Predicting Environmental Chemical Factors Associated with Disease-Related Gene Expression Data
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Early Diagnosis of Colorectal Cancer Via Plasma Proteomic Analysis of CRC and Advanced Adenomatous Polyp
Gastroenterology and Hepatology From Bed to Bench. ORIGINAL ARTICLE ©2019 RIGLD, Research Institute for Gastroenterology and Liver Diseases Early diagnosis of colorectal cancer via plasma proteomic analysis of CRC and advanced adenomatous polyp Setareh Fayazfar1, Hakimeh Zali2, Afsaneh Arefi Oskouie1, Hamid Asadzadeh Aghdaei3, Mostafa Rezaei Tavirani4, Ehsan Nazemalhosseini Mojarad5 1Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran 2School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran 3Basic and Molecular Epidemiology of Gastroenterology Disorders Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran 4Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran 5Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran ABSTRACT Aim: This paper aimed to identify new candidate biomarkers in blood for early diagnosis of CRC. Background: Colorectal cancer (CRC) is the third most widespread malignancies increasing globally. The high mortality rate associated with colorectal cancer is due to the delayed diagnosis in an advanced stage while the metastasis has occurred. For better clinical management and subsequently to reduce mortality of CRC, early detection biomarkers are in high demand. -
Exploring the Relationship Between Gut Microbiota and Major Depressive Disorders
E3S Web of Conferences 271, 03055 (2021) https://doi.org/10.1051/e3sconf/202127103055 ICEPE 2021 Exploring the Relationship between Gut Microbiota and Major Depressive Disorders Catherine Tian1 1Shanghai American School, Shanghai, China Abstract. Major Depressive Disorder (MDD) is a psychiatric disorder accompanied with a high rate of suicide, morbidity and mortality. With the symptom of an increasing or decreasing appetite, there is a possibility that MDD may have certain connections with gut microbiota, the colonies of microbes which reside in the human digestive system. In recent years, more and more studies started to demonstrate the links between MDD and gut microbiota from animal disease models and human metabolism studies. However, this relationship is still largely understudied, but it is very innovative since functional dissection of this relationship would furnish a new train of thought for more effective treatment of MDD. In this study, by using multiple genetic analytic tools including Allen Brain Atlas, genetic function analytical tools, and MicrobiomeAnalyst, I explored the genes that shows both expression in the brain and the digestive system to affirm that there is a connection between gut microbiota and the MDD. My approach finally identified 7 MDD genes likely to be associated with gut microbiota, implicating 3 molecular pathways: (1) Wnt Signaling, (2) citric acid cycle in the aerobic respiration, and (3) extracellular exosome signaling. These findings may shed light on new directions to understand the mechanism of MDD, potentially facilitating the development of probiotics for better psychiatric disorder treatment. 1 Introduction 1.1 Major Depressive Disorder Major Depressive Disorder (MDD) is a mood disorder that will affect the mood, behavior and other physical parts. -
High-Throughput Bioinformatics Approaches to Understand Gene Expression Regulation in Head and Neck Tumors
High-throughput bioinformatics approaches to understand gene expression regulation in head and neck tumors by Yanxiao Zhang A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Bioinformatics) in The University of Michigan 2016 Doctoral Committee: Associate Professor Maureen A. Sartor, Chair Professor Thomas E. Carey Assistant Professor Hui Jiang Professor Ronald J. Koenig Associate Professor Laura M. Rozek Professor Kerby A. Shedden c Yanxiao Zhang 2016 All Rights Reserved I dedicate this thesis to my family. For their unfailing love, understanding and support. ii ACKNOWLEDGEMENTS I would like to express my gratitude to Dr. Maureen Sartor for her guidance in my research