DOCSLIB.ORG

The KMT1A-GATA3-STAT3 Circuit Is a Novel Self-Renewal Signaling of Human Bladder Cancer Stem Cells Zhao Yang1, Luyun He2,3, Kais

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
The KMT1A-GATA3-STAT3 Circuit Is a Novel Self-Renewal Signaling of Human Bladder Cancer Stem Cells Zhao Yang1, Luyun He2,3, Kais The KMT1A-GATA3-STAT3 circuit is a novel self-renewal signaling of human bladder cancer stem cells Zhao Yang1, Luyun He2,3, Kaisu Lin4, Yun Zhang1, Aihua Deng1, Yong Liang1, Chong Li2, 5, & Tingyi Wen1, 6, 1CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China 2Core Facility for Protein Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China 3CAS Key Laboratory of Infection and Immunity, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China 4Department of Oncology, the Second Affiliated Hospital of Soochow University, Suzhou 215000, China 5Beijing Jianlan Institute of Medicine, Beijing 100190, China 6Savaid Medical School, University of Chinese Academy of Sciences, Beijing 100049, China Correspondence author: Tingyi Wen, e-mail: wenty@im.ac.cn Chong Li, e-mail: lichong@moon.ibp.ac.cn Supplementary Figure S1. Isolation of human bladder cancer stem cells. BCMab1 and CD44 were used to isolate bladder cancer stem cells (BCSCs: BCMab1+CD44+) and bladder cancer non-stem cells (BCNSCs: BCMab1-CD44-) from EJ, samples #1 and #2 by flow cytometry. Supplementary Figure S2. Gene ontology analysis of downregulated genes of human BCSCs. (A) Pathway enrichment of 103 downregulated genes in BCSCs. (B) The seven downregulated genes in BCSCs participating in centromeric heterochromatin, mRNA-3’-UTR binding and translation regulator activity signaling pathways were validated by qRT-PCR. Data are presented as mean ± SD. P < 0.05; P < 0.01. Supplementary Figure S3. The expression of KMT1A is higher in human BC than that in peri-tumor tissues. (A) The expression of KMT1A was higher in BC samples than that in peri-tumors as assessed by immunohistochemistry, Scale bar = 50 m. (B-C) The expression of KMT1A was analyzed according to the data from Bae’s cohort (GSE13507) and Kim’s cohort (GSE37815). Supplementary Figure S4. KMT1A is highly expressed in basal subtype of bladder cancer. (A and C). Clustering analysis of GSE48075 and GSE48276 according to the basal and luminal biomarkers. (B and D). The expression of KMT1A was analyzed in the basal and luminal subtypes (GSE48075 and GSE48276). Supplementary Figure S5. The expression of KMT1A and NSD1 in normal and tumor cell lines of different origin, and TCGA database. (A and B) The mRNA and protein expression levels of KMT1A in normal and tumor cell lines of different origin. (C and D) The analysis of the expression of KMT1A (C) and NSD1 (D) in tumor samples from TCGA database. KMT1A was highly expressed in ESCA, STES, STAD, LUSC, HNSC, BLCA and LIHC. NSD1 was only highly expressed in LIHC. BLCA, Bladder Urothelial Carcinoma; BRCA, Breast invasive carcinoma; COAD, Colon adenocarcinoma; COADREAD, Colorectal adenocarcinoma; ESCA, Esophageal carcinoma; HNSC, Head and Neck squamous cell carcinoma; KIPAN, Pan-kidney cohort (KICH+KIRC+KIRP); KIRC, Kidney renal clear cell carcinoma; KIRP, Kidney renal papillary cell carcinoma; LAML, Acute Myeloid Leukemia; LIHC, Liver hepatocellular carcinoma; LUAD, Lung adenocarcinoma; LUSC, Lung squamous