Growth Cones Are Actively Influenced by Substrate-Bound Adhesion Molecules
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Identifying MMP14 and COL12A1 As a Potential Combination of Prognostic Biomarkers in Pancreatic Ductal Adenocarcinoma Using Integrated Bioinformatics Analysis
Identifying MMP14 and COL12A1 as a potential combination of prognostic biomarkers in pancreatic ductal adenocarcinoma using integrated bioinformatics analysis Jingyi Ding1, Yanxi Liu2 and Yu Lai3 1 Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China 2 University of California, Los Angeles, Los Angeles, CA, United States of America 3 School of Basic Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, China ABSTRACT Background. Pancreatic ductal adenocarcinoma (PDAC) is a fatal malignant neo- plasm. It is necessary to improve the understanding of the underlying molecular mechanisms and identify the key genes and signaling pathways involved in PDAC. Methods. The microarray datasets GSE28735, GSE62165, and GSE91035 were down- loaded from the Gene Expression Omnibus. Differentially expressed genes (DEGs) were identified by integrated bioinformatics analysis, including protein–protein interaction (PPI) network, Gene Ontology (GO) enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The PPI network was established using the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape software. GO functional annotation and KEGG pathway analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery. Hub genes were validated via the Gene Expression Profiling Interactive Analysis tool (GEPIA) and the Human Protein Atlas (HPA) website. Results. A total of 263 DEGs (167 upregulated and 96 downregulated) were common to the three datasets. We used STRING and Cytoscape software to establish the PPI Submitted 25 August 2020 network and then identified key modules. From the PPI network, 225 nodes and 803 Accepted 2 November 2020 edges were selected. The most significant module, which comprised 11 DEGs, was Published 23 November 2020 identified using the Molecular Complex Detection plugin. -
The Therapeutic Effects of Rho-ROCK Inhibitors on CNS Disorders
REVIEW The therapeutic effects of Rho-ROCK inhibitors on CNS disorders Takekazu Kubo1 Abstract: Rho-kinase (ROCK) is a serine/threonine kinase and one of the major downstream Atsushi Yamaguchi1 effectors of the small GTPase Rho. The Rho-ROCK pathway is involved in many aspects of Nobuyoshi Iwata2 neuronal functions including neurite outgrowth and retraction. The Rho-ROCK pathway becomes Toshihide Yamashita1,3 an attractive target for the development of drugs for treating central nervous system (CNS) dis- orders, since it has been recently revealed that this pathway is closely related to the pathogenesis 1Department of Neurobiology, Graduate School of Medicine, Chiba of several CNS disorders such as spinal cord injuries, stroke, and Alzheimer’s disease (AD). In University, 1-8-1 Inohana, Chuo-ku, the adult CNS, injured axons regenerate poorly due to the presence of myelin-associated axonal 2 Chiba 260-8670, Japan; Information growth inhibitors such as myelin-associated glycoprotein (MAG), Nogo, oligodendrocyte- Institute for Medical Research Ltd.; 3Department of Molecular myelin glycoprotein (OMgp), and the recently identifi ed repulsive guidance molecule (RGM). Neuroscience, Graduate School The effects of these inhibitors are reversed by blockade of the Rho-ROCK pathway in vitro, of Medicine, Osaka University 2-2 and the inhibition of this pathway promotes axonal regeneration and functional recovery in the Yamadaoka, Suita, Osaka 565-0871, Japan injured CNS in vivo. In addition, the therapeutic effects of the Rho-ROCK inhibitors have been demonstrated in animal models of stroke. In this review, we summarize the involvement of the Rho-ROCK pathway in CNS disorders such as spinal cord injuries, stroke, and AD and also discuss the potential of Rho-ROCK inhibitors in the treatment of human CNS disorders. -
CHL1 and Nrcam Are Primarily Expressed in Low Grade Pediatric
Open Med. 2019; 14: 920-927 Research Article Robin Wachowiak, Steffi Mayer, Anne Suttkus, Illya Martynov, Martin Lacher, Nathaniel Melling, Jakob R. Izbicki, Michael Tachezy CHL1 and NrCAM are primarily expressed in low grade pediatric neuroblastoma https://doi.org/10.1515/med-2019-0109 Keywords: CHL1; NrCAM; Neuroblastoma; Immunohisto- received November 7, 2018; accepted October 19, 2019 chemistry; Tumor markers; Neuropathology Abstract: Background. Neural cell adhesion molecules like close homolog of L1 protein (CHL1) and neuronal glia related cell adhesion molecule (NrCAM) play an impor- tant role in development and regeneration of the central 1 Introduction nervous system. However, they are also associated with Neuroblastoma is an embryonic malignancy deriving cancerogenesis and progression in adult malignancies, from neural crest cells that undergo