DOCSLIB.ORG

Exploration of Myeloid Cell Biology Using the Hoxb8 Technology

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

Exploration of Myeloid Cell Biology Using the Hoxb8 Technology Pui Y. Lee, MD PhD Boston Children’s Hospital BWH / Nigrovic Laboratory I. Introduction of the Hoxb8 system II. Example of studies using murine Hoxb8 cells III. The JBC Hoxb8 Core Schematic of Hematopoietic stem cell differentiation Hematopoietic stem cell Common lymphocyte progenitor Common myeloid Erythrocytes progenitor Megakaryocytes Eosinophils Granulocyte-monocyte progenitor Basophils Monocyte-dendritic cell progenitor Neutrophils Common monocyte Common DC progenitor progenitor monocytes dendritic cells Myeloid cells: immunity and inflammation • Integral components of the innate immune system • Maintain tissue homeostasis at steady-state • First wave responders during infection and inflammation • Arsenal of pro-inflammatory mediators • Bridge to adaptive immunity • Tissue repair and wound healing Myeloid cells and inflammatory diseases • Rheumatoid arthritis • Systemic lupus erythematosus • Crystal arthropathy • Autoinflammatory syndromes Challenges in studying myeloid cells 1. Difficult to maintain ex-vivo 2. Limitation in cell numbers 3. Limited capacity for manipulation (KI, KO, KD) 4. Confounding effects of oncogenes in cell lines HoxB8-ER Myeloid Progenitor Cells - HoxB8: nuclear homeobox protein that suppresses myeloid cell development - immortalization of bone marrow myeloid progenitors by HoxB8 overexpression - Retrovirus transduction of HoxB8 gene driven by estrogen receptor followed by selection in b-estradiol and SCF (Wang et.al, Nature Methods, 2006) - Spontaneous differentiation after estrogen withdrawal - Quantitative production of monocytes and neutrophils HoxB8 Myeloid Progenitor + estrogen Lin Sca-1 CD117 CD34 - estrogen 100 101 102 103 104 100 101 102 103 104 100 101 102 103 104 100 101 102 103 104 FcγRII/III CD135 Ly6C CD11b 100 101 102 103 104 100 101 102 103 104 100 101 102 103 104 100 101 102 103 104 Granulocytes Monocytes Differentiation of HoxB8 cells upon Estradiol Removal - maintenance: RPMI with 10% FCS, 500nM b-estradiol, 20nm SCF - differentiation: RPMI with 10% FCS, 2 nM SCF Day 0 Day 4 Day 8 100 CD11b 80 CD117 60 40 20 % of maximum MFImaximum of % 0 0 2 4 6 8 Day Generation of other myeloid lineages using HoxB8 progenitors Neutrophils (GCSF, D4) Macs/neutrophils (GMCSF, D6) Mast Cells (IL-3 + SCF, Day 23) Osteoclasts (MCSF + RANKL, D6) Neutrophils Monocytes Macrophages Basophils Mast cells Dendritic cells Osteoclasts Lymphocytes Advantages of the Hoxb8 system • Easy to establish, store, and maintain • Versatile and strain independent • Low cost and minimizes need for mice • Rapid expansion for large-scale studies • Compatible with genetic manipulation – shRNA, CRISPR, Cre-mediated deletion • In vivo differentiation upon i.v. transfer Limitations • No parallel system for human stem cells (yet) • ? differences compared to primary cells • Difficult to transfect (requires viral vectors) • Requires confirmation using primary cells and in vivo studies I. Introduction of the Hoxb8 system II. Example of studies using murine Hoxb8 cells III. The JBC Hoxb8 Core Monocyte differentiation in colors: Double Reporter HoxB8 cells - Derived from BM of CCR2-RFP / CX3CR1-GFP mice high + - - Immature monocytes: Ly6C CCR2 CX3CR1 - Mature monocytes: Ly6Clow CCR2- CX3CR1high Day 0 Day 2 Day 4 Day 6 Day 8 104 104 104 104 104 103 103 103 103 103 102 102 102 102 102 CX3CR1-GFP FITC-A CX3CR1-GFP FITC-A CX3CR1-GFP FITC-A CX3CR1-GFP FITC-A CX3CR1-GFP FITC-A CX3CR1-GFP 101 101 101 101 101 CX3CR1 0 0 0 0 0 CD115- 10 10 10 10 10 100 101 102 103 104 100 101 102 103 104 100 101 102 103 104 100 101 102 103 104 100 101 102 103 104 