DOCSLIB.ORG

4. Defining a Binding Interaction Between KDM1A and the Long Non-Coding RNA HOTAIR

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
4. Defining a Binding Interaction Between KDM1A and the Long Non-Coding RNA HOTAIR Probing the Interfaces of Epigenetic Complexes: Efforts Towards Elucidating and Targeting Critical Protein:Protein and Protein:lncRNA Interactions of Lysine-Specific Demethylase 1 (KDM1A/LSD1) By Meghan Frances Lawler Department of Chemistry Duke University Date:_______________________ Approved: ___________________________ Dewey G. McCafferty, Supervisor ___________________________ Emily Derbyshire ___________________________ Michael Lynch ___________________________ Qiu Wang Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Chemistry in the Graduate School of Duke University 2019 ABSTRACT Probing the Interfaces of Epigenetic Complexes: Efforts Towards Elucidating and Targeting Critical Protein:Protein and Protein:lncRNA Interactions of Lysine-Specific Demethylase 1 (KDM1A/LSD1) by Meghan Frances Lawler Department of Chemistry Duke University Date:_______________________ Approved: ___________________________ Dewey G. McCafferty, Supervisor ___________________________ Emily Derbyshire ___________________________ Michael Lynch ___________________________ Qiu Wang An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Chemistry in the Graduate School of Duke University 2019 Copyright by Meghan Frances Lawler 2019 Abstract The post translational modification (PTM) of histone proteins is a highly dynamic process that is utilized in the control of gene transcription. This epigenetic process involves enzymatic ‘writers’ and ‘erasers’ which place or remove chemical modifications to the unstructured tails of histone proteins which protrude out from the nucleosomal core. In a highly dynamic manner, each PTM is spatiotemporally regulated and combinations of PTMs at a gene promotor or enhancer region leads to transcriptional enhancement or repression. The gene targets as well as selectivity and specificity of epigenetic enzymes is regulated by the multimeric complexes each enzyme is co-opted. Each complex contains a unique set of coregulatory proteins with RNA and DNA binding domains and PTM ‘reader’ domains to direct the catalytic machinery to a specific subset of genes. The coregulatory proteins also affect the specificity and selectivity of the enzyme through mechanisms which are only beginning to be explored. Our interest is in elucidating the role of coregulatory proteins and lncRNA with respect to lysine-specific demethylase 1 (LSD1/KDM1A). A flavin-dependent mono-and di-demethylase of H3K4me1/2 and H3K9me1/2, KDM1A has been implicated in many different multimeric enzymatic complexes which, in some cases such as the REST and NuRD complexes, function on opposing pathways. This disparity in the downstream outcome being coordinated by the same enzyme highlights the need to understand not iv only epigenetic enzymes, but to consider the complexes as a whole towards therapeutic targeting. The specific aims of my thesis were to (a) interrogate the role of individual and multiple coregulatory partners in enzyme selectivity and specificity (b) establish tools to study the mechanisms of biochemical and biophysical of protein:protein and protein:lncRNA interactions and (c) elucidate key characteristics of protein:protein and protein:lncRNA interfaces towards targeted disruption. To this end, I have utilized cloning and mutagenesis methods towards heterologous expression and purification of coregulatory partners of KDM1A in E. coli. I chose coregulatory partners found in a common catalytic core as well as several additional coregulatory proteins from a stable KDM1A-containing 5-mer complex. I have produced multiple constructs for four of these proteins to allow for multiple affinity purification routes as well as for future binding studies. I have further expressed each of these constructs and have made significant efforts towards the purification of each construct based on solubility. I furthermore established HDX-MS and SELEX protocol in our lab as tools to allow us to explore the dynamics of these epigenetic interactions. I further demonstrated and confirmed that there is no hotspot along the binding interface between KDM1A and CoREST, but that CoREST stabilizes the apical end of the KDM1A tower domain via HDX-MS with the highest change in deuterium uptake, over 20%, long KDM1A TαA residues 440-451. v I also made significant efforts towards elucidating the interaction between KDM1A and HOTAIR. Firstly, I established an RNA radiolabeled EMSA assay for the lab which allowed us to test the binding of HOTAIR to KDM1A. With this assay, we saw that CoREST286-482, specifically the linker region (residues 293-380), must be bound to KDM1A for HOTAIR to bind and that the dissociation constant was unchanged at 