cell carcinoma; OV, Ovarian serous cystadenocarcinoma; READ, Rectum adenocarcinoma; STAD; Stomach adenocarcinoma, STES, Stomach and Esophageal carcinoma; THCA, Thyroid carcinoma; UCEC, Uterine Corpus Endometrial Carcinoma. Data are presented as mean ± SD. P < 0.05. Supplementary Figure S6. The expression of KMT1A in human bladder. (A) The expression of KMT1A in bladder cancer stem cells (BCSCs: BCMab1+CD44+), bladder cancer non-stem cells (BCNSCs: BCMab1-CD44-), normal bladder stem cells (NBSCs: pan-CK+CD44+) and normal bladder non-stem cells (NBNSCs: pan-CK+CD44-) from primary bladder cancer samples, n = 5. (B) KMT1A was highly expressed in BCSCs and tumorspheres derived from bladder cancer cell lines compared to that in BCNSCs and non- sphere tumor cells, as assessed by qRT-PCR. Non-sphere: bladder cancer cell lines or primary bladder cancer cells that failed to form tumorspheres. (C) The expression levels of CD44 and KMT1A in BC cell lines and primary BC samples were examined by qRT-PCR and then subjected to a correlation analysis, n = 10. Data are presented as mean ± SD. P < 0.05; P < 0.01. Supplementary Figure S7. Depletion of KMT1A abrogates the self-renewal and tumorigenicity of human BCSCs. (A and B) The qRT-PCR (A) and WB (B) analysis of KMT1A in shCtrl and shKMT1A BCSCs. -actin served as a loading control. (C) Representative photographs of tumorspheres formed by shCtrl and shKMT1A BCSCs. The number of tumorspheres was counted in five independent fields/well after two weeks of cultivation. Scale bar = 100 m. (D) shKMT1A BCSCs consisted of fewer CD44+ cells than shCtrl BCSCs. (E) Kaplan-Meier curves comparing the overall survival between bladder carcinomas patients expressing high or low levels of KMT1A, log-rank test. n, patient number. Data are presented as mean ± SD. P < 0.05; P < 0.01. Supplementary Figure S8. STAT3 is highly expressed and activated in human BCSCs. (A) The qRT-PCR analysis of the expression levels of GLI1, STAT3, BMI1, HES1, CTNNB1, NANOG, POU5F1, SOX2 and CD44 in shCtrl and shKMT1A BCSCs. (B) The WB analysis of pY-STAT3, STAT3, GLI1 and SOX2 in shCtrl and shKMT1A BCSCs. -actin served as a loading control. (C) The expression of STAT3 was higher in KMT1Ahigh samples than that in KMT1Alow samples based on an analysis of McConkey’s cohort (GSE48276). (D) The expression of STAT3 along with KMT1A were analyzed using the data from McConkey’s cohort (GSE48276). (E) STAT3 is highly expressed in BCSCs and tumorspheres derived from bladder cancer cell lines compared to that in BCNSCs and non-sphere tumor cells, as assessed by qRT-PCR. Non-sphere: bladder cancer cell lines or primary bladder cancer cells that failed to form tumorspheres. Data are presented as mean ± SD. P < 0.05; P < 0.01. Supplementary Figure S9. STAT3 activation is indispensable for the self-renewal maintenance of human BCSCs. (A) The qRT-PCR analysis of STAT3 in shCtrl and shSTAT3 BCSCs. (B) The WB analysis of pY-STAT3 and STAT3 in shCtrl and shSTAT3 BCSCs. -actin served as a loading control. (C) Representative photographs of tumorspheres formed by shCtrl and shSTAT3 BCSCs. The number of tumorspheres was counted in five independent fields/well after two weeks of cultivation. Scale bar = 100 m. (D) shSTAT3 BCSCs consisted of fewer CD44+ cells than shCtrl BCSCs. (E) Kaplan-Meier curves comparing