CCR2-RFP PerCP-Cy5-5-A CCR2-RFP PerCP-Cy5-5-A CCR2-RFP PerCP-Cy5-5-A CCR2-RFP PerCP-Cy5-5-A CCR2-RFP PerCP-Cy5-5-A CCR2 CD115+ 104 104 104 104 104 103 103 103 103 103 102 102 102 102 102 CX3CR1-GFP FITC-A CX3CR1-GFP FITC-A CX3CR1-GFP FITC-A CX3CR1-GFP FITC-A CX3CR1-GFP FITC-A CX3CR1-GFP 101 101 101 101 101 CX3CR1 100 100 100 100 100 100 101 102 103 104 100 101 102 103 104 100 101 102 103 104 100 101 102 103 104 100 101 102 103 104 Ly6CLy6C PE-Cy7-A Ly6C PE-Cy7-A Ly6C PE-Cy7-A Ly6C PE-Cy7-A Ly6C PE-Cy7-A 100 CCR2 80 CX3CR1 60 Ly6C 40 20 % of maximumMFI of % 0 0 2 4 6 8 10 Day Lee et al. Sci Immunol (in press) Small molecule library screening using DR-HoxB8 cells -150+ compounds (Caymen Biochem) targeting major signaling pathways including Akt, PKC, PKA, NFkB, JNK, ERK, MAPK, Ras, PI3K, mTOR, RIP, JAK/STAT - each compound initially tested at 10uM and 1uM, then titrated if necessary - DR-HoxB8 cells cultured with SCF + individual compounds; FACS analysis on day 4 Lee et al. Sci Immunol (in press) In vivo confirmation using Raptor conditional KO mice Raptor is a critical component of mTOR Complex 1 Peripheral blood Bone marrow Lee et al. Sci Immunol (in press) RNAseq: mTORC1 is required for physiologic down- regulation of c-Myc during myeloid differentiation Primary Myeloid progenitors (GMP) Hoxb8 cells +/- Rapamycin Raptor KO : mTORC1 deficient Rapamycin : mTORC1 inhibitor Tsc2 KO : mTOR overactivation Broad Smart Seq2 platform – 96 well format Lee et al. Sci Immunol (in press) mTORC1 is required for physiologic down-regulation of c-Myc during myeloid differentiation Myc-GFP Hoxb8 cells Wild-type Hoxb8 cells Rapamycin : mTORC1 inhibitor 10058-F4 : Myc Inhibitor SL0101-01 : S6 Kinase inhibitor Lee et al. Sci Immunol (in press) Generation of Hoxb8 cells from KO mice Wild-type RANKL -/- Defective osteoclast production in RankL -/- Hoxb8 cells - Cell lines can be generated from live or frozen bone marrow cells and fetal liver cells (for embryonically lethal KO strains) - 3-4 weeks from receiving primary cells to sufficient Hoxb8 cells for experiments CRISPR/Cas9 Genomic Editing using Hoxb8 cells http://www.doublexscience.org - Cas9-Hoxb8 cells generated from Cas9-KI mice (R. Platt and F. Zhang) - gRNA lentivirus synthesized by the Broad Institute (96 well format) I. Introduction of the Hoxb8 system II. Example of studies using murine Hoxb8 cells III. The JBC Hoxb8 Core The JBC Hoxb8 Core Consultation and Project planning Existing line Library stock Reestablish line Analysis by New line end-user Stem cell expansion User-supplied bone Retroviral infection Establish new line marrow cells / femur and selection Consultation, order Genetic Manipulation CRISPR gRNA or shRNA in bulk format, infection and selection *Hoxb8 vectors are under MTA with UCSD / MGH Hoxb8 Core Library of established Hoxb8 cell lines Wildtype strains: Reporter strains: Transgenics / KO strains: C57BL/6 CX3CR1 +/GFP CX3CR1 GFP/GFP PAD2 -/- Balb/C CCR2 +/RFP CCR2 RFP/RFP PTPN22 -/- SJL (CD45.1) LysM-GFP IRF8 -/- RANKL -/- MRL mpJ RFP-LC3-GFP IRF5 -/- MNK1/2 -/- Myc-GFP MyD88 -/- KLF4 -/- Dock2 -/- PAD4 -/- Raptor fl/fl MRL lpr Raptor fl/+ Ubc-Cre B6 lpr Rictor fl/fl BXSB-YAA RagA fl/f Hif1a fl/fl RagA fl/fl Ubc-Cre VHL fl/fl TSC-1 fl/fl Nlpr3 -/- TSC-1 LysM-Cre Caspase1 -/- TSC-1 -/- CD18 -/- Rbpj -/- Cas9-EGFP-KI Acknowledgement Nigrovic Lab BWH • Peter Nigrovic • Julia Charles • Sarah Ameri • Kevin Wei • Ally Morris • Adam Chicoine • Nate Nelson-Maney • Pierre Cunin MGH • Gang Li • David Sykes • Anais Levescot • Demetrios Kalaitizidis • Marta Martinez • David Scadden • Minah Iqbal Broad Institute • David Root Funding • NIH T32 (BCH Allergy / Immunology) • RRF Scientist Development Award.
Recommended publications
  • Detailed Review Paper on Retinoid Pathway Signalling

