Investigation of YAP1 Localisation and Dynamics in Tumour Cell Biology
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Machine-Learning and Chemicogenomics Approach Defi Nes and Predicts Cross-Talk of Hippo and MAPK Pathways
Published OnlineFirst November 18, 2020; DOI: 10.1158/2159-8290.CD-20-0706 RESEARCH ARTICLE Machine -Learning and Chemicogenomics Approach Defi nes and Predicts Cross-Talk of Hippo and MAPK Pathways Trang H. Pham 1 , Thijs J. Hagenbeek 1 , Ho-June Lee 1 , Jason Li 2 , Christopher M. Rose 3 , Eva Lin 1 , Mamie Yu 1 , Scott E. Martin1 , Robert Piskol 2 , Jennifer A. Lacap 4 , Deepak Sampath 4 , Victoria C. Pham 3 , Zora Modrusan 5 , Jennie R. Lill3 , Christiaan Klijn 2 , Shiva Malek 1 , Matthew T. Chang 2 , and Anwesha Dey 1 ABSTRACT Hippo pathway dysregulation occurs in multiple cancers through genetic and non- genetic alterations, resulting in translocation of YAP to the nucleus and activation of the TEAD family of transcription factors. Unlike other oncogenic pathways such as RAS, defi ning tumors that are Hippo pathway–dependent is far more complex due to the lack of hotspot genetic alterations. Here, we developed a machine-learning framework to identify a robust, cancer type–agnostic gene expression signature to quantitate Hippo pathway activity and cross-talk as well as predict YAP/TEAD dependency across cancers. Further, through chemical genetic interaction screens and multiomics analyses, we discover a direct interaction between MAPK signaling and TEAD stability such that knockdown of YAP combined with MEK inhibition results in robust inhibition of tumor cell growth in Hippo dysregulated tumors. This multifaceted approach underscores how computational models combined with experimental studies can inform precision medicine approaches including predictive diagnostics and combination strategies. SIGNIFICANCE: An integrated chemicogenomics strategy was developed to identify a lineage- independent signature for the Hippo pathway in cancers. -
Table 2. Significant
Table 2. Significant (Q < 0.05 and |d | > 0.5) transcripts from the meta-analysis Gene Chr Mb Gene Name Affy ProbeSet cDNA_IDs d HAP/LAP d HAP/LAP d d IS Average d Ztest P values Q-value Symbol ID (study #5) 1 2 STS B2m 2 122 beta-2 microglobulin 1452428_a_at AI848245 1.75334941 4 3.2 4 3.2316485 1.07398E-09 5.69E-08 Man2b1 8 84.4 mannosidase 2, alpha B1 1416340_a_at H4049B01 3.75722111 3.87309653 2.1 1.6 2.84852656 5.32443E-07 1.58E-05 1110032A03Rik 9 50.9 RIKEN cDNA 1110032A03 gene 1417211_a_at H4035E05 4 1.66015788 4 1.7 2.82772795 2.94266E-05 0.000527 NA 9 48.5 --- 1456111_at 3.43701477 1.85785922 4 2 2.8237185 9.97969E-08 3.48E-06 Scn4b 9 45.3 Sodium channel, type IV, beta 1434008_at AI844796 3.79536664 1.63774235 3.3 2.3 2.75319499 1.48057E-08 6.21E-07 polypeptide Gadd45gip1 8 84.1 RIKEN cDNA 2310040G17 gene 1417619_at 4 3.38875643 1.4 2 2.69163229 8.84279E-06 0.0001904 BC056474 15 12.1 Mus musculus cDNA clone 1424117_at H3030A06 3.95752801 2.42838452 1.9 2.2 2.62132809 1.3344E-08 5.66E-07 MGC:67360 IMAGE:6823629, complete cds NA 4 153 guanine nucleotide binding protein, 1454696_at -3.46081884 -4 -1.3 -1.6 -2.6026947 8.58458E-05 0.0012617 beta 1 Gnb1 4 153 guanine nucleotide binding protein, 1417432_a_at H3094D02 -3.13334396 -4 -1.6 -1.7 -2.5946297 1.04542E-05 0.0002202 beta 1 Gadd45gip1 8 84.1 RAD23a homolog (S. -
Analysis of the Human Serum Proteome
