Transcriptome Analysis Identifies Novel Mechanisms Associated with the Antitumor Effect of Chitosan-Stabilized Selenium Nanopart
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Gene Expression Profiling Identifies Candidate Biomarkers for Active And
Lee et al. BMC Bioinformatics 2016, 17(Suppl 1):3 DOI 10.1186/s12859-015-0848-x PROCEEDINGS Open Access Gene expression profiling identifies candidate biomarkers for active and latent tuberculosis Shih-Wei Lee1,2†, Lawrence Shih-Hsin Wu3†, Guan-Mau Huang4, Kai-Yao Huang4, Tzong-Yi Lee4,5 and Julia Tzu-Ya Weng4,5* From The Fourteenth Asia Pacific Bioinformatics Conference (APBC 2016) San Francisco, CA, USA. 11 - 13 January 2016 Abstract Background: Tuberculosis (TB) is a serious infectious disease in that 90 % of those latently infected with Mycobacterium tuberculosis present no symptoms, but possess a 10 % lifetime chance of developing active TB. To prevent the spread of the disease, early diagnosis is crucial. However, current methods of detection require improvement in sensitivity, efficiency or specificity. In the present study, we conducted a microarray experiment, comparing the gene expression profiles in the peripheral blood mononuclear cells among individuals with active TB, latent infection, and healthy conditions in a Taiwanese population. Results: Bioinformatics analysis revealed that most of the differentially expressed genes belonged to immune responses, inflammation pathways, and cell cycle control. Subsequent RT-PCR validation identified four differentially expressed genes, NEMF, ASUN, DHX29, and PTPRC, as potential biomarkers for the detection of active and latent TB infections. Receiver operating characteristic analysis showed that the expression level of PTPRC may discriminate active TB patients from healthy individuals, while ASUN could differentiate between the latent state of TB infection and healthy condidtion. In contrast, DHX29 may be used to identify latently infected individuals among active TB patients or healthy individuals. To test the concept of using these biomarkers as diagnostic support, we constructed classification models using these candidate biomarkers and found the Naïve Bayes-based model built with ASUN, DHX29,and PTPRC to yield the best performance. -
Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model
Downloaded from http://www.jimmunol.org/ by guest on September 25, 2021 T + is online at: average * The Journal of Immunology , 34 of which you can access for free at: 2016; 197:1477-1488; Prepublished online 1 July from submission to initial decision 4 weeks from acceptance to publication 2016; doi: 10.4049/jimmunol.1600589 http://www.jimmunol.org/content/197/4/1477 Molecular Profile of Tumor-Specific CD8 Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. Waugh, Sonia M. Leach, Brandon L. Moore, Tullia C. Bruno, Jonathan D. Buhrman and Jill E. Slansky J Immunol cites 95 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html http://www.jimmunol.org/content/suppl/2016/07/01/jimmunol.160058 9.DCSupplemental This article http://www.jimmunol.org/content/197/4/1477.full#ref-list-1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material References Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 25, 2021. The Journal of Immunology Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. -
Unravelling the Cellular Origin and Clinical Prognostic Markers of Infant
Published Ahead of Print on January 24, 2019, as doi:10.3324/haematol.2018.206375. Copyright 2019 Ferrata Storti Foundation. Unravelling the cellular origin and clinical prognostic markers of infant B-cell acute lymphoblastic leukemia using genome-wide analysis by Antonio Agraz-Doblas, Clara Bueno, Rachael Bashford-Rogers, Anindita Roy, Pauline Schneider, Michela Bardini, Paola Ballerini, Gianni Cazzaniga, Thaidy Moreno, Carlos Revilla, Marta Gut, Maria G Valsecchi, Irene Roberts, Rob Pieters, Paola De Lorenzo, Ignacio Varela, Pablo Menendez, and Ronald W Stam Haematologica 2019 [Epub ahead of print] Citation: Antonio Agraz-Doblas, Clara Bueno, Rachael Bashford-Rogers, Anindita Roy, Pauline Schneider, Michela Bardini, Paola Ballerini, Gianni Cazzaniga, Thaidy Moreno, Carlos Revilla, Marta Gut, Maria G Valsecchi, Irene Roberts, Rob Pieters, Paola De Lorenzo, Ignacio Varela, Pablo Menendez, and Ronald W Stam. Unravelling the cellular origin and clinical prognostic markers of infant B-cell acute lymphoblastic leukemia using genome-wide analysis Haematologica. 