the overall survival between bladder carcinomas patients expressing high or low levels of STAT3. n, patient number. Data are presented as mean ± SD. P < 0.05; **P < 0.01. Supplementary Figure S10. KMT1A is not recruited on the promoters of GATA1, GATA2, NFB, c-Myc, SOCS3, P53 and STAT3 in human BCSCs. (A-F) ChIP analysis of the promoters of GATA1, GATA2, NFB, c-Myc, SOCS3, P53 and STAT3 promoters with IgG and KMT1A antibodies in BCSCs. The enrichment of different regions of the promoter was detected by qRT-PCR. Data are presented as mean ± SD. Supplementary Figure S11. GATA3 was downregulated in BCSCs compared with that in BCNSCs. Supplementary Figure S12. The expression of GATA3 was downregulated in BCSCs. (A) GATA3 was downregulated in CD44high samples compared to that in CD44low samples based on an analysis of Michor’s cohort (GSE48276) and Michor’s cohort (GSE31684). (B) The expression of GATA3 along with CD44 were analyzed using the data from Michor’s cohort (GSE48276) and Michor’s cohort (GSE31684). (C) Kaplan-Meier curves comparing the overall survival between bladder carcinomas patients expressing high or low levels of GATA3. n, patient number. Data are presented as mean ± SD. P < 0.05; P < 0.01. Supplementary Figure S13. The destruction of STAT3 promoter by Cas9 in human BCNSCs. (A) Recognition sequence of GATA3 in the STAT3 promoter. (B) Sanger sequencing of PCR product including the STAT3 promoter in WT and Mut BCNSCs. Red bases indicated the abrogation of the binding motif of GATA3. Supplementary Fig. S14. Depletion of GATA3 promotes the transcription of STAT3 in BCNSCs. (A) The qRT-PCR analysis of GATA3 in shCtrl and shGATA3 BCNSCs, Student’s t test. (B) The WB analysis of pY-STAT3, STAT3 and GATA3 in shCtrl and shGATA3 BCNSCs. -actin served as a loading control. (C) Representative photographs of tumorspheres formed by shCtrl and shGATA3 BCNSCs. The number of tumorspheres was calculated in five independent fields/well after two weeks of cultivation, Student’s t test. Scale bar = 100 m. Data are presented as mean ± SD. P < 0.05; P < 0.01. Supplementary Figure S15. The KMT1A-GATA3-STAT3 circuit triggers the self- renewal and tumorigenicity of human BCSCs. (A) The qRT-PCR analysis of GATA3 and STAT3 in vec, oeGATA3 and oeGATA3/STAT3 BCSCs. (B) The WB analysis of pY-STAT3, STAT3 and GATA3 in vec, oeGATA3 and oeGATA3/STAT3 BCSCs. -actin served as a loading control. (C) oeGATA3 BCSCs consisted of fewer CD44+ cells than vec BCSCs. The overexpression of STAT3 in oeGATA3 BCSCs rescued the percentage of CD44+ cells, Student’s t test. Data are presented as mean ± SD. P < 0.05; P < 0.01. Supplementary Figure S16. The mutation of STAT3 promoter abolished the negative regulation of GATA3 on the expression of STAT3 in BCSCs. (A) Sanger sequencing of PCR product including the STAT3 promoter in vec and oeGATA3 Mut BCSCs. Red bases indicated the abrogation of the binding motif of GATA3. (B) The qRT-PCR analysis of GATA3 in vec and oeGATA3 Mut BCSCs (#3, T2a, high grade and #6, T2a, high grade), Student’s t test. (C) The WB analysis of pY-STAT3, STAT3 and GATA3 in vec and oeGATA3 Mut BCSCs. -actin served as a loading control. (D) The percentage of tumor-free mice four months after the subcutaneous injection of the different dilutions of vec or oeGATA3 Mut BCSCs into immunodeficient mice, n=6.