Cedarville University DigitalCommons@Cedarville Pharmaceutical Sciences Faculty Publications Department of Pharmaceutical Sciences 6-2004 Analysis of the Human Serum Proteome King C. Chan David A. Lucas Denise Hise Carl F. Schaefer Zhen Xiao See next page for additional authors Follow this and additional works at: https://digitalcommons.cedarville.edu/ pharmaceutical_sciences_publications Part of the Pharmacy and Pharmaceutical Sciences Commons This Article is brought to you for free and open access by DigitalCommons@Cedarville, a service of the Centennial Library. It has been accepted for inclusion in Pharmaceutical Sciences Faculty Publications by an authorized administrator of DigitalCommons@Cedarville. For more information, please contact [email protected]. Authors King C. Chan, David A. Lucas, Denise Hise, Carl F. Schaefer, Zhen Xiao, George M. Janini, Kenneth H. Buetow, Haleem J. Issaq, Timothy D. Veenstra, and Thomas P. Conrads Clinical Proteomics Journal Copyright ©Humana Press Inc. All rights of any nature whatsoever are reserved. ISSN 1542-6416/04/01:101–225/$25.00 Serum/Plasma Proteome Analysis of the Human Serum Proteome King C. Chan,1,† David A. Lucas,1,† Denise Hise,2 Carl F. Schaefer,2 Zhen Xiao,1 George M. Janini,1 Kenneth H. Buetow,2 Haleem J. Issaq,1 Timothy D.Veenstra,1 and Thomas P. Conrads1,* 1Laboratory of Proteomics and Analytical Technologies, National Cancer Institute at Frederick, SAIC-Frederick, Inc, PO Box B, Frederick, MD 21702 2Center for Bioinformatics, National Cancer Institute, Bethesda, MD 20892 †These authors contributed equally to this work. each of which was analyzed by microcapillary Abstract reversed-phase liquid chromatography coupled Changes in serum proteins that signal online with MS/MS analysis. -
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. -
Targeting Tyro3 Ameliorates a Model of PGRN-Mutant FTLD-TDP Via Tau
ARTICLE DOI: 10.1038/s41467-018-02821-z OPEN Targeting Tyro3 ameliorates a model of PGRN- mutant FTLD-TDP via tau-mediated synaptic pathology Kyota Fujita1, Xigui Chen1, Hidenori Homma1, Kazuhiko Tagawa1, Mutsuki Amano 2, Ayumu Saito3, Seiya Imoto 4, Hiroyasu Akatsu5, Yoshio Hashizume6, Kozo Kaibuchi2, Satoru Miyano3 & Hitoshi Okazawa1 PGRN 1234567890():,; Mutations in the progranulin ( ) gene cause a tau pathology-negative and TDP43 pathology-positive form of frontotemporal lobar degeneration (FTLD-TDP). We generated a knock-in mouse harboring the R504X mutation (PGRN-KI). Phosphoproteomic analysis of this model revealed activation of signaling pathways connecting PKC and MAPK to tau prior to TDP43 aggregation and cognitive impairments, and identified PKCα as the kinase responsible for the early-stage tau phosphorylation at Ser203. Disinhibition of Gas6 binding to Tyro3 due to PGRN reduction results in activation of PKCα via PLCγ, inducing tau phosphorylation at Ser203, mislocalization of tau to dendritic spines, and spine loss. Administration of a PKC inhibitor, B-Raf inhibitor, or knockdown of molecules in the Gas6-Tyro3-tau axis rescues spine loss and cognitive impairment of PGRN-KI mice. Collectively, these results suggest that targeting of early-stage and aggregation-independent tau signaling represents a promising therapeutic strategy for this disease. 1 Department of Neuropathology, Medical Research Institute and Center for Brain Integration Research, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8510, Japan. 2 Department of Cell Pharmacology, Graduate School of Medicine, Nagoya University, 65, Tsurumai, Showa, Nagoya, Aichi 466-8550, Japan. 3 Human Genome Center, Institute of Medical Science, The University of Tokyo, 4-6-1, Shirokanedai, Minato-ku, Tokyo 108- 8639, Japan. -
A Key Genomic Signature Associated with Lymphovascular Invasion in Head and Neck Squamous Cell Carcinoma