    Detailed Review Paper on Retinoid Pathway Signalling

    1 1 Detailed Review Paper on Retinoid Pathway Signalling 2 December 2020 3 2 4 Foreword 5 1. Project 4.97 to develop a Detailed Review Paper (DRP) on the Retinoid System 6 was added to the Test Guidelines Programme work plan in 2015. The project was 7 originally proposed by Sweden and the European Commission later joined the project as 8 a co-lead. In 2019, the OECD Secretariat was added to coordinate input from expert 9 consultants. The initial objectives of the project were to: 10 draft a review of the biology of retinoid signalling pathway, 11 describe retinoid-mediated effects on various organ systems, 12 identify relevant retinoid in vitro and ex vivo assays that measure mechanistic 13 effects of chemicals for development, and 14 Identify in vivo endpoints that could be added to existing test guidelines to 15 identify chemical effects on retinoid pathway signalling. 16 2. This DRP is intended to expand the recommendations for the retinoid pathway 17 included in the OECD Detailed Review Paper on the State of the Science on Novel In 18 vitro and In vivo Screening and Testing Methods and Endpoints for Evaluating 19 Endocrine Disruptors (DRP No 178). The retinoid signalling pathway was one of seven 20 endocrine pathways considered to be susceptible to environmental endocrine disruption 21 and for which relevant endpoints could be measured in new or existing OECD Test 22 Guidelines for evaluating endocrine disruption. Due to the complexity of retinoid 23 signalling across multiple organ systems, this effort was foreseen as a multi-step process.
  • Genetic Variability in the Italian Heavy Draught Horse from Pedigree Data and Genomic Information

    Genetic Variability in the Italian Heavy Draught Horse from Pedigree Data and Genomic Information