Load more

Recommended publications
  • Gene Symbol Gene Description ACVR1B Activin a Receptor, Type IB
    Table S1. Kinase clones included in human kinase cDNA library for yeast two-hybrid screening Gene Symbol Gene Description ACVR1B activin A receptor, type IB ADCK2 aarF domain containing kinase 2 ADCK4 aarF domain containing kinase 4 AGK multiple substrate lipid kinase;MULK AK1 adenylate kinase 1 AK3 adenylate kinase 3 like 1 AK3L1 adenylate kinase 3 ALDH18A1 aldehyde dehydrogenase 18 family, member A1;ALDH18A1 ALK anaplastic lymphoma kinase (Ki-1) ALPK1 alpha-kinase 1 ALPK2 alpha-kinase 2 AMHR2 anti-Mullerian hormone receptor, type II ARAF v-raf murine sarcoma 3611 viral oncogene homolog 1 ARSG arylsulfatase G;ARSG AURKB aurora kinase B AURKC aurora kinase C BCKDK branched chain alpha-ketoacid dehydrogenase kinase BMPR1A bone morphogenetic protein receptor, type IA BMPR2 bone morphogenetic protein receptor, type II (serine/threonine kinase) BRAF v-raf murine sarcoma viral oncogene homolog B1 BRD3 bromodomain containing 3 BRD4 bromodomain containing 4 BTK Bruton agammaglobulinemia tyrosine kinase BUB1 BUB1 budding uninhibited by benzimidazoles 1 homolog (yeast) BUB1B BUB1 budding uninhibited by benzimidazoles 1 homolog beta (yeast) C9orf98 chromosome 9 open reading frame 98;C9orf98 CABC1 chaperone, ABC1 activity of bc1 complex like (S. pombe) CALM1 calmodulin 1 (phosphorylase kinase, delta) CALM2 calmodulin 2 (phosphorylase kinase, delta) CALM3 calmodulin 3 (phosphorylase kinase, delta) CAMK1 calcium/calmodulin-dependent protein kinase I CAMK2A calcium/calmodulin-dependent protein kinase (CaM kinase) II alpha CAMK2B calcium/calmodulin-dependent
    [Show full text]
  • Simultaneous Genome-Wide Association Studies of Anti-Cyclic Citrullinated Peptide in Rheumatoid Arthritis Using Penalized Orthogonal-Components Regression
    BMC Proceedings BioMed Central Proceedings Open Access Simultaneous genome-wide association studies of anti-cyclic citrullinated peptide in rheumatoid arthritis using penalized orthogonal-components regression Yanzhu Lin1,MinZhang1,LiboWang1, Vitara Pungpapong1, James C Fleet2 and Dabao Zhang*1 Addresses: 1Department of Statistics, Purdue University, West Lafayette, Indiana 47907, USA and 2Department of Foods and Nutrition, Purdue University, West Lafayette, Indiana 47907, USA E-mail: Yanzhu Lin - lin43@purdue.edu; Min Zhang - minzhang@purdue.edu; Libo Wang - wang220@purdue.edu; Vitara Pungpapong - vpungpap@purdue.edu; James C Fleet - fleet@purdue.edu; Dabao Zhang* - zhangdb@purdue.edu *Corresponding author from Genetic Analysis Workshop 16 St Louis, MO, USA 17-20 September 2009 Published: 15 December 2009 BMC Proceedings 2009, 3(Suppl 7):S20 doi: 10.1186/1753-6561-3-S7-S20 This article is available from: http://www.biomedcentral.com/1753-6561/3/S7/S20 © 2009 Lin et al; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Genome-wide associations between single-nucleotide polymorphisms and clinical traits were simultaneously conducted using penalized orthogonal-components regression. This method was developed to identify the genetic variants controlling phenotypes from a massive number of candidate variants. By investigating the association between all single-nucleotide polymorphisms to the phenotype of antibodies against cyclic citrullinated peptide using the rheumatoid arthritis data provided by Genetic Analysis Workshop 16, we identified genetic regions which may contribute to the pathogenesis of rheumatoid arthritis.
    [Show full text]
  • TRNT1 Gene Trna Nucleotidyl Transferase 1
    TRNT1 gene tRNA nucleotidyl transferase 1 Normal Function The TRNT1 gene provides instructions for making a protein involved in the production ( synthesis) of other proteins. During protein synthesis, a molecule called transfer RNA ( tRNA) helps assemble protein building blocks (amino acids) into a chain that forms the protein. Each tRNA carries a specific amino acid to the growing chain. The TRNT1 protein modifies tRNAs by adding a series of three DNA building blocks (nucleotides), called a CCA trinucleotide, to the molecule. This modification is essential for the correct amino acid to be attached to each tRNA. While most protein synthesis occurs in the fluid surrounding the nucleus (cytoplasm), some proteins are synthesized in cell structures called mitochondria, which are the energy-producing centers in cells. Many mitochondrial proteins form groups (complexes) that carry out the reactions that produce energy. Separate tRNA molecules are used to build proteins in the cytoplasm and mitochondria. The TRNT1 protein attaches the CCA trinucleotide to both cytoplasmic and mitochondrial tRNA molecules. Health Conditions Related to Genetic Changes TRNT1 deficiency More than 20 TRNT1 gene mutations have been found to cause TRNT1 deficiency, a condition with a range of signs and symptoms that affect many body systems. Features can include a blood disorder called sideroblastic anemia, recurrent fevers, a shortage of immune cells called B cells that leads to impairment of the immune system ( immunodeficiency), delayed development of speech and motor skills, and eye abnormalities that cause vision problems. The severity of the condition varies among affected individuals. The TRNT1 gene mutations that cause TRNT1 deficiency lead to a shortage (deficiency) of functional TRNT1 protein.