1.710.38 µM and 1.29±0.34 µM, respectively. Further, I confirmed that the first 320 nt of domain 4 of HOTAIR (nt 1500-1820) contain the critical binding and that the dissociation constant was slightly higher at 2.97±0.96 µM. I have also optimized SHAPE-MaP and crosslinking strategies to explore the binding interface between KDM1A:CoREST286-482 and lncRNA. I determined that there were 83 nt that displayed at least a 1.5-fold change in SHAPE reactivity of HOTAIR D4 due to the presence of KDM1A:CoREST286-482. I also utilized a free-energy based secondary structure model to establish a secondary structure for HOTAIR D4 based on my SHAPE-MaP data. I noted that 44% of the significant nt were confined to a stretch of RNA (nt 1538-1610, 1779-1844) that is predominantly dsRNA. Further usage of photochemical crosslinking strategies revealed a propensity for G:C paired nt to be crosslinked to KDM1A:CoREST286-482. A similar nt sequence around these paired nt suggests a binding motif. vi Dedication These last five years have truly been a journey. I came to graduate school at Duke University ready to learn and partake in exciting and relevant science. So first, and foremost, thank you to my advisor, Dewey McCafferty, for allowing me the space to explore but also to grow as a scientist and person. In addition, I have grown enormously as a person in ways that I could not even have imagined, and there are many people that I would like to take a moment to thank and dedicate this work to. None of this would have been possible without the support and belief the faculty at Western Carolina University had in me. Dr. William Kwochka, you sparked and fostered my interest in science, and encouraged me every step of the way. Your mentorship and guidance has been unparalleled – I never would have considered graduate school without you. Dr. David Evanoff, thank you for fostering my skills as an independent researcher while at Western, and for all of the advice and guidance during my time at Duke. Brittania Bintz, thank you for pushing me and teaching me to have the confidence to stand up for myself and to push for what I believe in. Bob Buckner, David Starnes, Matt Henley, and Jon Henson: the four of you kept me grounded and reminded me that there will always be time outside of science to follow my other passions. Thank you to the four of you for seeing the potential in me when I couldn’t see it in myself. To my parents, Mary and Kelly Lawler, thank you for your unwavering support and love, it hasn’t always been easy, but we’ve made it work the best way we know vii how. Thank you for always granting me opportunities to do what I need to do and not questioning my path. I am so blessed to have such supportive parents in my life, and I will never be able to thank you enough. There truly aren’t the words to express how grateful I am to not only have you as parents, but friends. To my siblings, Jonathan, Grace, and Shannon Lawler, each of you keep me balanced. Jonathan, thank you for all of the Friday evening conversations, you have no idea how much I looked forward to them some weeks. Grace, thank you for being a ray of sunshine and always willing to just talk even when I have nothing to say. Shannon, thanks for always being 100% authentic to yourself, it reminds me to do the same. I am so proud of each of you for pursuing your goals and dreams with drive and purpose, it has been a blessing watching you grow, and I can’t wait to keep watching your journeys. To my friends and Kappa Kappa Psi brothers, thank you for standing by my side and for being my family. Each of you have shaped and changed my perspective and life in ways that I don’t think I’ll ever be able to fully grasp. I am so grateful for each of you and the lessons you have taught me, the good and the bad, I am a stronger, more compassionate, and more conscientious person because of you. I’d like to specifically thank Brittany Clark, Rachel Caddell, Mary Kate Moore, Katie Durham, Nina Fiore, Jesse Nixon, Alexandra and Andrew Hall, Cameron Holmes, Chuck Hendrick, Christiana Gooden, Katherine and Bumki Kim, Alex Chaconas, and Ken Maksimchuk. Thank you to each of you for keeping me alive, sane, and well-fed over the past years. viii You all have each stood by me and stood in my corner through everything, and I can never thank you enough. The confidence each of you hold in me gave me strength when I most needed it. I’d also like to thank those that couldn’t walk with me through my entire time here at Duke, you each taught me of my individual strength and courage. I cherish all of the memories I have with each of you and wish you nothing but the best. “ I’d like to also thank my undergrads, Rebecca Haley and Maegan Burns. I know this project was not the easiest or straightforward, but the dedication and drive that both of you have has made me a better person and mentor and that is invaluable to me.
