A Logical Functional Analysis Pipeline
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Lemur Tyrosine Kinase 2 Acts As a Positive Regulator of NF-Κb Activation and Colon Cancer Cell Proliferation T
Cancer Letters 454 (2019) 70–77 Contents lists available at ScienceDirect Cancer Letters journal homepage: www.elsevier.com/locate/canlet Original Articles Lemur tyrosine kinase 2 acts as a positive regulator of NF-κB activation and colon cancer cell proliferation T ∗ Rongjing Zhanga,1, Xiuxiu Lia,1, Lumin Weib, Yanqing Qina, Jing Fangc,d, a CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China b Ruijin Hospital, Shanghai Jiaotong University, Shanghai, 200025, China c Cancer Institute, The Affiliated Hospital of Qingdao University, Qingdao, 266061, China d Cancer Institute, Qingdao University, 26601, Qingdao, 266061, China ARTICLE INFO ABSTRACT Keywords: Lemur tyrosine kinase 2 (LMTK2) belongs to both protein kinase and tyrosine kinase families. LMTK2 is less LMTK2 studied and little is known about its function. Here we demonstrate that LMTK2 modulates NF-κB activity and NF-κB functions to promote colonic tumorigenesis. We found that LMTK2 protein was abundant in colon cancer cells Colon cancer and LMTK2 knockdown (LMTK2-KD) inhibited proliferation of colon cancer cells through inactivating NF-κB. In unstimulated condition, LMTK2 modulated NF-κB through inhibiting phosphorylation of p65 at Ser468. Mechanistically, LMTK2 phosphorylated protein phosphatase 1A (PP1A) to prevent PP1A from depho- sphorylating p-GSK3β(Ser9). The p-GSK3β(Ser9) could not phosphorylate p65 at Ser468, which maintained the basal NF-κB activity. LMTK2 also modulated TNFα-activated NF-κB. LMTK2-KD repressed TNFα-induced IKKβ phosphorylation, IκBα degradation and NF-κB activation, implying that LMTK2 modulates TNFα-activated NF- κB via IKK. -
Ponatinib Shows Potent Antitumor Activity in Small Cell Carcinoma of the Ovary Hypercalcemic Type (SCCOHT) Through Multikinase Inhibition Jessica D
Published OnlineFirst February 9, 2018; DOI: 10.1158/1078-0432.CCR-17-1928 Cancer Therapy: Preclinical Clinical Cancer Research Ponatinib Shows Potent Antitumor Activity in Small Cell Carcinoma of the Ovary Hypercalcemic Type (SCCOHT) through Multikinase Inhibition Jessica D. Lang1,William P.D. Hendricks1, Krystal A. Orlando2, Hongwei Yin1, Jeffrey Kiefer1, Pilar Ramos1, Ritin Sharma3, Patrick Pirrotte3, Elizabeth A. Raupach1,3, Chris Sereduk1, Nanyun Tang1, Winnie S. Liang1, Megan Washington1, Salvatore J. Facista1, Victoria L. Zismann1, Emily M. Cousins4, Michael B. Major4, Yemin Wang5, Anthony N. Karnezis5, Aleksandar Sekulic1,6, Ralf Hass7, Barbara C. Vanderhyden8, Praveen Nair9, Bernard E. Weissman2, David G. Huntsman5,10, and Jeffrey M. Trent1 Abstract Purpose: Small cell carcinoma of the ovary, hypercalcemic type three SWI/SNF wild-type ovarian cancer cell lines. We further (SCCOHT) is a rare, aggressive ovarian cancer in young women identified ponatinib as the most effective clinically approved that is universally driven by loss of the SWI/SNF ATPase subunits RTK inhibitor. Reexpression of SMARCA4 was shown to confer SMARCA4 and SMARCA2. A great need exists for effective targeted a 1.7-fold increase in resistance to ponatinib. Subsequent therapies for SCCOHT. proteomic assessment of ponatinib target modulation in Experimental Design: To identify underlying therapeutic vul- SCCOHT cell models confirmed inhibition of nine known nerabilities in SCCOHT, we conducted high-throughput siRNA ponatinib target kinases alongside 77 noncanonical ponatinib and drug screens. Complementary proteomics approaches pro- targets in SCCOHT. Finally, ponatinib delayed tumor dou- filed kinases inhibited by ponatinib. Ponatinib was tested for bling time 4-fold in SCCOHT-1 xenografts while reducing efficacy in two patient-derived xenograft (PDX) models and one final tumor volumes in SCCOHT PDX models by 58.6% and cell-line xenograft model of SCCOHT. -
WO 2017/181183 Al 19 October 2017 (19.10.2017) P O P C T