A key genomic signature associated with lymphovascular invasion in head and neck squamous cell carcinoma Jian Zhang Aliated Cancer hospital & Institute of Guangzhou Medical University Huali Jiang Aliated Donghua Hospital of Sun Yat-sen University Tao Xie Aliated Cancer Hospital of Guangzhou Medical University Baiyao Wang Aliated Cancer Hospital of Guangzhou Medical Unversity Xiaoting Huang Aliated Cancer Hospital & Institute of Guangzhou Medical University Jie Lin Aliated Cancer Hospital & Institute of Guangzhou Medical University Anan Xu Aliated Cancer Hospital of Guangzhou Medical University Rong Li Aliated Cancer Hospital & Institute of Guangzhou Medical University Yawei Yuan ( [email protected] ) Guangzhou Medical University Aliated Cancer Hospital Research article Keywords: lymphovascular invasion, head and neck squamous cell carcinoma, hub genes, TCGA, weighted gene co-expression network analysis Posted Date: January 16th, 2020 DOI: https://doi.org/10.21203/rs.2.18349/v2 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/24 Abstract Objective: Lymphovascular invasion (LOI), a key pathological feature of head and neck squamous cell carcinoma (HNSCC), predicts poor survival. However, the associated clinical characteristics remain uncertain, and the molecular mechanisms are largely unknown. Methods: Weighted gene co-expression network analysis was performed to construct gene co-expression networks and investigate the relationship between modules and LOI clinical trait. Functional enrichment and KEGG pathway enrichment analysis were performed for differentially expressed genes using DAVID database. The protein-protein interaction network was constructed using Cytoscape software, and module analysis was performed using MCODE. Prognosis role and expression analysis was further validated by survival analysis, GEPIA analysis and HPA database. -
XP725 Antibody List Lot 129K4830
Panorama® Antibody Microarray-XPRESS Profiler725, XP725 List of Antibodies Lot: 129K4830 Reactivity Number Antibody Sigma No. Gene Ids Gene Symbols P/M Accessions Human Mouse Rat 3 Actin A5060 58 ACTA1 P NP_001091.1 n/d n/d n/d 5 Actin, αβ-Smooth Muscle A5228 59 ACTA2 M NP_001135417.1, NP_001604.1, yyy 6 β-Actin A1978 60 ACTB M NP_001092.1 yyy 7 β-Actin A2228 60 ACTB M NP_001092.1 yyy 8 a-Actinin A5044 87 ACTN1 M NP_001093.1 y y n/d 555 PARP P7605 142 PARP1 P NP_001609.2 y n/d n/d 11 β1 and β2-Adaptins A4450 162 AP1B1 M NP_001118.3 y n/d y 167 Chondroitin Sulfate C8035 176 ACAN M NP_001126.3, NP_037359.3 yyy 574 Protein Kinase Ba /Akt1 P2482 207 AKT1 M NP_001014431.1,NP_001014432.1 , NP_005154.2, yyy 575 Protein Kinase Ba /Akt1 P1601 207 AKT1 P NP_001014431.1,NP_001014432.1 , NP_005154.2, yyy 577 phospho-PKB (pSer473) P4112 207 AKT1 P NP_001014431.1,NP_001014432.1 , NP_005154.2, n/d y y 578 phospho-PKB (pThr308) P3862 207 AKT1 P NP_001014431.1,NP_001014432.1 , NP_005154.2, n/d y y 22 Annexin V A8604 308 ANXA5 M NP_001145.1 y n/d n/d 23 Annexin VII A4475 310 ANXA7 M NP_001147.1 yyy 29 Apaf1, N-Terminal A8469 317 APAF1 P NP_001151.1 y y n/d 457 Mint2 M3319 321 APBA2 P NP_001123886.1 n/d n/d y 28 AP Endonuclease A2105 328 APEX1 M NP_001632.2,NP_542379.1,NP_542380.1 yyy 692 Survivin S8191 332 BIRC5 P NP_001012270.1 yyy 17 β-Amyloid A8354 351 APP M NP_000475.1,NP_001129488.1 ,NP_001129601.1 ,NP_001129602.1 ,NP_001129603.1 ,NP_001191230.1 ,NP_001191231.1 ,NP_001191232.1,NP_958816.1,NP_9 y n/d n/d 18 Amyloid Precursor Protein, C-Terminal A8717 -
The Legionella Kinase Legk7 Exploits the Hippo Pathway Scaffold Protein MOB1A for Allostery and Substrate Phosphorylation
The Legionella kinase LegK7 exploits the Hippo pathway scaffold protein MOB1A for allostery and substrate phosphorylation Pei-Chung Leea,b,1, Ksenia Beyrakhovac,1, Caishuang Xuc, Michal T. Bonieckic, Mitchell H. Leea, Chisom J. Onub, Andrey M. Grishinc, Matthias P. Machnera,2, and Miroslaw Cyglerc,2 aDivision of Molecular and Cellular Biology, Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH, Bethesda, MD 20892; bDepartment of Biological Sciences, College of Liberal Arts and Sciences, Wayne State University, Detroit, MI 48202; and cDepartment of Biochemistry, University of Saskatchewan, Saskatoon, SK S7N5E5, Canada Edited by Ralph R. Isberg, Tufts University School of Medicine, Boston, MA, and approved May 1, 2020 (received for review January 12, 2020) During infection, the bacterial pathogen Legionella pneumophila Active LATS1/2 phosphorylate the cotranscriptional