    [Show full text]
  • Table 2. Significant
    Table 2. Significant (Q < 0.05 and |d | > 0.5) transcripts from the meta-analysis Gene Chr Mb Gene Name Affy ProbeSet cDNA_IDs d HAP/LAP d HAP/LAP d d IS Average d Ztest P values Q-value Symbol ID (study #5) 1 2 STS B2m 2 122 beta-2 microglobulin 1452428_a_at AI848245 1.75334941 4 3.2 4 3.2316485 1.07398E-09 5.69E-08 Man2b1 8 84.4 mannosidase 2, alpha B1 1416340_a_at H4049B01 3.75722111 3.87309653 2.1 1.6 2.84852656 5.32443E-07 1.58E-05 1110032A03Rik 9 50.9 RIKEN cDNA 1110032A03 gene 1417211_a_at H4035E05 4 1.66015788 4 1.7 2.82772795 2.94266E-05 0.000527 NA 9 48.5 --- 1456111_at 3.43701477 1.85785922 4 2 2.8237185 9.97969E-08 3.48E-06 Scn4b 9 45.3 Sodium channel, type IV, beta 1434008_at AI844796 3.79536664 1.63774235 3.3 2.3 2.75319499 1.48057E-08 6.21E-07 polypeptide Gadd45gip1 8 84.1 RIKEN cDNA 2310040G17 gene 1417619_at 4 3.38875643 1.4 2 2.69163229 8.84279E-06 0.0001904 BC056474 15 12.1 Mus musculus cDNA clone 1424117_at H3030A06 3.95752801 2.42838452 1.9 2.2 2.62132809 1.3344E-08 5.66E-07 MGC:67360 IMAGE:6823629, complete cds NA 4 153 guanine nucleotide binding protein, 1454696_at -3.46081884 -4 -1.3 -1.6 -2.6026947 8.58458E-05 0.0012617 beta 1 Gnb1 4 153 guanine nucleotide binding protein, 1417432_a_at H3094D02 -3.13334396 -4 -1.6 -1.7 -2.5946297 1.04542E-05 0.0002202 beta 1 Gadd45gip1 8 84.1 RAD23a homolog (S.
    [Show full text]
  • Searching the Genomes of Inbred Mouse Strains for Incompatibilities That Reproductively Isolate Their Wild Relatives
    Journal of Heredity 2007:98(2):115–122 ª The American Genetic Association. 2007. All rights reserved. doi:10.1093/jhered/esl064 For permissions, please email: journals.permissions@oxfordjournals.org. Advance Access publication January 5, 2007 Searching the Genomes of Inbred Mouse Strains for Incompatibilities That Reproductively Isolate Their Wild Relatives BRET A. PAYSEUR AND MICHAEL PLACE From the Laboratory of Genetics, University of Wisconsin, Madison, WI 53706. Address correspondence to the author at the address above, or e-mail: payseur@wisc.edu. Abstract Identification of the genes that underlie reproductive isolation provides important insights into the process of speciation. According to the Dobzhansky–Muller model, these genes suffer disrupted interactions in hybrids due to independent di- vergence in separate populations. In hybrid populations, natural selection acts to remove the deleterious heterospecific com- binations that cause these functional disruptions. When selection is strong, this process can maintain multilocus associations, primarily between conspecific alleles, providing a signature that can be used to locate incompatibilities. We applied this logic to populations of house mice that were formed by hybridization involving two species that show partial reproductive isolation, Mus domesticus and Mus musculus. Using molecular markers likely to be informative about species ancestry, we scanned the genomes of 1) classical inbred strains and 2) recombinant inbred lines for pairs of loci that showed extreme linkage disequi- libria. By using the same set of markers, we identified a list of locus pairs that displayed similar patterns in both scans. These genomic regions may contain genes that contribute to reproductive isolation between M. domesticus and M.