    Supplementary material for manuscript: Genetic variability in the Italian Heavy Draught Horse from pedigree data and genomic information. Enrico Mancin†, Michela Ablondi†, Roberto Mantovani*, Giuseppe Pigozzi, Alberto Sabbioni and Cristina Sartori ** Correspondence: [email protected] † These two Authors equally contributed to the work Supplementary Figure S1. Mares and foal of Italian Heavy Draught Horse (IHDH; courtesy of Cinzia Stoppa) Supplementary Figure S2. Number of Equivalent Generations (EqGen; above) and pedigree completeness (PC; below) over years in Italian Heavy Draught Horse population. Supplementary Table S1. Descriptive statistics of homozygosity (observed: Ho_obs; expected: Ho_exp; total: Ho_tot) in 267 genotyped individuals of Italian Heavy Draught Horse based on the number of homozygous genotypes. Parameter Mean SD Min Max Ho_obs 35,630.3 500.7 34,291 38,013 Ho_exp 35,707.8 64.0 35,010 35,740 Ho_tot 50,674.5 93.8 49,638 50,714 1 Definitions of the methods for inbreeding are in the text. Supplementary Figure S3. Values of BIC obtained by analyzing values of K from 1 to 10, corresponding on the same amount of clusters defining the proportion of ancestry in the 267 genotyped individuals. Supplementary Table S2. Estimation of genomic effective population size (Ne) traced back to 18 generations ago (Gen. ago). The linkage disequilibrium estimation, adjusted for sampling bias was also included (LD_r2), as well as the relative standard deviation (SD(LD_r2)). Gen. ago Ne LD_r2 SD(LD_r2) 1 100 0.009 0.014 2 108 0.011 0.018 3 118 0.015 0.024 4 126 0.017 0.028 5 134 0.019 0.031 6 143 0.021 0.034 7 156 0.023 0.038 9 173 0.026 0.041 11 189 0.029 0.046 14 213 0.032 0.052 18 241 0.036 0.058 Supplementary Table S3.
  • Genome-Wide DNA Methylation Analysis of KRAS Mutant Cell Lines Ben Yi Tew1,5, Joel K

    Genome-Wide DNA Methylation Analysis of KRAS Mutant Cell Lines Ben Yi Tew1,5, Joel K

    www.nature.com/scientificreports OPEN Genome-wide DNA methylation analysis of KRAS mutant cell lines Ben Yi Tew1,5, Joel K. Durand2,5, Kirsten L. Bryant2, Tikvah K. Hayes2, Sen Peng3, Nhan L. Tran4, Gerald C. Gooden1, David N. Buckley1, Channing J. Der2, Albert S. Baldwin2 ✉ & Bodour Salhia1 ✉ Oncogenic RAS mutations are associated with DNA methylation changes that alter gene expression to drive cancer. Recent studies suggest that DNA methylation changes may be stochastic in nature, while other groups propose distinct signaling pathways responsible for aberrant methylation. Better understanding of DNA methylation events associated with oncogenic KRAS expression could enhance therapeutic approaches. Here we analyzed the basal CpG methylation of 11 KRAS-mutant and dependent pancreatic cancer cell lines and observed strikingly similar methylation patterns. KRAS knockdown resulted in unique methylation changes with limited overlap between each cell line. In KRAS-mutant Pa16C pancreatic cancer cells, while KRAS knockdown resulted in over 8,000 diferentially methylated (DM) CpGs, treatment with the ERK1/2-selective inhibitor SCH772984 showed less than 40 DM CpGs, suggesting that ERK is not a broadly active driver of KRAS-associated DNA methylation. KRAS G12V overexpression in an isogenic lung model reveals >50,600 DM CpGs compared to non-transformed controls. In lung and pancreatic cells, gene ontology analyses of DM promoters show an enrichment for genes involved in diferentiation and development. Taken all together, KRAS-mediated DNA methylation are stochastic and independent of canonical downstream efector signaling. These epigenetically altered genes associated with KRAS expression could represent potential therapeutic targets in KRAS-driven cancer. Activating KRAS mutations can be found in nearly 25 percent of all cancers1.
  • SUPPLEMENTARY MATERIAL Bone Morphogenetic Protein 4 Promotes