and career development. She is a great mentor. She patiently taught me when I started new in this field, granted me freedom to explore and helped me out when I got lost. Her dedication to work, enthusiasm in teaching, mentoring and communicating science have inspired me to feel the excite- ment of research beyond novel scientific discoveries. I’m also grateful to have an interdisciplinary committee. Their feedback on my research progress and presentation skills is very valuable. In particular, I would like to thank Dr. Thomas Carey and Dr. Laura Rozek for insightful discussions on the biology of head and neck cancers and human papillomavirus, Dr. Ronald Koenig for expert knowledge on thyroid cancers, Dr. Hui Jiang and Dr. Kerby Shedden for feedback on the statistics part of my thesis. I would like to thank all the past and current members of Sartor lab for making the lab such a lovely place to stay and work in. -
Goat Anti-Ymer / CCDC50 Antibody Size: 100Μg Specific Antibody in 200Μl
EB06551 - Goat Anti-Ymer / CCDC50 Antibody Size: 100µg specific antibody in 200µl Target Protein Principal Names: Ymer protein, coiled-coil domain containing 50, C3orf6, YMER, C3orf6, chromosome 3 open reading frame 6 UK Office Official Symbol: CCDC50 Accession Number(s): NP_848018.1; NP_777568.1 Everest Biotech Ltd Human GeneID(s): 152137 Cherwell Innovation Centre Important Comments: This antibody is expected to recognise both reported isoforms of 77 Heyford Park human Ymer protein. Upper Heyford Oxfordshire Immunogen OX25 5HD Peptide with sequence CFSKSESSHKGFHYK, from the internal region of the protein UK sequence according to NP_848018.1; NP_777568.1. Enquiries: Please note the peptide is available for sale. [email protected] Sales: Purification and Storage [email protected] Purified from goat serum by ammonium sulphate precipitation followed by antigen affinity Tech support: chromatography using the immunizing peptide. [email protected] Supplied at 0.5 mg/ml in Tris saline, 0.02% sodium azide, pH7.3 with 0.5% bovine serum albumin. Tel: +44 (0)1869 238326 Aliquot and store at -20°C. Minimize freezing and thawing. Fax: +44 (0)1869 238327 Applications Tested US Office Peptide ELISA: antibody detection limit dilution 1:32000. Everest Biotech c/o Abcore Western blot: Preliminary experiments gave an approx 18kDa band in Human Brain 405 Maple Street, Suite A106 lysates after 1µg/ml antibody staining. Please note that currently we cannot find an Ramona, explanation in the literature for the band we observe given the calculated size of 56.3kDa CA 92065 according to NP_848018.1 and 35.8kDa according to NP_777568.1. The 18kDa band was USA successfully blocked by incubation with the immunizing peptide. -
Gene Mapping and Medical Genetics
J Med Genet: first published as 10.1136/jmg.24.8.451 on 1 August 1987. Downloaded from Gene mapping and medical genetics Journal of Medical Genetics 1987, 24, 451-456 Molecular genetics of human chromosome 16 GRANT R SUTHERLAND*, STEPHEN REEDERSt, VALENTINE J HYLAND*, DAVID F CALLEN*, ANTONIO FRATINI*, AND JOHN C MULLEY* From *the Cytogenetics Unit, Adelaide Children's Hospital, North Adelaide, South Australia 5006; and tUniversity of Oxford, Nuffield Department of Clinical Medicine, John Radcliffe Hospital, Headington, Oxford OX3 9DU. SUMMARY The major diseases mapped to chromosome 16 are adult polycystic kidney disease and those resulting from mutations in the a globin complex. There are at least six other less important genetic diseases which map to this chromosome. The adenine phosphoribosyltransferase gene allows for selection of chromosome 16 in somatic cell hybrids and a hybrid panel is available which segments the chromosome into six regions to facilitate gene mapping. Genes which have been mapped to this chromosome or which have had their location redefined since HGM8 include APRT, TAT, MT, HBA, PKDI, CTRB, PGP, HAGH, HP, PKCB, and at least 19 cloned DNA sequences. There are RFLPs at 13 loci which have been regionally mapped and can be used for linkage studies. Chromosome 16 is not one of the more extensively have been cloned and mapped to this chromosome. mapped human autosomes. However, it has a Brief mention will be made of a hybrid cell panel http://jmg.bmj.com/ number of features which make it attractive to the which allows for an efficient regional localisation of gene mapper. -