regulator manipulates a variety of host cell signaling pathways, including YAP1 (yes-associated protein 1) and its homolog TAZ (tran- the Hippo pathway which controls cell proliferation and differen- scriptional coactivator with PDZ-binding motif). Phosphorylated tiation in eukaryotes. Our previous studies revealed that L. pneu- YAP1 and TAZ are prevented from entering the nucleus by being mophila encodes the effector kinase LegK7 which phosphorylates either sequestered in the cytosol through binding to 14-3-3 pro- MOB1A, a highly conserved scaffold protein of the Hippo path- teins or targeted for proteolytic degradation (6, 8). Consequently, way. Here, we show that MOB1A, in addition to being a substrate the main outcome of signal transduction along the Hippo pathway of LegK7, also functions as an allosteric activator of its kinase is changes in gene expression (6). -
Genetic and Genomic Analysis of Hyperlipidemia, Obesity and Diabetes Using (C57BL/6J × TALLYHO/Jngj) F2 Mice
University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Nutrition Publications and Other Works Nutrition 12-19-2010 Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice Taryn P. Stewart Marshall University Hyoung Y. Kim University of Tennessee - Knoxville, [email protected] Arnold M. Saxton University of Tennessee - Knoxville, [email protected] Jung H. Kim Marshall University Follow this and additional works at: https://trace.tennessee.edu/utk_nutrpubs Part of the Animal Sciences Commons, and the Nutrition Commons Recommended Citation BMC Genomics 2010, 11:713 doi:10.1186/1471-2164-11-713 This Article is brought to you for free and open access by the Nutrition at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Nutrition Publications and Other Works by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. Stewart et al. BMC Genomics 2010, 11:713 http://www.biomedcentral.com/1471-2164/11/713 RESEARCH ARTICLE Open Access Genetic and genomic analysis of hyperlipidemia, obesity and diabetes using (C57BL/6J × TALLYHO/JngJ) F2 mice Taryn P Stewart1, Hyoung Yon Kim2, Arnold M Saxton3, Jung Han Kim1* Abstract Background: Type 2 diabetes (T2D) is the most common form of diabetes in humans and is closely associated with dyslipidemia and obesity that magnifies the mortality and morbidity related to T2D. The genetic contribution to human T2D and related metabolic disorders is evident, and mostly follows polygenic inheritance. The TALLYHO/ JngJ (TH) mice are a polygenic model for T2D characterized by obesity, hyperinsulinemia, impaired glucose uptake and tolerance, hyperlipidemia, and hyperglycemia. -
Serum Albumin OS=Homo Sapiens
Protein Name Cluster of Glial fibrillary acidic protein OS=Homo sapiens GN=GFAP PE=1 SV=1 (P14136) Serum albumin OS=Homo sapiens GN=ALB PE=1 SV=2 Cluster of Isoform 3 of Plectin OS=Homo sapiens GN=PLEC (Q15149-3) Cluster of Hemoglobin subunit beta OS=Homo sapiens GN=HBB PE=1 SV=2 (P68871) Vimentin OS=Homo sapiens GN=VIM PE=1 SV=4 Cluster of Tubulin beta-3 chain OS=Homo sapiens GN=TUBB3 PE=1 SV=2 (Q13509) Cluster of Actin, cytoplasmic 1 OS=Homo sapiens GN=ACTB PE=1 SV=1 (P60709) Cluster of Tubulin alpha-1B chain OS=Homo sapiens GN=TUBA1B PE=1 SV=1 (P68363) Cluster of Isoform 2 of Spectrin alpha chain, non-erythrocytic 1 OS=Homo sapiens GN=SPTAN1 (Q13813-2) Hemoglobin subunit alpha OS=Homo sapiens GN=HBA1 PE=1 SV=2 Cluster of Spectrin beta chain, non-erythrocytic 1 OS=Homo sapiens GN=SPTBN1 PE=1 SV=2 (Q01082) Cluster of Pyruvate kinase isozymes M1/M2 OS=Homo sapiens GN=PKM PE=1 SV=4 (P14618) Glyceraldehyde-3-phosphate dehydrogenase OS=Homo sapiens GN=GAPDH PE=1 SV=3 Clathrin heavy chain 1 OS=Homo sapiens GN=CLTC PE=1 SV=5 Filamin-A OS=Homo sapiens GN=FLNA PE=1 SV=4 Cytoplasmic dynein 1 heavy chain 1 OS=Homo sapiens GN=DYNC1H1 PE=1 SV=5 Cluster of ATPase, Na+/K+ transporting, alpha 2 (+) polypeptide OS=Homo sapiens GN=ATP1A2 PE=3 SV=1 (B1AKY9) Fibrinogen beta chain OS=Homo sapiens GN=FGB PE=1 SV=2 Fibrinogen alpha chain OS=Homo sapiens GN=FGA PE=1 SV=2 Dihydropyrimidinase-related protein 2 OS=Homo sapiens GN=DPYSL2 PE=1 SV=1 Cluster of Alpha-actinin-1 OS=Homo sapiens GN=ACTN1 PE=1 SV=2 (P12814) 60 kDa heat shock protein, mitochondrial OS=Homo -