Load more

Recommended publications
  • Screening and Identification of Key Biomarkers in Clear Cell Renal Cell Carcinoma Based on Bioinformatics Analysis
    bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 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. Screening and identification of key biomarkers in clear cell renal cell carcinoma based on bioinformatics analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 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. Abstract Clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignancy of the urinary system. The pathogenesis and effective diagnosis of ccRCC have become popular topics for research in the previous decade. In the current study, an integrated bioinformatics analysis was performed to identify core genes associated in ccRCC. An expression dataset (GSE105261) was downloaded from the Gene Expression Omnibus database, and included 26 ccRCC and 9 normal kideny samples. Assessment of the microarray dataset led to the recognition of differentially expressed genes (DEGs), which was subsequently used for pathway and gene ontology (GO) enrichment analysis.
    [Show full text]
  • FK506-Binding Protein 12.6/1B, a Negative Regulator of [Ca2+], Rescues Memory and Restores Genomic Regulation in the Hippocampus of Aging Rats
    This Accepted Manuscript has not been copyedited and formatted. The final version may differ from this version. A link to any extended data will be provided when the final version is posted online. Research Articles: Neurobiology of Disease FK506-Binding Protein 12.6/1b, a negative regulator of [Ca2+], rescues memory and restores genomic regulation in the hippocampus of aging rats John C. Gant1, Eric M. Blalock1, Kuey-Chu Chen1, Inga Kadish2, Olivier Thibault1, Nada M. Porter1 and Philip W. Landfield1 1Department of Pharmacology & Nutritional Sciences, University of Kentucky, Lexington, KY 40536 2Department of Cell, Developmental and Integrative Biology, University of Alabama at Birmingham, Birmingham, AL 35294 DOI: 10.1523/JNEUROSCI.2234-17.2017 Received: 7 August 2017 Revised: 10 October 2017 Accepted: 24 November 2017 Published: 18 December 2017 Author contributions: J.C.G. and P.W.L. designed research; J.C.G., E.M.B., K.-c.C., and I.K. performed research; J.C.G., E.M.B., K.-c.C., I.K., and P.W.L. analyzed data; J.C.G., E.M.B., O.T., N.M.P., and P.W.L. wrote the paper. Conflict of Interest: The authors declare no competing financial interests. NIH grants AG004542, AG033649, AG052050, AG037868 and McAlpine Foundation for Neuroscience Research Corresponding author: Philip W. Landfield, [email protected], Department of Pharmacology & Nutritional Sciences, University of Kentucky, 800 Rose Street, UKMC MS 307, Lexington, KY 40536 Cite as: J. Neurosci ; 10.1523/JNEUROSCI.2234-17.2017 Alerts: Sign up at www.jneurosci.org/cgi/alerts to receive customized email alerts when the fully formatted version of this article is published.