The T(6;16)(P21;Q22) Chromosome Translocation in the Lncap Prostate Carcinoma Cell Line Results in a Tpc/Hpr Fusion Gene'
CANCERRESEARCH56.728-732.February15. 9961 Advances in Brief The t(6;16)(p21;q22) Chromosome Translocation in the LNCaP Prostate Carcinoma Cell Line Results in a tpc/hpr Fusion Gene' Maria Luisa Veronese, Florencia Bulinch, Massimo Negrini, and Carlo M. Croce2 Jefferson Cancer Center, Jefferson Cancer Institute and Department of Microbiology and Immunology, Thomas Jefferson University, Philadelphia, Pennsylvania 19107 Abstract level. We have found that the translocation results in fusion of the hpr gene on chromosome 16 to the tpc gene, a novel gene coding for a Very little is known about the molecular and genetic mechanisms protein similar to nbosomal protein 510. involved in prostate cancer.Previousstudieshaveshownfrequent lossof heterozygosity(40%)at chromosomalregions8p, lOq,and 16q,suggesting thepresenceoftumorsuppressorgenesintheseregions.TheLNCaP cell Materials and Methods line, establishedfrom a metastaticlesionof human prostatic adenocarci Rodent-Human Hybrids. The hybrids seriesA9LN were obtainedfrom noma,carries a t(6;16)(p21;q22)translocation.To determinewhether this translocation involved genesimportant in the processof malignant trans thefusionof thehumanprostatecarcinomacellline LNCaPandthemouseA9 formation, weclonedand sequencedthet(6;16) breakpoint ofthis cell line. cell line as previously described (15). PCR analysis with primers from both the Sequenceanalysisshowedthat the breakpoint is within the haptoglobin shortandlongarmsof chromosome16wascarriedout in 1 X PCRbufferwith geneclusteron chromosome16,and that, on chromosome6,the break MgCI2 (Boehringer Mannheim) with 100 ng template DNA, 100 ng each of occurs within a novel gene,tpc, similar to the prokaryotic SlO ribosomal forward and reverseprimer, 250 @Mdeoxynucleotidetriphosphates(Perkin protein gene. The translocation results in the production of a fusion Elmer/Cetus), and 0.5 units of Taq DNA polymerase (Boehringer Mannheim) transcript, tpc/hpr. -
Nº Ref Uniprot Proteína Péptidos Identificados Por MS/MS 1 P01024
Document downloaded from http://www.elsevier.es, day 26/09/2021. This copy is for personal use. Any transmission of this document by any media or format is strictly prohibited. Nº Ref Uniprot Proteína Péptidos identificados 1 P01024 CO3_HUMAN Complement C3 OS=Homo sapiens GN=C3 PE=1 SV=2 por 162MS/MS 2 P02751 FINC_HUMAN Fibronectin OS=Homo sapiens GN=FN1 PE=1 SV=4 131 3 P01023 A2MG_HUMAN Alpha-2-macroglobulin OS=Homo sapiens GN=A2M PE=1 SV=3 128 4 P0C0L4 CO4A_HUMAN Complement C4-A OS=Homo sapiens GN=C4A PE=1 SV=1 95 5 P04275 VWF_HUMAN von Willebrand factor OS=Homo sapiens GN=VWF PE=1 SV=4 81 6 P02675 FIBB_HUMAN Fibrinogen beta chain OS=Homo sapiens GN=FGB PE=1 SV=2 78 7 P01031 CO5_HUMAN Complement C5 OS=Homo sapiens GN=C5 PE=1 SV=4 66 8 P02768 ALBU_HUMAN Serum albumin OS=Homo sapiens GN=ALB PE=1 SV=2 66 9 P00450 CERU_HUMAN Ceruloplasmin OS=Homo sapiens GN=CP PE=1 SV=1 64 10 P02671 FIBA_HUMAN Fibrinogen alpha chain OS=Homo sapiens GN=FGA PE=1 SV=2 58 11 P08603 CFAH_HUMAN Complement factor H OS=Homo sapiens GN=CFH PE=1 SV=4 56 12 P02787 TRFE_HUMAN Serotransferrin OS=Homo sapiens GN=TF PE=1 SV=3 54 13 P00747 PLMN_HUMAN Plasminogen OS=Homo sapiens GN=PLG PE=1 SV=2 48 14 P02679 FIBG_HUMAN Fibrinogen gamma chain OS=Homo sapiens GN=FGG PE=1 SV=3 47 15 P01871 IGHM_HUMAN Ig mu chain C region OS=Homo sapiens GN=IGHM PE=1 SV=3 41 16 P04003 C4BPA_HUMAN C4b-binding protein alpha chain OS=Homo sapiens GN=C4BPA PE=1 SV=2 37 17 Q9Y6R7 FCGBP_HUMAN IgGFc-binding protein OS=Homo sapiens GN=FCGBP PE=1 SV=3 30 18 O43866 CD5L_HUMAN CD5 antigen-like OS=Homo -
A Genome-Wide in Vitro Bacterial-Infection Screen Reveals Human Variation in the Host Response Associated with Inflammatory Disease