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization International Bureau (10) International Publication Number (43) International Publication Date WO 2017/181183 Al 19 October 2017 (19.10.2017) P O P C T (51) International Patent Classification: (74) Agents: KARNAKIS, Jennifer A. et al; COOLEY LLP, C12Q 1/68 (2006.01) Attn: Patent Group, 1299 Pennsylvania Avenue, NW, Suite 700, Washington, District of Columbia 20004 (US). (21) International Application Number: PCT/US20 17/027944 (81) Designated States (unless otherwise indicated, for every kind of national protection available): AE, AG, AL, AM, (22) International Filing Date: AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, 17 April 2017 (17.04.2017) BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, (25) Filing Language: English DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IR, IS, JP, KE, KG, KH, KN, (26) Publication Language: English KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, (30) Priority Data: MD, ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, 62/322,982 15 April 2016 (15.04.2016) US NI, NO, NZ, OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, (71) Applicant: EXOSOME DIAGNOSTICS, INC. [US/US]; TH, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, Riverside Technology Center, 840 Memorial Drive, Suite ZA, ZM, ZW. 3, Cambridge, Massachusetts 02139 (US). -
Logic Programming for Big Data in Computational Biology
Logic Programming for Big Data in Computational Biology Nicos Angelopoulos Wellcome Sanger Institute Hinxton, Cambridge [email protected] 18.9.18 overview I knowledge for Bayesian machine learning over model structure I applied knowledge representation for biological data analytics Bayesian inference of model structure (Bims) A Bayesian machine learning system that can model prior knowledge by means of a probabilistic logic programming. Nonmeclature I DLPs = Distributional logic programs I Bims = Bayesian inference of model structure Timeline I Theory (York, 2000-5) I Applications (Edinburgh, 2006-8, IAH 2009, NKI 2013) I Bims library and theory paper 2015-2017 Bims Overview I syntax of DLPs I a succinct classification tree prior program I Bayesian learning of model structure I learning classification and regression trees I Bayesian learning of Bayesian networks I thebims library DLPs- description We extend LP's clausal syntax with probabilistic guards that associate a resolution step using a particular clause with a probability whose value is computed on-the-fly. The intuition is that this value can be used as the probability with which the clause is selected for resolution. Thus in addition to the logical relation, a clause defines over the objects that appear as arguments in its head, it also defines a probability distribution over aspects of this relation. DLPs example member(H; [Hj T ]): member(El; [ HjT ]) :− (C1) member(El; T ): L :: length(List; L) ∼ El :: umember(El; List)(G1) 1 :: L :: umember(El; [EljTail]): (C ) L 2 1 1 − :: L :: umember(El; [HjTail]) :− (C ) L 3 umember(El; Tail): DLPs probabilistic goals 1 :: L :: umember(El; [EljTail]): (C ) L 4 1 1 − :: L :: umember(El; [HjTail]) :− (C ) L 5 K is L − 1; K :: umember(El; Tail): DLPs query ? − umember(X ; [a; b; c]): X = a (1=3 of the times = 1=3); X = b (1=3 of the times = 2=3 ∗ 1=2); X = c (1=3 of the times = 2=3 ∗ 1=2 ∗ 1): simple tree prior ?- cart( ζ, ξ, A,M). -
Taqman® Human Protein Kinase Array
TaqMan® Gene Signature Arrays TaqMan® Human Protein Kinase Array This array is part of a collection of TaqMan® Gene Signature these kinases are from receptor protein-tyrosine kinase (RPTK) Arrays that enable analysis of hundreds of TaqMan® Gene families: EGFR, InsulinR, PDGFR, VEGFR, FGFR, CCK, NGFR, Expression Assays on a micro fluidic card with minimal effort. HGFR, EPHR, AXL, TIE, RYK, DDR, RET, ROS, LTK, ROR and MUSK. The remaining 15 kinases are Ser/Thr kinases from the Protein kinases are one of the largest families of genes in kinase families: CAMKL, IRAK, Lmr, RIPK and STKR. eukaryotes. They belong to one superfamily containing a eukaryotic protein kinase catalytic domain. The ability of kinases We have also selected assays for 26 non-kinase genes in the to reversibly phosphorylate and regulate protein function Human Protein Kinase Array. These genes are involved in signal has been a subject of intense investigation. Kinases are transduction and mediate protein-protein interaction, transcrip- responsible for most of the signal transduction in eukaryotic tional regulation, neural development and cell adhesion. cells, affecting cellular processes including metabolism, References: angiogenesis, hemopoiesis, apoptosis, transcription and Manning, G., Whyte, D.B., Martinez, R., Hunter, T., and differentiation. Protein kinases are also involved in functioning Sudarsanam, S. 2002. The Protein Kinase Complement of the of the nervous and immune systems, in physiologic responses Human Genome. Science 298:1912–34. and in development. Imbalances in signal transduction due to accumulation of mutations or genetic alterations have Blume-Jensen, P. and Hunter, T. 2001. Oncogenic kinase been shown to result in malignant transformation. -