rapid differentia- thus gain increasing importance in cancer research. We tion during fetal development. As the transition from therefore studied the expression of CHL1 and NrCAM normal to malignant tissue can occur in multiple steps, according to the course of disease in children with neu- its phenotype is highly heterogeneous [1]. Although pro- roblastoma. gress has been made in the treatment of neuroblastoma, Methods. CHL1 and NrCAM expression levels were histo- the outcome of children at high risk remains poor with a logically assessed by tissue microarrays from surgically long-term survival as low as 50 % [2]. Different parameters resected neuroblastoma specimens of 56 children. Expres- such as age, stage and chromosomal aberrations have an sion of both markers was correlated to demographics as impact on prognosis. Still, there is an ongoing need for well as clinical data including metastatic dissemination tumor markers, which allow a better determination of the and survival. -
Broad and Thematic Remodeling of the Surface Glycoproteome on Isogenic
bioRxiv preprint doi: https://doi.org/10.1101/808139; this version posted October 17, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Broad and thematic remodeling of the surface glycoproteome on isogenic cells transformed with driving proliferative oncogenes Kevin K. Leung1,5, Gary M. Wilson2,5, Lisa L. Kirkemo1, Nicholas M. Riley2,4, Joshua J. Coon2,3, James A. Wells1* 1Department of Pharmaceutical Chemistry, UCSF, San Francisco, CA, USA Departments of Chemistry2 and Biomolecular Chemistry3, University of Wisconsin- Madison, Madison, WI, 53706, USA 4Present address Department of Chemistry, Stanford University, Stanford, CA, 94305, USA 5These authors contributed equally *To whom correspondence should be addressed bioRxiv preprint doi: https://doi.org/10.1101/808139; this version posted October 17, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Abstract: The cell surface proteome, the surfaceome, is the interface for engaging the extracellular space in normal and cancer cells. Here We apply quantitative proteomics of N-linked glycoproteins to reveal how a collection of some 700 surface proteins is dramatically remodeled in an isogenic breast epithelial cell line stably expressing any of six of the most prominent proliferative oncogenes, including the receptor tyrosine kinases, EGFR and HER2, and downstream signaling partners such as KRAS, BRAF, MEK and AKT. -
Identification of Potential Biomarkers and Drugs for Papillary Thyroid Cancer Based on Gene Expression Profile Analysis
MOLECULAR MEDICINE REPORTS 14: 5041-5048, 2016 Identification of potential biomarkers and drugs for papillary thyroid cancer based on gene expression profile analysis TING QU1*, YAN-PING LI2*, XIAO-HONG LI1 and YAN CHEN1 Departments of 1Pharmacy and 2Endodontics, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150001, P.R. China Received September 17, 2015; Accepted September 29, 2016 DOI: 10.3892/mmr.2016.5855 Abstract. The present study aimed to systematically examine sition and responding to steroid hormone stimuli, respectively. the molecular mechanisms of papillary thyroid cancer (PTC), Ocriplasmin, β-mercaptoethanol and recombinant α 1-anti- and identify potential biomarkers and drugs for the treatment trypsin may be potential drugs for the treatment of PTC. of PTC. Two microarray data sets (GSE3467 and GSE3678), containing 16 PTC samples and 16 paired normal samples, Introduction were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were Thyroid cancer is one of the most common types of endocrine identified using the Linear Models for Microarray Analysis malignancy, the incidence rate of which has rapidly increased package. Subsequently, the common DEGs were screened for during previous years (1,2). It has been estimated that the functional and pathway enrichment analysis using the Database annual number of cases of thyroid cancer diagnosed in the for Annotation Visualization and Integrated Discovery. The USA and the associated mortality rate are 12.9/100,000 -
Self-Organized Cortical Map Formation by Guiding Connections
SELF-ORGANIZED CORTICAL MAP FORMATION BY GUIDING CONNECTIONS Stanley Y. M. Lam1, Bertram E. Shi1and Kwabena A. Boahen2 1Dept. of EEE, HKUST, {eelym,eebert}@ust.hk and 2Dept. of Bioengineering, UPenn, [email protected] ABSTRACT demonstrate that the system can start with random initial connec- tions and gradually evolve the connections over time to replicate We describe an algorithm for self-organizing connections from a the topography of the source array in the target array. source array to a target array of neurons that is inspired by neural This paper has three goals. First, it demonstrates that this growth cone guidance. Each source neuron projects a Gaussian approach can lead to retinotopic maps that also exhibit other prop- pattern of connections to the target