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector ARTICLE A Genome-wide In Vitro Bacterial-Infection Screen Reveals Human Variation in the Host Response Associated with Inflammatory Disease Dennis C. Ko,1 Kajal P. Shukla,1 Christine Fong,1 Michael Wasnick,1 Mitchell J. Brittnacher,1 Mark M. Wurfel,2 Tarah D. Holden,2 Grant E. O’Keefe,5 Brian Van Yserloo,2 Joshua M. Akey,3 and Samuel I. Miller1,2,3,4,* Recent progress in cataloguing common genetic variation has made possible genome-wide studies that are beginning to elucidate the causes and consequences of our genetic differences. Approaches that provide a mechanistic understanding of how genetic variants func- tion to alter disease susceptibility and why they were substrates of natural selection would complement other approaches to human- genome analysis. Here we use a novel cell-based screen of bacterial infection to identify human variation in Salmonella-induced cell death. A loss-of-function allele of CARD8, a reported inhibitor of the proinflammatory protease caspase-1, was associated with increased cell death in vitro (p ¼ 0.013). The validity of this association was demonstrated through overexpression of alternative alleles and RNA interference in cells of varying genotype. Comparison of mammalian CARD8 orthologs and examination of variation among different human populations suggest that the increase in infectious-disease burden associated with larger animal groups (i.e., herds and colonies), and possibly human population expansion, may have naturally selected for loss of CARD8. We also find that the loss-of-function CARD8 allele shows a modest association with an increased risk of systemic inflammatory response syndrome in a small study (p ¼ 0.05). -
Identification of Novel Diagnostic Biomarkers for Thyroid Carcinoma
www.impactjournals.com/oncotarget/ Oncotarget, 2017, Vol. 8, (No. 67), pp: 111551-111566 Research Paper Identification of novel diagnostic biomarkers for thyroid carcinoma Xiliang Wang1,2, Qing Zhang1, Zhiming Cai1, Yifan Dai3 and Lisha Mou1 1Shenzhen Xenotransplantation Medical Engineering Research and Development Center, Institute of Translational Medicine, Shenzhen Second People's Hospital, First Affiliated Hospital of Shenzhen University, Shenzhen 518035, China 2Department of Biochemistry in Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China 3Jiangsu Key Laboratory of Xenotransplantation, Nanjing Medical University, Nanjing 210029, China Correspondence to: Lisha Mou, email: [email protected] Keywords: thyroid carcinoma; bioinformatics; dysregulation network; biomarker Received: June 27, 2017 Accepted: November 19, 2017 Published: December 04, 2017 Copyright: Wang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT Thyroid carcinoma (THCA) is the most universal endocrine malignancy worldwide. Unfortunately, a limited number of large-scale analyses have been performed to identify biomarkers for THCA. Here, we conducted a meta-analysis using 505 THCA patients and 59 normal controls from The Cancer Genome Atlas. After identifying differentially expressed long non-coding RNA (lncRNA) and protein coding genes (PCG), we found vast difference in various lncRNA-PCG co-expressed pairs in THCA. A dysregulation network with scale-free topology was constructed. Four molecules (LA16c-380H5.2, RP11-203J24.8, MLF1 and SDC4) could potentially serve as diagnostic biomarkers of THCA with high sensitivity and specificity. -
Supplementary Tables S1-S3
Supplementary Table S1: Real time RT-PCR primers COX-2 Forward 5’- CCACTTCAAGGGAGTCTGGA -3’ Reverse 5’- AAGGGCCCTGGTGTAGTAGG -3’ Wnt5a Forward 5’- TGAATAACCCTGTTCAGATGTCA -3’ Reverse 5’- TGTACTGCATGTGGTCCTGA -3’ Spp1 Forward 5'- GACCCATCTCAGAAGCAGAA -3' Reverse 5'- TTCGTCAGATTCATCCGAGT -3' CUGBP2 Forward 5’- ATGCAACAGCTCAACACTGC -3’ Reverse 5’- CAGCGTTGCCAGATTCTGTA -3’ Supplementary Table S2: Genes synergistically regulated by oncogenic Ras and TGF-β AU-rich probe_id Gene Name Gene Symbol element Fold change RasV12 + TGF-β RasV12 TGF-β 1368519_at serine (or cysteine) peptidase inhibitor, clade E, member 1 Serpine1 ARE 42.22 5.53 75.28 1373000_at sushi-repeat-containing protein, X-linked 2 (predicted) Srpx2 19.24 25.59 73.63 1383486_at Transcribed locus --- ARE 5.93 27.94 52.85 