UNIVERSITY of CALIFORNIA Los Angeles Non-Mutated Kinases in Metastatic Prostate Cancer
UNIVERSITY OF CALIFORNIA Los Angeles Non-mutated kinases in metastatic prostate cancer: drivers and therapeutic targets A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Molecular Biology by Claire Faltermeier 2016 © Copyright by Claire Faltermeier 2016 ABSTRACT OF THE DISSERTATION Non-mutated kinases in prostate cancer: drivers and therapeutic targets by Claire Faltermeier Doctor of Philosophy in Molecular Biology University of California, Los Angeles, 2016 Professor Hanna K. A. Mikkola, Chair Metastatic prostate cancer lacks effective treatments and is a major cause of death in the United States. Targeting mutationally activated protein kinases has improved patient survival in numerous cancers. However, genetic alterations resulting in constitutive kinase activity are rare in metastatic prostate cancer. Evidence suggests that non-mutated, wild-type kinases are involved in advanced prostate cancer, but it remains unknown whether kinases contribute mechanistically to metastasis and should be pursued as therapeutic targets. Using a mass- spectrometry based phosphoproteomics approach, we identified tyrosine, serine, and threonine kinases that are differentially activated in human metastatic prostate cancer tissue specimens compared to localized disease. To investigate the functional role of these kinases in prostate cancer metastasis, we screened over 100 kinases identified from our phosphoproteomic and previously-published transcriptomic studies for their ability to drive metastasis. In a primary ii screen using a lung colonization assay, we identified 20 kinases that when overexpressed in murine prostate cancer cells could promote metastasis to the lungs with different latencies. We queried these 20 kinases in a secondary in vivo screen using non-malignant human prostate cells. -
Quantitative Phosphoproteomics Uncovers Dysregulated
bioRxiv preprint doi: https://doi.org/10.1101/2020.08.18.255778; this version posted August 18, 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 Quantitative phosphoproteomics 2 uncovers dysregulated kinase 3 networks in Alzheimer’s disease 4 Nader Morshed1,2, Meelim Lee1 , Felicia H. Rodriguez3, Douglas A. Lauffenburger1, Diego 5 Mastroeni4 , Forest White1,2,5,* 6 1 Department of Bioengineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA 7 2 Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 8 02139, USA 9 3 Department of Chemical and Materials Engineering, New Mexico State University, Las Cruces, NM 10 88003, USA 11 4 Arizona State University-Banner Neurodegenerative Disease Research Center, Tempe, Arizona 85287, 12 USA 13 5 Center for Precision Cancer Medicine, Massachusetts Institute of Technology, Cambridge, MA 02139, 14 USA 15 * Correspondence: [email protected] 16 Abstract 17 Alzheimer’s disease (AD) is a form of dementia characterized by amyloid-β plaques and Tau 18 neurofibrillary tangles that progressively disrupt neural circuits in the brain. The signaling networks 19 underlying the pathological changes in AD are poorly characterized at the level phosphoproteome. Using 20 mass spectrometry, we performed a combined analysis of the tyrosine, serine, and threonine 21 phosphoproteome, and proteome of temporal cortex tissue from AD patients and aged matched 22 controls. We identified several co-correlated peptide modules that were associated with varying levels 23 of phospho-Tau, oligodendrocyte, astrocyte, microglia, and neuronal pathologies in AD patients. -
Combinational Blockade of MET and PD-L1 Improves Pancreatic Cancer