    [Show full text]
  • Long Non-Coding RNA HOTAIR Regulates Polycomb-Dependent Chromatin
    Author Manuscript Published OnlineFirst on August 23, 2011; DOI: 10.1158/0008-5472.CAN-11-1021 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Kogo et al. 1 Long non-coding RNA HOTAIR regulates Polycomb-dependent chromatin modification and is associated with poor prognosis in colorectal cancers. Ryunosuke Kogo1, 4, 6, Teppei Shimamura2, 6, Koshi Mimori1, 6, Kohichi Kawahara3, Seiya Imoto2, Tomoya Sudo1, Fumiaki Tanaka1, Kohei Shibata1, Akira Suzuki3, Shizuo Komune4, Satoru Miyano2, and Masaki Mori5 Authors’ Affiliations 1 Department of Surgery, Medical Institute of Bioregulation, Kyushu University, 4546, Tsurumihara, Beppu 874-0838, Japan. 2 Human Genome Center, Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan. 3 Division of Cancer Genetics, Medical Institute Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan. 4 Department of Otorhinolaryngology, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan. 5 Department of Gastroenterological Surgery, Graduate School of Medicine, Osaka Downloaded from cancerres.aacrjournals.org on September 28, 2021. © 2011 American Association for Cancer Research. Author Manuscript Published OnlineFirst on August 23, 2011; DOI: 10.1158/0008-5472.CAN-11-1021 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Kogo et al. 2 University, 2-2 Yamadaoka, Suita, 565-0871, Japan 6) These authors contributed equally to this work. Running title: HOTAIR in colorectal cancer Key words: HOTAIR, ncRNA, colorectal cancer, PRC2, liver metastasis Disclosure: There are no potential conflicts of interest to disclose.
    [Show full text]
  • DNA Methylation Regulates Discrimination of Enhancers From
    Sharifi-Zarchi et al. BMC Genomics (2017) 18:964 DOI 10.1186/s12864-017-4353-7 RESEARCHARTICLE Open Access DNA methylation regulates discrimination of enhancers from promoters through a H3K4me1-H3K4me3 seesaw mechanism Ali Sharifi-Zarchi1,2,3,4†, Daniela Gerovska5†, Kenjiro Adachi6, Mehdi Totonchi3, Hamid Pezeshk7,8, Ryan J. Taft9, Hans R. Schöler6,10, Hamidreza Chitsaz2, Mehdi Sadeghi8,11, Hossein Baharvand3,12* and Marcos J. Araúzo-Bravo5,13,14* Abstract Background: DNA methylation at promoters is largely correlated with inhibition of gene expression. However, the role of DNA methylation at enhancers is not fully understood, although a crosstalk with chromatin marks is expected. Actually, there exist contradictory reports about positive and negative correlations between DNA methylation and H3K4me1, a chromatin hallmark of enhancers. Results: We investigated the relationship between DNA methylation and active chromatin marks through genome- wide correlations, and found anti-correlation between H3K4me1 and H3K4me3 enrichment at low and intermediate DNA methylation loci. We hypothesized “seesaw” dynamics between H3K4me1 and H3K4me3 in the low and intermediate DNA methylation range, in which DNA methylation discriminates between enhancers and promoters, marked by H3K4me1 and H3K4me3, respectively. Low methylated regions are H3K4me3 enriched, while those with intermediate DNA methylation levels are progressively H3K4me1 enriched. Additionally, the enrichment of H3K27ac, distinguishing active from primed enhancers, follows a plateau in the lower range of the intermediate DNA methylation level, corresponding to active enhancers, and decreases linearly in the higher range of the intermediate DNA methylation. Thus, the decrease of the DNA methylation switches smoothly the state of the enhancers from a primed to an active state.