layer. Learning modifies the erties associated with the primary visual cortex, such as ocular pattern center location. The small number of parameters required dominance and orientation selectivity. Second, it establishes the to specify connectivity has enabled this algorithm's implementa- stability of this map formation process. Finally, it relates this tion in a neuromorphic silicon system. We demonstrate that this approach to previously proposed algorithms for map formation. algorithm can lead to topographic feature maps similar to those observed in the visual cortex, and characterize its operation as Section 2 of this paper introduces the learning algorithm. Section function maximization, which connects this approach with other 3 shows via simulation that this algorithm can lead to ocular dom- models of cortical map formation. inance and orientation maps similar to those observed in cortex. Section 4 analyzes the dynamics of learning, and shows that it evolves in such a way as to maximize an energy function. -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like, -
Human Brain Organoids Reveal Accelerated Development of Cortical Neuron Classes As a Shared Feature of Autism Risk Genes
bioRxiv preprint doi: https://doi.org/10.1101/2020.11.10.376509; this version posted November 12, 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. Human brain organoids reveal accelerated development of cortical neuron classes as a shared feature of autism risk genes Bruna Paulsen1,2,†, Silvia Velasco1,2,†,#, Amanda J. Kedaigle1,2,3,†, Martina Pigoni1,2,†, Giorgia Quadrato4,5 Anthony Deo2,6,7,8, Xian Adiconis2,3, Ana Uzquiano1,2, Kwanho Kim1,2,3, Sean K. Simmons2,3, Kalliopi Tsafou2, Alex Albanese9, Rafaela Sartore1,2, Catherine Abbate1,2, Ashley Tucewicz1,2, Samantha Smith1,2, Kwanghun Chung9,10,11,12, Kasper Lage2,13, Aviv Regev3,14, Joshua Z. Levin2,3, Paola Arlotta1,2,# † These authors contributed equally to the work # Correspondence should be addressed to [email protected] and [email protected] 1 Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA 2 Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA 3 Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA 4 Department of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA; 5 Eli and Edythe Broad CIRM Center for Regenerative Medicine and Stem Cell Research at the University of Southern California, Los Angeles, CA 90033, USA. 6 Department of Psychiatry, -
Pioneer Growth Cone Morphologies Reveal Proximal Increases in Substrate Affinity Within Leg Segments of Grasshopper Embryos
The Journal of Neuroscience February 1986, 6(2): 364-379 Pioneer Growth Cone Morphologies Reveal Proximal Increases in Substrate Affinity Within Leg Segments of Grasshopper Embryos Michael Gaudy* and David Bentley-f *Biophysics Group and tDepartment of Zoology, University of California, Berkeley, California 94720 We have compared the morphologies of approximately 5000 limb segment boundaries (Bentley and Caudy, 1983b) and antibody-labeled afferent pioneer growth cones fixed at various guidepost cells. The dominant mechanism appears to be the stages of growth along their characteristic path over the epithe- guidepost cells, a set of nonadjacent, axonless cell bodies of lium in the legs of grasshopper embryos, and have used growth immature neurons (Bentley and Caudy, 1983a, b; Bentley and cone morphology as an indicator of differences in the affinity of Keshishian, 1982a, b; Ho and Goodman, 1982; Keshishian and the epithelial substrate for pioneer growth cones in viva. Growth Bentley, 1983a-c; Taghert et al., 1982). Ablation of the most cone morphologies differ markedly between different locations proximal guidepost cell pair has been shown to result in lack of in limb buds, and also in the same location in limbs at different normal growth (Bentley and Caudy, 1983a, b). stages of differentiation. Growth cones characteristically extend Additional mechanisms apparently guide the Ti 1 growth cones branches and lamellae circumferentially along segment bound- proximally before they contact any of the above cues (Bentley aries, and filopodia and lamellae are retained (or extended) and Caudy, 1983b). One possible external cue is an adhesion longer there. Where they contact a relatively well-differentiated gradient on the epithelial substrate over which the pioneer growth segment boundary, the growth cones also abruptly reorient cir- cones navigate (Bentley and Caudy, 1983b; Berlot and Good- cumferentially. -
Identification of Common Gene Networks Responsive To