Li et al. Journal of Experimental & Clinical Cancer Research (2021) 40:279 https://doi.org/10.1186/s13046-021-02055-w RESEARCH Open Access Combinational blockade of MET and PD-L1 improves pancreatic cancer immunotherapeutic efficacy Enliang Li1,2,3,4,5,6†, Xing Huang1,2,3,4,5,6*†, Gang Zhang1,2,3,4,5,6† and Tingbo Liang1,2,3,4,5,6* Abstract Background: Dysregulated expression and activation of receptor tyrosine kinases (RTKs) are associated with a range of human cancers. However, current RTK-targeting strategies exert little effect on pancreatic cancer, a highly malignant tumor with complex immune microenvironment. Given that immunotherapy for pancreatic cancer still remains challenging, this study aimed to elucidate the prognostic role of RTKs in pancreatic tumors with different immunological backgrounds and investigate their targeting potential in pancreatic cancer immunotherapy. Methods: Kaplan–Meier plotter was used to analyze the prognostic significance of each of the all-known RTKs to date in immune “hot” and “cold” pancreatic cancers. Gene Expression Profiling Interactive Analysis-2 was applied to assess the differential expression of RTKs between pancreatic tumors and normal pancreatic tissues, as well as its correlation with immune checkpoints (ICPs). One hundred and fifty in-house clinical tissue specimens of pancreatic cancer were collected for expression and correlation validation via immunohistochemical analysis. Two pancreatic cancer cell lines were used to demonstrate the regulatory effects of RTKs on ICPs by biochemistry and flow cytometry. Two in vivo models bearing pancreatic tumors were jointly applied to investigate the combinational regimen of RTK inhibition and immune checkpoint blockade for pancreatic cancer immunotherapy. -
Supporting Information
Supporting Information Faltermeier et al. 10.1073/pnas.1521674112 A. FU-R1-R2-V5-SV40-BlasƟ-CGW UbiquiƟn-C CMV 5’ LTR R1 Kinase R2 V5 SV40 BlastiR 3’ LTR promoter promoter GFP B. Kinase (kDa) 210 CMV GFP WPR 105 promot E er 78 49 38 28 V5 293t cells Fig. S1. Lentivirus-mediated overexpression of V5-tagged kinases. (A) Full-length kinases were cloned into the FU-R1-R2-V5-SV40-Blasti-CGW lentiviral vector shown. R1 and R2 represent recombination sites required for recombination-based Gateway cloning. LTR, Long-terminal repeat. (B) Western blot showing expression of selected kinases in 293t cells detected by a V5 antibody. The molecular mass of each kinase is indicated in parentheses. A. vector SrcY529F 3 Cap8 cells 2 weeks 2 x107 Tail vein Y529F Src injecƟon SCID 1 Luciferase reporter BLI Radiance (p/sec/cm3/sr) B. Lungs from mice injected with Cap8-SrcY529F cells Mouse 1 Mouse 2 Fig. S2. SrcY529F promotes lung colonization when overexpressed in murine prostate cells. (A) Experimental design to demonstrate that expression of mu- tationally activated kinase SrcY529F in Cap8 cells promotes lung colonization. (B) Bright-field images of lungs removed from mice 3 wk after being injected with Cap8-SrcY529F cells. (Scale bars, 5 mm.) Faltermeier et al. www.pnas.org/cgi/content/short/1521674112 1of5 A. Lungs-NTRK2 210 105 NTRK2 78 49 38 V5 293t cells Metastases Ɵssue Lungs-EGFR 210 EGFR 105 78 49 38 V5 293t cells Metastases Ɵssues Lungs-Her2 210 105 HER2 78 49 38 V5 293t cells Metastases Ɵssues B. -
Gene Symbol Accession Alias/Prev Symbol Official Full Name AAK1 NM 014911.2 KIAA1048, Dkfzp686k16132 AP2 Associated Kinase 1
Gene Symbol Accession Alias/Prev Symbol Official Full Name AAK1 NM_014911.2 KIAA1048, DKFZp686K16132 AP2 associated kinase 1 (AAK1) AATK NM_001080395.2 AATYK, AATYK1, KIAA0641, LMR1, LMTK1, p35BP apoptosis-associated tyrosine kinase (AATK) ABL1 NM_007313.2 ABL, JTK7, c-ABL, p150 v-abl Abelson murine leukemia viral oncogene homolog 1 (ABL1) ABL2 NM_007314.3 ABLL, ARG v-abl Abelson murine leukemia viral oncogene homolog 2 (arg, Abelson-related gene) (ABL2) ACVR1 NM_001105.2 ACVRLK2, SKR1, ALK2, ACVR1A activin A receptor ACVR1B NM_004302.3 ACVRLK4, ALK4, SKR2, ActRIB activin A receptor, type IB (ACVR1B) ACVR1C NM_145259.2 ACVRLK7, ALK7 activin A receptor, type IC (ACVR1C) ACVR2A NM_001616.3 ACVR2, ACTRII activin A receptor ACVR2B NM_001106.2 ActR-IIB activin A receptor ACVRL1 NM_000020.1 ACVRLK1, ORW2, HHT2, ALK1, HHT activin A receptor type II-like 1 (ACVRL1) ADCK1 NM_020421.2 FLJ39600 aarF domain containing kinase 1 (ADCK1) ADCK2 NM_052853.3 MGC20727 aarF domain containing kinase 2 (ADCK2) ADCK3 NM_020247.3 CABC1, COQ8, SCAR9 chaperone, ABC1 activity of bc1 complex like (S. pombe) (CABC1) ADCK4 NM_024876.3 aarF domain containing kinase 4 (ADCK4) ADCK5 NM_174922.3 FLJ35454 aarF domain containing kinase 5 (ADCK5) ADRBK1 NM_001619.2 GRK2, BARK1 adrenergic, beta, receptor kinase 1 (ADRBK1) ADRBK2 NM_005160.2 GRK3, BARK2 adrenergic, beta, receptor kinase 2 (ADRBK2) AKT1 NM_001014431.1 RAC, PKB, PRKBA, AKT v-akt murine thymoma viral oncogene homolog 1 (AKT1) AKT2 NM_001626.2 v-akt murine thymoma viral oncogene homolog 2 (AKT2) AKT3 NM_181690.1 -