    [Show full text]
  • 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 (cevansmo@iu.edu) 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.
    [Show full text]
  • Supplementary Materials
    1 Supplementary Materials: Supplemental Figure 1. Gene expression profiles of kidneys in the Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice. (A) A heat map of microarray data show the genes that significantly changed up to 2 fold compared between Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice (N=4 mice per group; p<0.05). Data show in log2 (sample/wild-type). 2 Supplemental Figure 2. Sting signaling is essential for immuno-phenotypes of the Fcgr2b-/-lupus mice. (A-C) Flow cytometry analysis of splenocytes isolated from wild-type, Fcgr2b-/- and Fcgr2b-/-. Stinggt/gt mice at the age of 6-7 months (N= 13-14 per group). Data shown in the percentage of (A) CD4+ ICOS+ cells, (B) B220+ I-Ab+ cells and (C) CD138+ cells. Data show as mean ± SEM (*p < 0.05, **p<0.01 and ***p<0.001). 3 Supplemental Figure 3. Phenotypes of Sting activated dendritic cells. (A) Representative of western blot analysis from immunoprecipitation with Sting of Fcgr2b-/- mice (N= 4). The band was shown in STING protein of activated BMDC with DMXAA at 0, 3 and 6 hr. and phosphorylation of STING at Ser357. (B) Mass spectra of phosphorylation of STING at Ser357 of activated BMDC from Fcgr2b-/- mice after stimulated with DMXAA for 3 hour and followed by immunoprecipitation with STING. (C) Sting-activated BMDC were co-cultured with LYN inhibitor PP2 and analyzed by flow cytometry, which showed the mean fluorescence intensity (MFI) of IAb expressing DC (N = 3 mice per group). 4 Supplemental Table 1. Lists of up and down of regulated proteins Accession No.
    [Show full text]
  • Novocib Nucleoside Kinases
    PRECICE ® Services Information sheet Nucleoside kinases, rate-limiting step of nucleoside analogues activation Nucleoside analogues have proven to be a highly successful class of anti-cancer and anti-viral drugs. The therapeutic efficacy of nucleoside analogues is dependent of their intracellular phosphorylation. Two cellular nucleoside kinases, deoxycytidine kinase (dCK) and UMP-CMP kinase (CMK) are critical for phosphorylation of cytidine analogues. These kinases provide two first steps of activation of highly effective anti-cancer and anti-viral drugs, such as 1-β-D- arabinofuranosylcytosine (araC, aracytidine ), 2’,2’difluorodeoxycytidine (dFdC, gemcitabine ), β-D-2’3’- dideoxycytidine (ddC). Both kinases phosphorylate unnatural L-nucleosides (e.g., β-L-2’3’-dideoxy-3’thiacytidine, L- SSdC, 3-TC or lamividune ). Kinetic constants of araC, dFdC and 3TC phosphorylation by recombinant dCK and UMP-CMPK have been published. The comparison of phosphorylation properties of new nucleoside analogues with those of known drugs provides the rational basis for selection of analogues of better therapeutic potential. To characterize the phosphorylation properties of new nucleoside analogues, Novo CIB has developed human recombinant dCK and human recombinant CMK nucleoside phosphorylation assays. As shown in Table 1, CMK assay must be performed with monophosphate forms of nucleoside analogues and requires preliminary phosphorylation of nucleoside analogues and their purification. To circumvent this time-consuming step, NovoCIB has developed a coupled dCK-CMK nucleoside phosphorylation assay that delivers in one step the critical information on both dCK and CMK substrate properties of nucleoside analogue. Ribavirin (1-β-D-ribofuranosyl-1,2,4-triazole-3-carboxamide) is a purine nucleoside analogue with a broad-spectrum antiviral activity.