    SUPPLEMENTARY MATERIAL Bone Morphogenetic Protein 4 Promotes

    www.intjdevbiol.com doi: 10.1387/ijdb.160040mk SUPPLEMENTARY MATERIAL corresponding to: Bone morphogenetic protein 4 promotes craniofacial neural crest induction from human pluripotent stem cells SUMIYO MIMURA, MIKA SUGA, KAORI OKADA, MASAKI KINEHARA, HIROKI NIKAWA and MIHO K. FURUE* *Address correspondence to: Miho Kusuda Furue. Laboratory of Stem Cell Cultures, National Institutes of Biomedical Innovation, Health and Nutrition, 7-6-8, Saito-Asagi, Ibaraki, Osaka 567-0085, Japan. Tel: 81-72-641-9819. Fax: 81-72-641-9812. E-mail: [email protected] Full text for this paper is available at: http://dx.doi.org/10.1387/ijdb.160040mk TABLE S1 PRIMER LIST FOR QRT-PCR Gene forward reverse AP2α AATTTCTCAACCGACAACATT ATCTGTTTTGTAGCCAGGAGC CDX2 CTGGAGCTGGAGAAGGAGTTTC ATTTTAACCTGCCTCTCAGAGAGC DLX1 AGTTTGCAGTTGCAGGCTTT CCCTGCTTCATCAGCTTCTT FOXD3 CAGCGGTTCGGCGGGAGG TGAGTGAGAGGTTGTGGCGGATG GAPDH CAAAGTTGTCATGGATGACC CCATGGAGAAGGCTGGGG MSX1 GGATCAGACTTCGGAGAGTGAACT GCCTTCCCTTTAACCCTCACA NANOG TGAACCTCAGCTACAAACAG TGGTGGTAGGAAGAGTAAAG OCT4 GACAGGGGGAGGGGAGGAGCTAGG CTTCCCTCCAACCAGTTGCCCCAAA PAX3 TTGCAATGGCCTCTCAC AGGGGAGAGCGCGTAATC PAX6 GTCCATCTTTGCTTGGGAAA TAGCCAGGTTGCGAAGAACT p75 TCATCCCTGTCTATTGCTCCA TGTTCTGCTTGCAGCTGTTC SOX9 AATGGAGCAGCGAAATCAAC CAGAGAGATTTAGCACACTGATC SOX10 GACCAGTACCCGCACCTG CGCTTGTCACTTTCGTTCAG Suppl. Fig. S1. Comparison of the gene expression profiles of the ES cells and the cells induced by NC and NC-B condition. Scatter plots compares the normalized expression of every gene on the array (refer to Table S3). The central line
  • A Conserved Tissue-Specific Homeodomain-Less Isoform of MEIS1 Is Downregulated in Colorectal Cancer

    A Conserved Tissue-Specific Homeodomain-Less Isoform of MEIS1 Is Downregulated in Colorectal Cancer

    Thomas Jefferson University Jefferson Digital Commons Department of Microbiology and Immunology Faculty Papers Department of Microbiology and Immunology 8-17-2011 A conserved tissue-specific homeodomain-less isoform of MEIS1 is downregulated in colorectal cancer. Richard C Crist Department of Microbiology and Immunology, Thomas Jefferson University, Philadelphia Jacquelyn J Roth Department of Microbiology and Immunology, Thomas Jefferson University, Philadelphia Scott A Waldman Department of Pharmacology and Experimental Therapeutics, Thomas Jefferson University, Philadelphia Arthur M Buchberg Department of Microbiology and Immunology, Thomas Jefferson University, Philadelphia Follow this and additional works at: https://jdc.jefferson.edu/mifp Part of the Gastroenterology Commons, Medical Genetics Commons, Medical Microbiology Commons, Oncology Commons, and the Pathology Commons Let us know how access to this document benefits ouy Recommended Citation Crist, Richard C; Roth, Jacquelyn J; Waldman, Scott A; and Buchberg, Arthur M, "A conserved tissue-specific homeodomain-less isoform of MEIS1 is downregulated in colorectal cancer." (2011). Department of Microbiology and Immunology Faculty Papers. Paper 25. https://jdc.jefferson.edu/mifp/25 This Article is brought to you for free and open access by the Jefferson Digital Commons. The Jefferson Digital Commons is a service of Thomas Jefferson University's Center for Teaching and Learning (CTL). The Commons is a showcase for Jefferson books and journals, peer-reviewed scholarly publications, unique historical collections from the University archives, and teaching tools. The Jefferson Digital Commons allows researchers and interested readers anywhere in the world to learn about and keep up to date with Jefferson scholarship. This article has been accepted for inclusion in Department of Microbiology and Immunology Faculty Papers by an authorized administrator of the Jefferson Digital Commons.
  • Expression Pattern of the Class I Homeobox Genes in Ovarian Carcinoma