2019; 104:xxx doi:10.3324/haematol.2018.206375 Publisher's Disclaimer. E-publishing ahead of print is increasingly important for the rapid dissemination of science. Haematologica is, therefore, E-publishing PDF files of an early version of manuscripts that have completed a regular peer review and have been accepted for publication. E-publishing of this PDF file has been approved by the authors. After having E-published Ahead of Print, manuscripts will then undergo technical and English editing, typesetting, proof correction and be presented for the authors' final approval; the final version of the manuscript will then appear in print on a regular issue of the journal. All legal disclaimers that apply to the journal also pertain to this production process. -
Cytokine-Driven Cell Cycling Is Mediated Through Cdc25a
JCB: ARTICLE Cytokine-driven cell cycling is mediated through Cdc25A Annette R. Khaled,1,3 Dmitry V. Bulavin,2 Christina Kittipatarin,1 Wen Qing Li,3 Michelle Alvarez,1 Kyungjae Kim,3,5 Howard A. Young,4 Albert J. Fornace,2 and Scott K. Durum3 1University of Central Florida, BioMolecular Science Center, Orlando, FL 32628 2Division of Basic Sciences, National Cancer Institute, Bethesda, MD 20892 3Laboratory of Molecular Immunoregulation and 4Laboratory of Experimental Immunology, National Cancer Institute at Frederick, Frederick, MD 21702 5Department of Pharmacy, Sahm-Yook University, Seoul, Korea, 139-742 ymphocytes are the central mediators of the im- the critical mediator of proliferation. Withdrawal of IL-7 mune response, requiring cytokines for survival and or IL-3 from dependent lymphocytes activates the stress L proliferation. Survival signaling targets the Bcl-2 kinase, p38 MAPK, which phosphorylates Cdc25A, in- family of apoptotic mediators, however, the pathway for ducing its degradation. As a result, Cdk/cyclin com- the cytokine-driven proliferation of lymphocytes is poorly plexes remain phosphorylated and inactive and cells understood. Here we show that cytokine-induced cell arrest before the induction of apoptosis. Inhibiting p38 cycle progression is not solely dependent on the synthe- MAPK or expressing a mutant Cdc25A, in which the two sis of cyclin-dependent kinases (Cdks) or cyclins. Rather, p38 MAPK target sites, S75 and S123, are altered, ren- we observe that in lymphocyte cell lines dependent on ders cells resistant to cytokine withdrawal, restoring the interleukin-3 or interleukin-7, or primary lymphocytes activity of Cdk/cyclin complexes and driving the cell cycle dependent on interleukin 7, the phosphatase Cdc25A is independent of a growth stimulus. -
The Role and Mechanisms of Action of Micrornas in Cancer Drug Resistance Wengong Si1,2,3, Jiaying Shen4, Huilin Zheng1,5 and Weimin Fan1,6*
Si et al. Clinical Epigenetics (2019) 11:25 https://doi.org/10.1186/s13148-018-0587-8 REVIEW Open Access The role and mechanisms of action of microRNAs in cancer drug resistance Wengong Si1,2,3, Jiaying Shen4, Huilin Zheng1,5 and Weimin Fan1,6* Abstract MicroRNAs (miRNAs) are small non-coding RNAs with a length of about 19–25 nt, which can regulate various target genes and are thus involved in the regulation of a variety of biological and pathological processes, including the formation and development of cancer. Drug resistance in cancer chemotherapy is one of the main obstacles to curing this malignant disease. Statistical data indicate that over 90% of the mortality of patients with cancer is related to drug resistance. Drug resistance of cancer chemotherapy can be caused by many mechanisms, such as decreased antitumor drug uptake, modified drug