174; https://doi.org/10.1038/s41436- heart, blood, skin, muscle, and bones. Summarized here are many 020-0779-4 examples of the different presentations in males and females. Other INTRODUCTION SEX DIFFERENCES ARE DUE TO X-INACTIVATION Sex differences in human disease are usually attributed to The sex differences in the effect of X-linked pathologic variants sex specific life experiences, and sex hormones that is due to our method of X chromosome dosage compensation, influence the function of susceptible genes throughout the called X-inactivation;9 humans and most placental mammals – genome.1 5 Such factors do account for some dissimilarities. compensate for the sex difference in number of X chromosomes However, a major cause of sex-determined expression of (that is, XX females versus XY males) by transcribing only one disease has to do with differences in how males and females of the two female X chromosomes. X-inactivation silences all X transcribe their gene-rich human X chromosomes, which is chromosomes but one; therefore, both males and females have a often underappreciated as a cause of sex differences in single active X.10,11 disease.6 Males are the usual ones affected by X-linked For 46 XY males, that X is the only one they have; it always pathogenic variants.6 Females are biologically superior; a comes from their mother, as fathers contribute their Y female usually has no disease, or much less severe disease chromosome.
  • The P90 RSK Family Members: Common Functions and Isoform Specificity

    The P90 RSK Family Members: Common Functions and Isoform Specificity

    Published OnlineFirst August 22, 2013; DOI: 10.1158/0008-5472.CAN-12-4448 Cancer Review Research The p90 RSK Family Members: Common Functions and Isoform Specificity Romain Lara, Michael J. Seckl, and Olivier E. Pardo Abstract The p90 ribosomal S6 kinases (RSK) are implicated in various cellular processes, including cell proliferation, survival, migration, and invasion. In cancer, RSKs modulate cell transformation, tumorigenesis, and metastasis. Indeed, changes in the expression of RSK isoforms have been reported in several malignancies, including breast, prostate, and lung cancers. Four RSK isoforms have been identified in humans on the basis of their high degree of sequence homology. Although this similarity suggests some functional redundancy between these proteins, an increasing body of evidence supports the existence of isoform-based specificity among RSKs in mediating particular cellular processes. This review briefly presents the similarities between RSK family members before focusing on the specific function of each of the isoforms and their involvement in cancer progression. Cancer Res; 73(17); 1–8. Ó2013 AACR. Introduction subsequently cloned throughout the Metazoan kingdom (2). The extracellular signal–regulated kinase (ERK)1/2 pathway The genomic analysis of several cancer types suggests that fi is involved in key cellular processes, including cell prolifera- these genes are not frequently ampli ed or mutated, with some tion, differentiation, survival, metabolism, and migration. notable exceptions (e.g., in the case of hepatocellular carcino- More than 30% of all human cancers harbor mutations within ma; ref. 6). Table 1 summarizes reported genetic changes in this pathway, mostly resulting in gain of function and conse- RSK genes.