Dynamics of Dual Specificity Phosphatases and Their Interplay with Protein Kinases in Immune Signaling Yashwanth Subbannayya1,2, Sneha M
bioRxiv preprint doi: https://doi.org/10.1101/568576; this version posted March 5, 2019. 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. Dynamics of dual specificity phosphatases and their interplay with protein kinases in immune signaling Yashwanth Subbannayya1,2, Sneha M. Pinto1,2, Korbinian Bösl1, T. S. Keshava Prasad2 and Richard K. Kandasamy1,3,* 1Centre of Molecular Inflammation Research (CEMIR), and Department of Clinical and Molecular Medicine (IKOM), Norwegian University of Science and Technology, N-7491 Trondheim, Norway 2Center for Systems Biology and Molecular Medicine, Yenepoya (Deemed to be University), Mangalore 575018, India 3Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo and Oslo University Hospital, N-0349 Oslo, Norway *Correspondence: Richard K. Kandasamy ([email protected]) Abstract Dual specificity phosphatases (DUSPs) have a well-known role as regulators of the immune response through the modulation of mitogen activated protein kinases (MAPKs). Yet the precise interplay between the various members of the DUSP family with protein kinases is not well understood. Recent multi-omics studies characterizing the transcriptomes and proteomes of immune cells have provided snapshots of molecular mechanisms underlying innate immune response in unprecedented detail. In this study, we focused on deciphering the interplay between members of the DUSP family with protein kinases in immune cells using publicly available omics datasets. Our analysis resulted in the identification of potential DUSP- mediated hub proteins including MAPK7, MAPK8, AURKA, and IGF1R. Furthermore, we analyzed the association of DUSP expression with TLR4 signaling and identified VEGF, FGFR and SCF-KIT pathway modules to be regulated by the activation of TLR4 signaling. -
Exploring BCR-ABL-Independent Mechanisms of TKI-Resistance in Chronic Myeloid Leukaemia
Mitchell, Rebecca (2017) Exploring BCR-ABL-independent mechanisms of TKI-resistance in chronic myeloid leukaemia. PhD thesis. https://theses.gla.ac.uk/7977/ Copyright and moral rights for this work are retained by the author A copy can be downloaded for personal non-commercial research or study, without prior permission or charge This work cannot be reproduced or quoted extensively from without first obtaining permission in writing from the author The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the author When referring to this work, full bibliographic details including the author, title, awarding institution and date of the thesis must be given Enlighten: Theses https://theses.gla.ac.uk/ [email protected] Exploring BCR-ABL-independent mechanisms of TKI-Resistance in Chronic Myeloid Leukaemia By Rebecca Mitchell BSc (Hons), MRes Submitted in the fulfilment of the requirements for the degree of Doctor of Philosophy September 2016 Section of Experimental Haematology Institute of Cancer Sciences College of Medical, Veterinary and Life Science University of Glasgow 2 Abstract As the prevalence of Chronic Myeloid Leukaemia (CML) grows, due to the therapeutic success of tyrosine kinase inhibitors (TKI), we are witnessing increased incidences of drug resistance. Some of these patients have failed all currently licensed TKIs and have no mutational changes in the kinase domain that may explain the cause of TKI resistance. This poses a major clinical challenge as there are currently no other drug treatment options available for these patients. Therefore, our aim was to identify and target alternative survival pathways against BCR-ABL in order to eradicate TKI-resistant cells.