    [Show full text]
  • Understanding Chronic Kidney Disease: Genetic and Epigenetic Approaches
    University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2017 Understanding Chronic Kidney Disease: Genetic And Epigenetic Approaches Yi-An Ko Ko University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Bioinformatics Commons, Genetics Commons, and the Systems Biology Commons Recommended Citation Ko, Yi-An Ko, "Understanding Chronic Kidney Disease: Genetic And Epigenetic Approaches" (2017). Publicly Accessible Penn Dissertations. 2404. https://repository.upenn.edu/edissertations/2404 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/2404 For more information, please contact [email protected]. Understanding Chronic Kidney Disease: Genetic And Epigenetic Approaches Abstract The work described in this dissertation aimed to better understand the genetic and epigenetic factors influencing chronic kidney disease (CKD) development. Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) significantly associated with chronic kidney disease. However, these studies have not effectively identified target genes for the CKD variants. Most of the identified variants are localized to non-coding genomic regions, and how they associate with CKD development is not well-understood. As GWAS studies only explain a small fraction of heritability, we hypothesized that epigenetic changes could explain part of this missing heritability. To identify potential gene targets of the genetic variants, we performed expression quantitative loci (eQTL) analysis, using genotyping arrays and RNA sequencing from human kidney samples. To identify the target genes of CKD-associated SNPs, we integrated the GWAS-identified SNPs with the eQTL results using a Bayesian colocalization method, coloc. This resulted in a short list of target genes, including PGAP3 and CASP9, two genes that have been shown to present with kidney phenotypes in knockout mice.
    [Show full text]
  • HOTAIR Launches Lncrnas
    Annotated Classic HOTAIR Launches lncRNAs Irene Bozzoni1,* 1Department of Biology and Biotechnology, “Charles Darwin” Sapienza - University of Rome, P. le A. Moro 5, 00185 Rome, Italy *Correspondence: [email protected] We are pleased to present a series of Annotated Classics celebrating 40 years of exciting biology in the pages of Cell. This install- ment revisits “Functional Demarcation of Active and Silent Chromatin Domains in Human HOX Loci by Noncoding RNAs” from Howard Chang’s lab. Here, Irene Bozzoni comments on how Rinn et al. ignited our appreciation for the ability of noncoding RNAs to regulate key cellular and developmental processes in trans. Each Annotated Classic offers a personal perspective on a groundbreaking Cell paper from leader in the field with notes on what stood out at the time of first reading and retrospective comments regarding the longer term influence of the work. To see Irene Bozzoni’s thoughts on different parts of the manuscript, just download the PDF and then hover over or double-click the highlighted text and comment boxes on the following pages. You can also view the annotations by opening the Comments navigation panel in Acrobat. Cell 159, November 20, 2014 ©2014 Elsevier Inc. Functional Demarcation of Active and Silent Chromatin Domains in Human HOX Loci by Noncoding RNAs John L. Rinn,1 Michael Kertesz,3,5 Jordon K. Wang,1,5 Sharon L. Squazzo,4 Xiao Xu,1 Samantha A. Brugmann,2 L. Henry Goodnough,2 Jill A. Helms,2 Peggy J. Farnham,4 Eran Segal,3,* and Howard Y. Chang1,* 1 Program in Epithelial Biology 2 Department of Surgery Stanford University School of Medicine, Stanford, CA 94305, USA 3 Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 76100, Israel 4 Department of Pharmacology and Genome Center, University of California, Davis, CA 95616, USA 5 These authors contributed equally to this work.
    [Show full text]
  • Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
    Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase
    [Show full text]
  • Supplementary Material
    BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) J Neurol Neurosurg Psychiatry Page 1 / 45 SUPPLEMENTARY MATERIAL Appendix A1: Neuropsychological protocol. Appendix A2: Description of the four cases at the transitional stage. Table A1: Clinical status and center proportion in each batch. Table A2: Complete output from EdgeR. Table A3: List of the putative target genes. Table A4: Complete output from DIANA-miRPath v.3. Table A5: Comparison of studies investigating miRNAs from brain samples. Figure A1: Stratified nested cross-validation. Figure A2: Expression heatmap of miRNA signature. Figure A3: Bootstrapped ROC AUC scores. Figure A4: ROC AUC scores with 100 different fold splits. Figure A5: Presymptomatic subjects probability scores. Figure A6: Heatmap of the level of enrichment in KEGG pathways. Kmetzsch V, et al. J Neurol Neurosurg Psychiatry 2021; 92:485–493. doi: 10.1136/jnnp-2020-324647 BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) J Neurol Neurosurg Psychiatry Appendix A1. Neuropsychological protocol The PREV-DEMALS cognitive evaluation included standardized neuropsychological tests to investigate all cognitive domains, and in particular frontal lobe functions. The scores were provided previously (Bertrand et al., 2018). Briefly, global cognitive efficiency was evaluated by means of Mini-Mental State Examination (MMSE) and Mattis Dementia Rating Scale (MDRS). Frontal executive functions were assessed with Frontal Assessment Battery (FAB), forward and backward digit spans, Trail Making Test part A and B (TMT-A and TMT-B), Wisconsin Card Sorting Test (WCST), and Symbol-Digit Modalities test.