KIF1A-Related Autosomal Dominant Spastic Paraplegias (SPG30) in Russian Families G
Rudenskaya et al. BMC Neurology (2020) 20:290 https://doi.org/10.1186/s12883-020-01872-4 RESEARCH ARTICLE Open Access KIF1A-related autosomal dominant spastic paraplegias (SPG30) in Russian families G. E. Rudenskaya1 , V. A. Kadnikova1* , O. P. Ryzhkova1 , L. A. Bessonova1, E. L. Dadali1 , D. S. Guseva1 , T. V. Markova1 , D. N. Khmelkova2 and A. V. Polyakov1 Abstract Background: Spastic paraplegia type 30 (SPG30) caused by KIF1A mutations was first reported in 2011 and was initially considered a very rare autosomal recessive (AR) form. In the last years, thanks to the development of massive parallel sequencing, SPG30 proved to be a rather common autosomal dominant (AD) form of familial or sporadic spastic paraplegia (SPG),, with a wide range of phenotypes: pure and complicated. The aim of our study is to detect AD SPG30 cases and to examine their molecular and clinical characteristics for the first time in the Russian population. Methods: Clinical, genealogical and molecular methods were used. Molecular methods included massive parallel sequencing (MPS) of custom panel ‘spastic paraplegias’ with 62 target genes complemented by familial Sanger sequencing. One case was detected by the whole -exome sequencing. Results: AD SPG30 was detected in 10 unrelated families, making it the 3rd (8.4%) most common SPG form in the cohort of 118 families. No AR SPG30 cases were detected. In total, 9 heterozygous KIF1A mutations were detected, with 4 novel and 5 known mutations. All the mutations were located within KIF1A motor domain. Six cases had pure phenotypes, of which 5 were familial, where 2 familial cases demonstrated incomplete penetrance, early onset and slow relatively benign SPG course. -
Dimerization of Mammalian Kinesin-3 Motors Results in Superprocessive Motion
Dimerization of mammalian kinesin-3 motors results in superprocessive motion Virupakshi Soppinaa,1, Stephen R. Norrisa,b, Aslan S. Dizajia, Matt Kortusa, Sarah Veatchb, Michelle Peckhamc, and Kristen J. Verheya,1 aDepartment of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, MI 48109; bDepartment of Biophysics, University of Michigan, Ann Arbor, MI 48109; and cSchool of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, United Kingdom Edited by J. Richard McIntosh, University of Colorado, Boulder, CO, and approved March 7, 2014 (received for review January 15, 2014) The kinesin-3 family is one of the largest among the kinesin Defects in kinesin-3 transport have been implicated in a wide superfamily and its members play important roles in a wide range variety of neurodegenerative, developmental, and cancer dis- of cellular transport activities, yet the molecular mechanisms of eases (22). However, a mechanistic understanding of this im- kinesin-3 regulation and cargo transport are largely unknown. portant class of cellular transporters is currently limited. We performed a comprehensive analysis of mammalian kinesin-3 To date, mechanistic studies have focused on truncated ver- motors from three different subfamilies (KIF1, KIF13, and KIF16). sions of mammalian KIF1A and its homolog CeUNC-104, and Using Forster resonance energy transfer microscopy in live cells, these studies have yielded contradictory results (23). For exam- we show for the first time to our knowledge that KIF16B motors ple, murine KIF1A has been proposed to function as a monomer undergo cargo-mediated dimerization. The molecular mechanisms that diffuses along the microtubule surface or as a processive dimer.