1367581_a_at secreted phosphoprotein 1 Spp1 2.46 19.28 49.76 1368359_a_at VGF nerve growth factor inducible Vgf 3.11 4.61 48.10 1392618_at Transcribed locus --- ARE 3.48 24.30 45.76 1398302_at prolactin-like protein F Prlpf ARE 1.39 3.29 45.23 1392264_s_at serine (or cysteine) peptidase inhibitor, clade E, member 1 Serpine1 ARE 24.92 3.67 40.09 1391022_at laminin, beta 3 Lamb3 2.13 3.31 38.15 1384605_at Transcribed locus --- 2.94 14.57 37.91 1367973_at chemokine (C-C motif) ligand 2 Ccl2 ARE 5.47 17.28 37.90 1369249_at progressive ankylosis homolog (mouse) Ank ARE 3.12 8.33 33.58 1398479_at ryanodine receptor 3 Ryr3 ARE 1.42 9.28 29.65 1371194_at tumor necrosis factor alpha induced protein 6 Tnfaip6 ARE 2.95 7.90 29.24 1386344_at Progressive ankylosis homolog (mouse) -
Download Ppis for Each Single Seed, Thus Obtaining Each Seed’S Interactome (Ferrari Et Al., 2018)
bioRxiv preprint doi: https://doi.org/10.1101/2021.01.14.425874; this version posted January 16, 2021. 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 4.0 International license. Integrating protein networks and machine learning for disease stratification in the Hereditary Spastic Paraplegias Nikoleta Vavouraki1,2, James E. Tomkins1, Eleanna Kara3, Henry Houlden3, John Hardy4, Marcus J. Tindall2,5, Patrick A. Lewis1,4,6, Claudia Manzoni1,7* Author Affiliations 1: Department of Pharmacy, University of Reading, Reading, RG6 6AH, United Kingdom 2: Department of Mathematics and Statistics, University of Reading, Reading, RG6 6AH, United Kingdom 3: Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, WC1N 3BG, United Kingdom 4: Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, WC1N 3BG, United Kingdom 5: Institute of Cardiovascular and Metabolic Research, University of Reading, Reading, RG6 6AS, United Kingdom 6: Department of Comparative Biomedical Sciences, Royal Veterinary College, London, NW1 0TU, United Kingdom 7: School of Pharmacy, University College London, London, WC1N 1AX, United Kingdom *Corresponding author: [email protected] Abstract The Hereditary Spastic Paraplegias are a group of neurodegenerative diseases characterized by spasticity and weakness in the lower body. Despite the identification of causative mutations in over 70 genes, the molecular aetiology remains unclear. Due to the combination of genetic diversity and variable clinical presentation, the Hereditary Spastic Paraplegias are a strong candidate for protein- protein interaction network analysis as a tool to understand disease mechanism(s) and to aid functional stratification of phenotypes. -
Bolton Et Al. Supplement
Bolton_et_al._Supplement SUPPLEMENTAL RESULTS AND DISCUSSION Some HPr-1AR ARE-containing Genes Are Unresponsive to Androgen Intracellular receptors specify complex patterns of gene expression that are cell and gene specific. For example, among the 62 androgen non-responsive genes in HPr-1AR that nevertheless bear AR-occupied intragenic AREs in those cells, seven are androgen regulated in LNCaP cells (DePrimo et al. 2002; Nelson et al. 2002). In general, it seems likely that many of these AR binding sites may confer androgen responses in different cellular contexts, reflecting, for example, requirements for additional coregulators to enable hormonal control. Thus, for this subset of genes, AR occupancy is not the primary determinant for AR regulation. Alternatively, some of these AR-occupied genes may be strongly expressed prior to androgen treatment, rendering their induction difficult to measure. However, our qPCR expression data do not support this alternative. ARBRs Function as AREs in Androgen-Mediated Transcriptional Regulation Interestingly, four of the 500-bp ARBRs identified near repressed ARGs produced activation rather than repression of luciferase expression when tested in reporter contexts, whereas three failed to confer androgen regulation in either direction (ECB and KRY, unpublished). Although we do not yet understand this regulatory “polarity reversal”, our result is similar to earlier findings in which “negative” glucocortoicoid response elements direct transcriptional activation in simple contexts (M. Cronin and KRY,