Cancer Gene Therapy (2014) 21, 542–548 © 2014 Nature America, Inc. All rights reserved 0929-1903/14 www.nature.com/cgt ORIGINAL ARTICLE Identification of common gene networks responsive to radiotherapy in human cancer cells D-L Hou1, L Chen2, B Liu1, L-N Song1 and T Fang1 Identification of the genes that are differentially expressed between radiosensitive and radioresistant cancers by global gene analysis may help to elucidate the mechanisms underlying tumor radioresistance and improve the efficacy of radiotherapy. An integrated analysis was conducted using publicly available GEO datasets to detect differentially expressed genes (DEGs) between cancer cells exhibiting radioresistance and cancer cells exhibiting radiosensitivity. Gene Ontology (GO) enrichment analyses, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and protein–protein interaction (PPI) networks analysis were also performed. Five GEO datasets including 16 samples of radiosensitive cancers and radioresistant cancers were obtained. A total of 688 DEGs across these studies were identified, of which 374 were upregulated and 314 were downregulated in radioresistant cancer cell. The most significantly enriched GO terms were regulation of transcription, DNA-dependent (GO: 0006355, P = 7.00E-09) for biological processes, while those for molecular functions was protein binding (GO: 0005515, P = 1.01E-28), and those for cellular component was cytoplasm (GO: 0005737, P = 2.81E-26). The most significantly enriched pathway in our KEGG analysis was Pathways in cancer (P = 4.20E-07). PPI network analysis showed that IFIH1 (Degree = 33) was selected as the most significant hub protein. This integrated analysis may help to predict responses to radiotherapy and may also provide insights into the development of individualized therapies and novel therapeutic targets. -
Ca -Dependent Regulation of Rho Gtpases Triggers Turning of Nerve Growth Cones
2338 • The Journal of Neuroscience, March 2, 2005 • 25(9):2338–2347 Development/Plasticity/Repair Ca2ϩ-Dependent Regulation of Rho GTPases Triggers Turning of Nerve Growth Cones Ming Jin,1,2* Chen-bing Guan,1,2* Yun-ai Jiang,1,2* Gang Chen,1,2 Chun-tao Zhao,1,2 Kai Cui,1,2 Yuan-quan Song,1 Chien-ping Wu,1 Mu-ming Poo,1,3 and Xiao-bing Yuan1 1Institute of Neuroscience, Shanghai Institutes of Biological Sciences, Chinese Academy of Sciences, and 2Graduate School of the Chinese Academy of Sciences, Shanghai 200031, China, and 3Division of Neurobiology, Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720- 3200 Cytoplasmic Ca 2ϩ elevation and changes in Rho GTPase activity are both known to mediate axon guidance by extracellular factors, but the causal relationship between these two events has been unclear. Here we show that direct elevation of cytoplasmic Ca 2ϩ by extracel- lular application of a low concentration of ryanodine, which activated Ca 2ϩ release from intracellular stores, upregulated Cdc42/Rac, but downregulated RhoA, in cultured cerebellar granule cells and human embryonic kidney 293T cells. Chemoattractive turning of the growth cone triggered by a gradient of ryanodine was blocked by overexpression of mutant forms of Cdc42 but not of RhoA in Xenopus spinal cord neurons. Furthermore, Ca 2ϩ-induced GTPase activity correlated with activation of protein kinase C and required a basal activity of Ca 2ϩ/calmodulin-dependent protein kinase II. Thus, Rho GTPases may mediate axon guidance by linking upstream Ca 2ϩ signals triggered by guidance factors to downstream cytoskeletal rearrangements. -
Bioinformatics Analysis to Screen Key Genes in Papillary Thyroid Carcinoma
ONCOLOGY LETTERS 19: 195-204, 2020 Bioinformatics analysis to screen key genes in papillary thyroid carcinoma YUANHU LIU1*, SHUWEI GAO2*, YAQIONG JIN2, YERAN YANG2, JUN TAI1, SHENGCAI WANG1, HUI YANG2, PING CHU2, SHUJING HAN2, JIE LU2, XIN NI1,2, YONGBO YU2 and YONGLI GUO2 1Department of Otolaryngology, Head and Neck Surgery, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health; 2Beijing Key Laboratory for Pediatric Diseases of Otolaryngology, Head and Neck Surgery, MOE Key Laboratory of Major Diseases in Children, Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, P.R. China Received April 22, 2019; Accepted September 24, 2019 DOI: 10.3892/ol.2019.11100 Abstract. Papillary thyroid carcinoma (PTC) is the most verifying their potential for clinical diagnosis. Taken together, common type of thyroid carcinoma, and its incidence has the findings of the present study suggest that these genes and been on the increase in recent years. However, the molecular related pathways are involved in key events of PTC progression mechanism of PTC is unclear and misdiagnosis remains a and facilitate the identification of prognostic biomarkers. major issue. Therefore, the present study aimed to investigate this mechanism, and to identify key prognostic biomarkers. Introduction Integrated analysis was used to explore differentially expressed genes (DEGs) between PTC and healthy thyroid tissue. To Thyroid carcinoma is the most common malignancy of investigate the functions and pathways associated with DEGs, the head and neck, and accounts for 91.5% of all endocrine Gene Ontology, pathway and protein-protein interaction (PPI) malignancies (1).