    Expression Pattern of the Class I Homeobox Genes in Ovarian Carcinoma

    J Gynecol Oncol Vol. 21, No. 1:29-37, March 2010 DOI:10.3802/jgo.2010.21.1.29 Original Article Expression pattern of the class I homeobox genes in ovarian carcinoma Jin Hwa Hong1, Jae Kwan Lee1, Joong Jean Park2, Nak Woo Lee1, Kyu Wan Lee1, Jung Yeol Na1 Departments of 1Obstetrics and Gynecology, 2Physiology, Korea University College of Medicine, Seoul, Korea Objective: Although some sporadic reports reveal the link between the homeobox (HOX) genes and ovarian carcinoma, there is no comprehensive analysis of the expression pattern of the class I homeobox genes in ovarian carcinoma that determines the candidate genes involved in ovarian carcinogenesis. Methods: The different patterns of expression of 36 HOX genes were analyzed, including 4 ovarian cancer cell lines and 4 normal ovarian tissues. Using a reverse transcription-polymerase chain reaction (RT-PCR) and quantification analysis, the specific gene that showed a significantly higher expression in ovarian cancer cell lines than in normal ovaries was selected, and western blot analysis was performed adding 7 ovarian cancer tissue specimens. Finally, immunohistochemical and immunocytochemical analyses were performed to compare the pattern of expression of the specific HOX gene between ovarian cancer tissue and normal ovaries. Results: Among 36 genes, 11 genes had a different level of mRNA expression between the cancer cell lines and the normal ovarian tissues. Of the 11 genes, only HOXB4 had a significantly higher level of expression in ovarian cancer cell lines than in normal ovaries (p=0.029). Based on western blot, immunohistochemical, and immunocytochemical analyses, HOXB4 was expressed exclusively in the ovarian cancer cell lines or cancer tissue specimens, but not in the normal ovaries.
  • Targeting Chromatin Regulators Inhibits Leukemogenic Gene Expression in NPM1 Mutant Leukemia

    Targeting Chromatin Regulators Inhibits Leukemogenic Gene Expression in NPM1 Mutant Leukemia

    Published OnlineFirst August 17, 2016; DOI: 10.1158/2159-8290.CD-16-0237 RESEARCH ARTICLE Targeting Chromatin Regulators Inhibits Leukemogenic Gene Expression in NPM1 Mutant Leukemia Michael W.M. Kühn1,2, Evelyn Song1, Zhaohui Feng1, Amit Sinha1, Chun-Wei Chen1, Aniruddha J. Deshpande1, Monica Cusan1, Noushin Farnoud1, Annalisa Mupo3, Carolyn Grove4,5, Richard Koche1, James E. Bradner6, Elisa de Stanchina7, George S. Vassiliou3, Takayuki Hoshii1, and Scott A. Armstrong1,8 ABSTRACT Homeobox (HOX) proteins and the receptor tyrosine kinase FLT3 are frequently highly expressed and mutated in acute myeloid leukemia (AML). Aberrant HOX expression is found in nearly all AMLs that harbor a mutation in the Nucleophosmin (NPM1) gene, and FLT3 is concomitantly mutated in approximately 60% of these cases. Little is known about how mutant NPM1 (NPM1mut) cells maintain aberrant gene expression. Here, we demonstrate that the histone modi- fiers MLL1 and DOT1L controlHOX and FLT3 expression and differentiation in NPM1mut AML. Using a CRISPR/Cas9 genome editing domain screen, we show NPM1mut AML to be exceptionally dependent on the menin binding site in MLL1. Pharmacologic small-molecule inhibition of the menin–MLL1 protein interaction had profound antileukemic activity in human and murine models of NPM1mut AML. Combined pharmacologic inhibition of menin–MLL1 and DOT1L resulted in dramatic suppression of HOX and FLT3 expression, induction of differentiation, and superior activity against NPM1mut leukemia. SIGNIFICANCE: MLL1 and DOT1L are chromatin regulators that control HOX, MEIS1, and FLT3 expres- sion and are therapeutic targets in NPM1mut AML. Combinatorial small-molecule inhibition has synergistic on-target activity and constitutes a novel therapeutic concept for this common AML subtype.
  • Supplementary Table 1