targets, altered cell cycle checkpoints, or increased DNA damage repair, among others. In recent years, many studies have shown that miRNAs are involved in the drug resistance of tumor cells by targeting drug-resistance-related genes or influencing genes related to cell proliferation, cell cycle, and apoptosis. A single miRNA often targets a number of genes, and its regulatory effect is tissue-specific. In this review, we emphasize the miRNAs that are involved in the regulation of drug resistance among different cancers and probe the mechanisms of the deregulated expression of miRNAs. The molecular targets of miRNAs and their underlying signaling pathways are also explored comprehensively. A holistic understanding of the functions of miRNAs in drug resistance will help us develop better strategies to regulate them efficiently and will finally pave the way toward better translation of miRNAs into clinics, developing them into a promising approach in cancer therapy. -
Identification and Characterization of TPRKB Dependency in TP53 Deficient Cancers
Identification and Characterization of TPRKB Dependency in TP53 Deficient Cancers. by Kelly Kennaley A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Molecular and Cellular Pathology) in the University of Michigan 2019 Doctoral Committee: Associate Professor Zaneta Nikolovska-Coleska, Co-Chair Adjunct Associate Professor Scott A. Tomlins, Co-Chair Associate Professor Eric R. Fearon Associate Professor Alexey I. Nesvizhskii Kelly R. Kennaley [email protected] ORCID iD: 0000-0003-2439-9020 © Kelly R. Kennaley 2019 Acknowledgements I have immeasurable gratitude for the unwavering support and guidance I received throughout my dissertation. First and foremost, I would like to thank my thesis advisor and mentor Dr. Scott Tomlins for entrusting me with a challenging, interesting, and impactful project. He taught me how to drive a project forward through set-backs, ask the important questions, and always consider the impact of my work. I’m truly appreciative for his commitment to ensuring that I would get the most from my graduate education. I am also grateful to the many members of the Tomlins lab that made it the supportive, collaborative, and educational environment that it was. I would like to give special thanks to those I’ve worked closely with on this project, particularly Dr. Moloy Goswami for his mentorship, Lei Lucy Wang, Dr. Sumin Han, and undergraduate students Bhavneet Singh, Travis Weiss, and Myles Barlow. I am also grateful for the support of my thesis committee, Dr. Eric Fearon, Dr. Alexey Nesvizhskii, and my co-mentor Dr. Zaneta Nikolovska-Coleska, who have offered guidance and critical evaluation since project inception. -
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. -
Mig-6 Controls EGFR Trafficking and Suppresses Gliomagenesis
Mig-6 controls EGFR trafficking and suppresses gliomagenesis Haoqiang Yinga,1, Hongwu Zhenga,1, Kenneth Scotta, Ruprecht Wiedemeyera, Haiyan Yana, Carol Lima, Joseph Huanga, Sabin Dhakala, Elena Ivanovab, Yonghong Xiaob,HaileiZhangb,JianHua, Jayne M. Stommela, Michelle A. Leea, An-Jou Chena, Ji-Hye Paika,OresteSegattoc, Cameron Brennand,e, Lisa A. Elferinkf,Y.AlanWanga,b, Lynda China,b,g, and Ronald A. DePinhoa,b,h,2 aDepartment of Medical Oncology, bBelfer Institute for Applied Cancer Science, Belfer Foundation Institute for Innovative Cancer Science, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA 02115; cLaboratory of Immunology, Istituto Regina Elena, Rome 00158, Italy; dHuman Oncology and Pathogenesis Program and eDepartment of Neurosurgery, Memorial Sloan-Kettering Cancer Center, New York, NY 10065; fDepartment of Neuroscience and Cell Biology, University of Texas Medical Branch, Galveston, TX 77555; gDepartment of Dermatology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115; and hDepartment of Medicine and Genetics, Harvard Medical School, Boston, MA 02115 Edited* by Webster K. Cavenee, Ludwig Institute, University of California, La Jolla, CA, and approved March 8, 2010 (received for review December 23, 2009) Glioblastoma multiforme (GBM) is the most common and lethal structural aberrations that serve as a key pathological driving primary brain cancer that is driven by aberrant signaling of growth force for tumor progression and many of them remain to be factor receptors, particularly the epidermal growth factor receptor characterized (6, 7). GBM possesses a highly rearranged genome (EGFR). EGFR signaling is tightly regulated by receptor endocytosis and high-resolution genome analysis has uncovered myriad and lysosome-mediated degradation, although the molecular somatic alterations on the genomic and epigenetic levels (2, 3). -
Principles and Applications of Rabbit Models for Atherosclerosis Research
J Atheroscler Thromb, 2018; 25: 213-220. http://doi.org/10.5551/jat.RV17018 Review Principles and Applications of Rabbit Models for Atherosclerosis Research Jianglin Fan1, Yajie Chen1, Haizhao Yan1, Manabu Niimi1, Yanli Wang2 and Jingyan Liang3 1Department of Molecular Pathology, Faculty of Medicine, Graduate School of Medical Sciences, University of Yamanashi, Yamanashi, Japan 2Department of Pathology, Xi’an Medical University, Xi’an, China 3Research Center for Vascular Biology, Yangzhou University School of Medicine, Yangzhou, China Rabbits are one of the most used experimental animals for biomedical research, particularly as a bio- reactor for the production of antibodies. However, many unique features of the rabbit have also made it as an excellent species for examining a number of aspects of human diseases such as atherosclerosis. Rabbits are phylogenetically closer to humans than rodents, in addition to their relatively proper size, tame disposition, and ease of use and maintenance in the laboratory facility. Due to their short life spans, short gestation periods, high numbers of progeny, low cost (compared with other large ani- mals) and availability of genomics and proteomics, rabbits usually serve to bridge the gap between smaller rodents (mice and rats) and larger animals, such as dogs, pigs and monkeys, and play an important role in many translational research activities such as pre-clinical testing of drugs and diag- nostic methods for patients. The principle of using rabbits rather than other animals as an experi- mental model is very simple: rabbits should be used for research, such as translational research, that is difficult to accomplish with other species. Recently, rabbit genome sequencing and transcriptomic profiling of atherosclerosis have been successfully completed, which has paved a new way for researchers to use this model in the future. -
Anti- Histone-H3 Antibody
anti- Histone-H3 antibody Product Information Catalog No.: FNab03890 Size: 100μg Form: liquid Purification: Immunogen affinity purified Purity: ≥95% as determined by SDS-PAGE Host: Rabbit Clonality: polyclonal Clone ID: None IsoType: IgG Storage: PBS with 0.02% sodium azide and 50% glycerol pH 7.3, -20℃ for 12 months (Avoid repeated freeze / thaw cycles.) Background HIST2H3A,histone cluster 2, H3a.It is the core component of nucleosome. Nucleosomes wrap and compact DNA into chromatin, limiting DNA accessibility to the cellular machineries which require DNA as a template. Histones thereby play a central role in transcription regulation, DNA repair, DNA replication and chromosomal stability. DNA accessibility is regulated via a complex set of post-translational modifications of histones, also called histone code, and nucleosome remodeling. HIST2H3A is Expressed during S phase, then expression strongly decreases as cell division slows down during the process of differentiation. Immunogen information Immunogen: histone cluster 2, H3a Synonyms: H3/n, H3/o, H3F2, H3FM, HIST2H3A, HIST2H3C, HIST2H3D, histone cluster 2, H3a, Histone H3, Histone H3.2, Histone H3/m, Histone H3/o Observed MW: 15-17 kDa Uniprot ID : Q71DI3 Application 1 Wuhan Fine Biotech Co., Ltd. B9 Bld, High-Tech Medical Devices Park, No. 818 Gaoxin Ave.East Lake High-Tech Development Zone.Wuhan, Hubei, China(430206) Tel :( 0086)027-87384275 Fax: (0086)027-87800889 www.fn-test.com Reactivity: Human, Mouse, Rat Tested Application: ELISA, WB, IHC, IF Recommended dilution: WB: 1:500-1:5000; IHC: 1:50-1:200; IF: 1:20-1:200 Image: Immunohistochemistry of paraffin-embedded human breast cancer tissue slide using FNab03890(Histone-H3 Antibody) at dilution of 1:50 Immunofluorescent analysis of HEK-293 cells using FNab03890 (Histone-H3 Antibody) at dilution of 1:50 and Rhodamine-Goat anti-Rabbit IgG 2 Wuhan Fine Biotech Co., Ltd. -