    [Show full text]
  • Genes in a Refined Smith-Magenis Syndrome Critical Deletion Interval on Chromosome 17P11.2 and the Syntenic Region of the Mouse
    Downloaded from genome.cshlp.org on September 25, 2021 - Published by Cold Spring Harbor Laboratory Press Article Genes in a Refined Smith-Magenis Syndrome Critical Deletion Interval on Chromosome 17p11.2 and the Syntenic Region of the Mouse Weimin Bi,1,6 Jiong Yan,1,6 Paweł Stankiewicz,1 Sung-Sup Park,1,7 Katherina Walz,1 Cornelius F. Boerkoel,1 Lorraine Potocki,1,3 Lisa G. Shaffer,1 Koen Devriendt,4 Małgorzata J.M. Nowaczyk,5 Ken Inoue,1 and James R. Lupski1,2,3,8 Departments of 1Molecular & Human Genetics, 2Pediatrics, Baylor College of Medicine, 3Texas Children’s Hospital, Houston, Texas 77030, USA; 4Centre for Human Genetics, University Hospital Gasthuisberg, Catholic University of Leuven, B-3000 Leuven, Belgium; 5Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario L8S 4J9, Canada Smith-Magenis syndrome (SMS) is a multiple congenital anomaly/mental retardation syndrome associated with behavioral abnormalities and sleep disturbance. Most patients have the same ∼4 Mb interstitial genomic deletion within chromosome 17p11.2. To investigate the molecular bases of the SMS phenotype, we constructed BAC/PAC contigs covering the SMS common deletion interval and its syntenic region on mouse chromosome 11. Comparative genome analysis reveals the absence of all three ∼200-kb SMS-REP low-copy repeats in the mouse and indicates that the evolution of SMS-REPs was accompanied by transposition of adjacent genes. Physical and genetic map comparisons in humans reveal reduced recombination in both sexes. Moreover, by examining the deleted regions in SMS patients with unusual-sized deletions, we refined the minimal Smith-Magenis critical region (SMCR) to an ∼1.1-Mb genomic interval that is syntenic to an ∼1.0-Mb region in the mouse.
    [Show full text]
  • 1 Supporting Information for a Microrna Network Regulates
    Supporting Information for A microRNA Network Regulates Expression and Biosynthesis of CFTR and CFTR-ΔF508 Shyam Ramachandrana,b, Philip H. Karpc, Peng Jiangc, Lynda S. Ostedgaardc, Amy E. Walza, John T. Fishere, Shaf Keshavjeeh, Kim A. Lennoxi, Ashley M. Jacobii, Scott D. Rosei, Mark A. Behlkei, Michael J. Welshb,c,d,g, Yi Xingb,c,f, Paul B. McCray Jr.a,b,c Author Affiliations: Department of Pediatricsa, Interdisciplinary Program in Geneticsb, Departments of Internal Medicinec, Molecular Physiology and Biophysicsd, Anatomy and Cell Biologye, Biomedical Engineeringf, Howard Hughes Medical Instituteg, Carver College of Medicine, University of Iowa, Iowa City, IA-52242 Division of Thoracic Surgeryh, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Canada-M5G 2C4 Integrated DNA Technologiesi, Coralville, IA-52241 To whom correspondence should be addressed: Email: michael-welsh@uiowa.edu (M.J.W.); yi- xing@uiowa.edu (Y.X.); Email: paul-mccray@uiowa.edu (P.B.M.) This PDF file includes: Materials and Methods References Fig. S1. miR-138 regulates SIN3A in a dose-dependent and site-specific manner. Fig. S2. miR-138 regulates endogenous SIN3A protein expression. Fig. S3. miR-138 regulates endogenous CFTR protein expression in Calu-3 cells. Fig. S4. miR-138 regulates endogenous CFTR protein expression in primary human airway epithelia. Fig. S5. miR-138 regulates CFTR expression in HeLa cells. Fig. S6. miR-138 regulates CFTR expression in HEK293T cells. Fig. S7. HeLa cells exhibit CFTR channel activity. Fig. S8. miR-138 improves CFTR processing. Fig. S9. miR-138 improves CFTR-ΔF508 processing. Fig. S10. SIN3A inhibition yields partial rescue of Cl- transport in CF epithelia.