    Supplementary Table 1

    Supplementary Table 1. 492 genes are unique to 0 h post-heat timepoint. The name, p-value, fold change, location and family of each gene are indicated. Genes were filtered for an absolute value log2 ration 1.5 and a significance value of p ≤ 0.05. Symbol p-value Log Gene Name Location Family Ratio ABCA13 1.87E-02 3.292 ATP-binding cassette, sub-family unknown transporter A (ABC1), member 13 ABCB1 1.93E-02 −1.819 ATP-binding cassette, sub-family Plasma transporter B (MDR/TAP), member 1 Membrane ABCC3 2.83E-02 2.016 ATP-binding cassette, sub-family Plasma transporter C (CFTR/MRP), member 3 Membrane ABHD6 7.79E-03 −2.717 abhydrolase domain containing 6 Cytoplasm enzyme ACAT1 4.10E-02 3.009 acetyl-CoA acetyltransferase 1 Cytoplasm enzyme ACBD4 2.66E-03 1.722 acyl-CoA binding domain unknown other containing 4 ACSL5 1.86E-02 −2.876 acyl-CoA synthetase long-chain Cytoplasm enzyme family member 5 ADAM23 3.33E-02 −3.008 ADAM metallopeptidase domain Plasma peptidase 23 Membrane ADAM29 5.58E-03 3.463 ADAM metallopeptidase domain Plasma peptidase 29 Membrane ADAMTS17 2.67E-04 3.051 ADAM metallopeptidase with Extracellular other thrombospondin type 1 motif, 17 Space ADCYAP1R1 1.20E-02 1.848 adenylate cyclase activating Plasma G-protein polypeptide 1 (pituitary) receptor Membrane coupled type I receptor ADH6 (includes 4.02E-02 −1.845 alcohol dehydrogenase 6 (class Cytoplasm enzyme EG:130) V) AHSA2 1.54E-04 −1.6 AHA1, activator of heat shock unknown other 90kDa protein ATPase homolog 2 (yeast) AK5 3.32E-02 1.658 adenylate kinase 5 Cytoplasm kinase AK7
  • Hoxb8 Requires Its Pbx-Interaction Motif to Block Di€Erentiation Of

    Hoxb8 Requires Its Pbx-Interaction Motif to Block Di€Erentiation Of

    Oncogene (2001) 20, 5440 ± 5448 ã 2001 Nature Publishing Group All rights reserved 0950 ± 9232/01 $15.00 www.nature.com/onc HoxB8 requires its Pbx-interaction motif to block dierentiation of primary myeloid progenitors and of most cell line models of myeloid dierentiation Paul S Knoep¯er2,3, David B Sykes1,3, Martina Pasillas1 and Mark P Kamps*,1 1Department of Pathology, University of California, San Diego, School of Medicine, 9500 Gilman Drive, La Jolla, California, CA 92093, USA; 2Department of Basic Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N., Seattle, Washington, WA 98109, USA HoxB8 was the ®rst homeobox gene identi®ed as a cause Introduction of leukemia. In murine WEHI3B acute myeloid leukemia (AML) cells, proviral integration leads to the expression Homeodomain (HD) proteins of the Hox, Pbx, and of both HoxB8 and Interleukin (IL-3). Enforced Meis families regulate gene expression in normal expression of HoxB8 blocks dierentiation of factor- development, and mutations that alter their expres- dependent myeloid progenitors, while IL-3 co-expression sion or function can lead to cancer. The mammalian induces autocrine proliferation and overt leukemogeni- Class I Hox genes are homologs of the Drosophila city. Previously, we demonstrated that HoxB8 binds homeobox genes located in the homeotic complex, DNA cooperatively with members of the Pbx family of and encode transcription factors that orchestrate transcription factors, and that HoxB8 makes contact anterior-posterior pattern formation (McGinnis and with the Pbx homeodomain through a hexameric Krumlauf, 1992), determine segmental identity during sequence designated the Pbx-interaction motif (PIM). embryogenesis (Krumlauf, 1994; Lewis, 1978) and E2a-Pbx1, an oncogenic derivative of Pbx1, both retains contribute to lineage-speci®c proliferation and/or its ability to heterodimerize with Hox proteins and arrest dierentiation of hematopoietic progenitors (Law- myeloid dierentiation.
  • Evidence for a Functional Role of Epigenetically Regulated Midcluster HOXB Genes in the Development of Barrett Esophagus