    [Show full text]
  • 1714 Gene Comprehensive Cancer Panel Enriched for Clinically Actionable Genes with Additional Biologically Relevant Genes 400-500X Average Coverage on Tumor
    xO GENE PANEL 1714 gene comprehensive cancer panel enriched for clinically actionable genes with additional biologically relevant genes 400-500x average coverage on tumor Genes A-C Genes D-F Genes G-I Genes J-L AATK ATAD2B BTG1 CDH7 CREM DACH1 EPHA1 FES G6PC3 HGF IL18RAP JADE1 LMO1 ABCA1 ATF1 BTG2 CDK1 CRHR1 DACH2 EPHA2 FEV G6PD HIF1A IL1R1 JAK1 LMO2 ABCB1 ATM BTG3 CDK10 CRK DAXX EPHA3 FGF1 GAB1 HIF1AN IL1R2 JAK2 LMO7 ABCB11 ATR BTK CDK11A CRKL DBH EPHA4 FGF10 GAB2 HIST1H1E IL1RAP JAK3 LMTK2 ABCB4 ATRX BTRC CDK11B CRLF2 DCC EPHA5 FGF11 GABPA HIST1H3B IL20RA JARID2 LMTK3 ABCC1 AURKA BUB1 CDK12 CRTC1 DCUN1D1 EPHA6 FGF12 GALNT12 HIST1H4E IL20RB JAZF1 LPHN2 ABCC2 AURKB BUB1B CDK13 CRTC2 DCUN1D2 EPHA7 FGF13 GATA1 HLA-A IL21R JMJD1C LPHN3 ABCG1 AURKC BUB3 CDK14 CRTC3 DDB2 EPHA8 FGF14 GATA2 HLA-B IL22RA1 JMJD4 LPP ABCG2 AXIN1 C11orf30 CDK15 CSF1 DDIT3 EPHB1 FGF16 GATA3 HLF IL22RA2 JMJD6 LRP1B ABI1 AXIN2 CACNA1C CDK16 CSF1R DDR1 EPHB2 FGF17 GATA5 HLTF IL23R JMJD7 LRP5 ABL1 AXL CACNA1S CDK17 CSF2RA DDR2 EPHB3 FGF18 GATA6 HMGA1 IL2RA JMJD8 LRP6 ABL2 B2M CACNB2 CDK18 CSF2RB DDX3X EPHB4 FGF19 GDNF HMGA2 IL2RB JUN LRRK2 ACE BABAM1 CADM2 CDK19 CSF3R DDX5 EPHB6 FGF2 GFI1 HMGCR IL2RG JUNB LSM1 ACSL6 BACH1 CALR CDK2 CSK DDX6 EPOR FGF20 GFI1B HNF1A IL3 JUND LTK ACTA2 BACH2 CAMTA1 CDK20 CSNK1D DEK ERBB2 FGF21 GFRA4 HNF1B IL3RA JUP LYL1 ACTC1 BAG4 CAPRIN2 CDK3 CSNK1E DHFR ERBB3 FGF22 GGCX HNRNPA3 IL4R KAT2A LYN ACVR1 BAI3 CARD10 CDK4 CTCF DHH ERBB4 FGF23 GHR HOXA10 IL5RA KAT2B LZTR1 ACVR1B BAP1 CARD11 CDK5 CTCFL DIAPH1 ERCC1 FGF3 GID4 HOXA11 IL6R KAT5 ACVR2A
    [Show full text]
  • NF-Κb-HOTAIR Axis Links DNA Damage Response, Chemoresistance and Cellular Senescence in Ovarian Cancer
    HHS Public Access Author manuscript Author ManuscriptAuthor Manuscript Author Oncogene Manuscript Author . Author manuscript; Manuscript Author available in PMC 2016 October 14. Published in final edited form as: Oncogene. 2016 October 13; 35(41): 5350–5361. doi:10.1038/onc.2016.75. NF-κB-HOTAIR axis links DNA damage response, chemoresistance and cellular senescence in ovarian cancer Ali R. Özeş1, David F. Miller2, Osman N. Özeş3, Fang Fang2, Yunlong Liu4,5,6, Daniela Matei6,7,8, Tim Huang9, and Kenneth P. Nephew1,2,6,8,10,* 1Molecular and Cellular Biochemistry Department, Indiana University, Bloomington, IN 47405, USA 2Medical Sciences Program, Indiana University School of Medicine, Bloomington, IN 47405, USA 3Department of Medical Biology and Genetics, Akdeniz University, Antalya, Turkey 4Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana 46202, USA 5Center for Computational Biology and Bioinformatics, Indianapolis, Indiana 46202, USA 6Indiana University Melvin and Bren Simon Cancer Center, Indianapolis, Indiana 