9. Atypical Dusps: 19 Phosphatases in Search of a Role
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Digital.CSIC Transworld Research Network 37/661 (2), Fort P.O. Trivandrum-695 023 Kerala, India Emerging Signaling Pathways in Tumor Biology, 2010: 185-208 ISBN: 978-81-7895-477-6 Editor: Pedro A. Lazo 9. Atypical DUSPs: 19 phosphatases in search of a role Yolanda Bayón and Andrés Alonso Instituto de Biología y Genética Molecular, CSIC-Universidad de Valladolid c/ Sanz y Forés s/n, 47003 Valladolid, Spain Abstract. Atypical Dual Specificity Phosphatases (A-DUSPs) are a group of 19 phosphatases poorly characterized. They are included among the Class I Cys-based PTPs and contain the active site motif HCXXGXXR conserved in the Class I PTPs. These enzymes present a phosphatase domain similar to MKPs, but lack any substrate targeting domain similar to the CH2 present in this group. Although most of these phosphatases have no more than 250 amino acids, their size ranges from the 150 residues of the smallest A-DUSP, VHZ/DUSP23, to the 1158 residues of the putative PTP DUSP27. The substrates of this family include MAPK, but, in general terms, it does not look that MAPK are the general substrates for the whole group. In fact, other substrates have been described for some of these phosphatases, like the 5’CAP structure of mRNA, glycogen, or STATs and still the substrates of many A-DUSPs have not been identified. In addition to the PTP domain, most of these enzymes present no additional recognizable domains in their sequence, with the exception of CBM-20 in laforin, GTase in HCE1 and a Zn binding domain in DUSP12. -
Download Validation Data
PrimePCR™Assay Validation Report Gene Information Gene Name FAST kinase domain-containing protein 1 Gene Symbol Fastkd1 Organism Rat Gene Summary Description Not Available Gene Aliases Not Available RefSeq Accession No. NM_001191738 UniGene ID Rn.226110 Ensembl Gene ID ENSRNOG00000024335 Entrez Gene ID 311112 Assay Information Unique Assay ID qRnoCEP0034063 Assay Type Probe - Validation information is for the primer pair using SYBR® Green detection Detected Coding Transcript(s) ENSRNOT00000036585 Amplicon Context Sequence AAAAAAAAAAACTACAGTCATGATCTGCCTGCTCCAAATATCTGTTCTCTCAGGTA GTCCATCCGTGTATCCTTCGTTGACATTGCCATGGAGTTCCA Amplicon Length (bp) 68 Chromosome Location 3:62537455-62537552 Assay Design Exonic Purification Desalted Validation Results Efficiency (%) 97 R2 0.9997 cDNA Cq 23.19 cDNA Tm (Celsius) 79 gDNA Cq Specificity (%) 100 Information to assist with data interpretation is provided at the end of this report. Page 1/4 PrimePCR™Assay Validation Report Fastkd1, Rat Amplification Plot Amplification of cDNA generated from 25 ng of universal reference RNA Melt Peak Melt curve analysis of above amplification Standard Curve Standard curve generated using 20 million copies of template diluted 10-fold to 20 copies Page 2/4 PrimePCR™Assay Validation Report Products used to generate validation data Real-Time PCR Instrument CFX384 Real-Time PCR Detection System Reverse Transcription Reagent iScript™ Advanced cDNA Synthesis Kit for RT-qPCR Real-Time PCR Supermix SsoAdvanced™ SYBR® Green Supermix Experimental Sample qPCR Reference Total RNA Data Interpretation Unique Assay ID This is a unique identifier that can be used to identify the assay in the literature and online. Detected Coding Transcript(s) This is a list of the Ensembl transcript ID(s) that this assay will detect. Details for each transcript can be found on the Ensembl website at www.ensembl.org.