    [Show full text]
  • Functional Genomics Atlas of Synovial Fibroblasts Defining Rheumatoid Arthritis
    medRxiv preprint doi: https://doi.org/10.1101/2020.12.16.20248230; this version posted December 18, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Functional genomics atlas of synovial fibroblasts defining rheumatoid arthritis heritability Xiangyu Ge1*, Mojca Frank-Bertoncelj2*, Kerstin Klein2, Amanda Mcgovern1, Tadeja Kuret2,3, Miranda Houtman2, Blaž Burja2,3, Raphael Micheroli2, Miriam Marks4, Andrew Filer5,6, Christopher D. Buckley5,6,7, Gisela Orozco1, Oliver Distler2, Andrew P Morris1, Paul Martin1, Stephen Eyre1* & Caroline Ospelt2*,# 1Versus Arthritis Centre for Genetics and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK 2Department of Rheumatology, Center of Experimental Rheumatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland 3Department of Rheumatology, University Medical Centre, Ljubljana, Slovenia 4Schulthess Klinik, Zurich, Switzerland 5Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK 6NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust, University of Birmingham, Birmingham, UK 7Kennedy Institute of Rheumatology, University of Oxford Roosevelt Drive Headington Oxford UK *These authors contributed equally #corresponding author: caroline.ospelt@usz.ch NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. 1 medRxiv preprint doi: https://doi.org/10.1101/2020.12.16.20248230; this version posted December 18, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.
    [Show full text]
  • Supplementary File 2A Revised
    Supplementary file 2A. Differentially expressed genes in aldosteronomas compared to all other samples, ranked according to statistical significance. Missing values were not allowed in aldosteronomas, but to a maximum of five in the other samples. Acc UGCluster Name Symbol log Fold Change P - Value Adj. P-Value B R99527 Hs.8162 Hypothetical protein MGC39372 MGC39372 2,17 6,3E-09 5,1E-05 10,2 AA398335 Hs.10414 Kelch domain containing 8A KLHDC8A 2,26 1,2E-08 5,1E-05 9,56 AA441933 Hs.519075 Leiomodin 1 (smooth muscle) LMOD1 2,33 1,3E-08 5,1E-05 9,54 AA630120 Hs.78781 Vascular endothelial growth factor B VEGFB 1,24 1,1E-07 2,9E-04 7,59 R07846 Data not found 3,71 1,2E-07 2,9E-04 7,49 W92795 Hs.434386 Hypothetical protein LOC201229 LOC201229 1,55 2,0E-07 4,0E-04 7,03 AA454564 Hs.323396 Family with sequence similarity 54, member B FAM54B 1,25 3,0E-07 5,2E-04 6,65 AA775249 Hs.513633 G protein-coupled receptor 56 GPR56 -1,63 4,3E-07 6,4E-04 6,33 AA012822 Hs.713814 Oxysterol bining protein OSBP 1,35 5,3E-07 7,1E-04 6,14 R45592 Hs.655271 Regulating synaptic membrane exocytosis 2 RIMS2 2,51 5,9E-07 7,1E-04 6,04 AA282936 Hs.240 M-phase phosphoprotein 1 MPHOSPH -1,40 8,1E-07 8,9E-04 5,74 N34945 Hs.234898 Acetyl-Coenzyme A carboxylase beta ACACB 0,87 9,7E-07 9,8E-04 5,58 R07322 Hs.464137 Acyl-Coenzyme A oxidase 1, palmitoyl ACOX1 0,82 1,3E-06 1,2E-03 5,35 R77144 Hs.488835 Transmembrane protein 120A TMEM120A 1,55 1,7E-06 1,4E-03 5,07 H68542 Hs.420009 Transcribed locus 1,07 1,7E-06 1,4E-03 5,06 AA410184 Hs.696454 PBX/knotted 1 homeobox 2 PKNOX2 1,78 2,0E-06
    [Show full text]