46202, USA 7Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA 8Department of Obstetrics and Gynecology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA 9Department of Molecular Medicine/Institute of Biotechnology, The University of Texas Health Science Center at San Antonio, San Antonio, TX, 78229-3900 10Department of Cellular and Integrative Physiology, Indiana University School of Medicine, Indianapolis, IN 46202, USA Abstract The transcription factor nuclear factor kappa B (NF-κB) and the long non-coding RNA (lncRNA) HOTAIR (HOX transcript antisense RNA) play diverse functional roles in cancer. In this study, we show that upregulation of HOTAIR induced platinum resistance in ovarian cancer, and increased HOTAIR levels were observed in recurrent platinum-resistant ovarian tumors vs.
    [Show full text]
  • UC Riverside UCR Honors Capstones 2020-2021
    UC Riverside UCR Honors Capstones 2020-2021 Title Transcriptomic Analysis of Molecular Mechanisms of Neuroprotection by Neuregulin-1 Following Ischemic Stroke Permalink https://escholarship.org/uc/item/1c89b11s Author Bennett, Kimberly R. Publication Date 2021-08-13 Data Availability The data associated with this publication are within the manuscript. eScholarship.org Powered by the California Digital Library University of California TRANSCRIPTOMIC ANALYSIS OF MOLECULAR MECHANISMS OF NEUROPROTECTION BY NERUEGULIN-1 FOLLOWING ISCHEMIC STROKE By Kimberly R. Bennett A capstone project submitted for graduation with University Honors May 06, 2021 University Honors University of California, Riverside APPROVED Dr. Victor G. J. Rodgers Department of Bioengineering Dr. Byron D. Ford Department of Biomedical Sciences Dr. Richard Cardullo, Howard H Hays Jr. Chair University Honors ABSTRACT Ischemic stroke is a global health problem that is characterized by early neuronal death, apoptosis, inflammation, and oxidative stress following an obstruction of the blood supply to the brain. Previous studies have shown that ischemic stroke causes a release of pro-inflammatory cytokines that produce changes in gene expression, primarily in inflammation and cell death. Neuregulin-1 (NRG-1) is growth factor that has been investigated for its neuroprotective properties and ability to delay neuronal death following ischemic stroke. While NRG-1 has shown significant promise in preventing brain damage and stimulating post-injury repair following stroke, the mechanisms behind its neuroprotective effects are unclear. The goal of this research was to investigate the effects of NRG-1 treatment on ischemia-induced gene expression profiles following a permanent middle cerebral artery occlusion (pMCAO) in rat models. Rats were sacrificed twelve hours following vehicle or NRG-1 treatment.
    [Show full text]
  • Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
    Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A.
    [Show full text]