    Evidence for a Functional Role of Epigenetically Regulated Midcluster HOXB Genes in the Development of Barrett Esophagus

    Evidence for a functional role of epigenetically regulated midcluster HOXB genes in the development of Barrett esophagus Massimiliano di Pietroa, Pierre Lao-Sirieixa, Shelagh Boyleb, Andy Cassidyc, Dani Castillod, Amel Saadic, Ragnhild Eskelandb,1, and Rebecca C. Fitzgeralda,2 aMedical Research Council Cancer Cell Unit, Hutchison Medical Research Council Research Centre, CB2 0XZ Cambridge, United Kingdom; bMedical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, EH4 2XU Edinburgh, United Kingdom; cCancer Research United Kingdom, Cambridge Research Institute, Li Ka Shing Centre, CB2 0RE Cambridge, United Kingdom; and dSection of Gastrointestinal Surgery, Hospital Universitari del Mar, Universitat Autónoma de Barcelona, 08003 Barcelona, Spain Edited* by Walter Fred Bodmer, Weatherall Institute of Molecular Medicine, Oxford University, Oxford, United Kingdom, and approved April 18, 2012 (received for review October 17, 2011) Barrett esophagus (BE) is a human metaplastic condition that is the CDXs on their own are sufficient to induce an intestinal pheno- only known precursor to esophageal adenocarcinoma. BE is charac- type in the mouse esophagus. terized by a posterior intestinal-like phenotype in an anterior organ An intestinal-like epithelium in the esophagus is reminiscent of and therefore it is reminiscent of homeotic transformations, which homeotic transformations, which have been linked to mutations of can occur in transgenic animal models during embryonic develop- HOX genes (10). The 39 human HOX genes are divided into four ment as a consequence of mutations in HOX genes. In humans, clusters (HOXA, HOXB, HOXC, and HOXD) and have a collin- acquired deregulation of HOX genes during adulthood has been ear expression during development along the anterior-posterior linked to carcinogenesis; however, little is known about their role (A-P) axis, whereby 3′ end genes are activated earlier and are more in the pathogenesis of premalignant conditions.
  • Overview Gene List Target Scan Vs DIANA Group a Group B Group A

    Overview Gene List Target Scan Vs DIANA Group a Group B Group A

    Overview Gene list Target scan vs DIANA Group A Group B Group A hsa-miR-181a hsa-miR-323 hsa-miR-326 Target scan Diana microT Overlap Target scan Diana microT Overlap Target scan SEPT3 SEPT3 SEPT3 SEPT7 ADARB1 HPCAL4 ABHD2 ABL2 ABHD13 ACVR2A ADCYAP1R1 AKAP13 PDPK1 ACRBP ACAN ABI1 ADAMTS1 ALAD APOBR ACVRL1 ACCN2 ABLIM1 ADAMTSL1 ANKRD52 ATXN1 ADAM19 ACER3 ACSL1 AKAP7 ARID2 C18orf23,RNF165 ADAM33 ACVR2A ACTN2 ANKRD43 ARL3 C20orf29 ADAMTS2 ADAMTS1 ACVR2A AP1S3 ARRB1 CACNG4 AHCYL2 ADAMTS18 ACVR2B ARID2 BBC3 CCNJL ALOX15B ADAMTS5 ADAM11 ATP11A BTG1 CYP2E1 ANK1 ADAMTSL1 ADAM22 ATXN1 C18orf62 GNB1L ANKS6 ADARB1 ADAMTS1 B4GALT1 C1orf21 GPR61 APBA1 AFAP1 ADAMTS6 BAG4 CADM4 GTSE1 ARCN1 AFTPH ADAMTSL1 BAI3 CALML4 HPCAL4 ARHGEF37 AK3 ADCY9 BNC2 CAPN6 KIAA0152 ARID3B AKAP7 ADRBK1 BRD1 CBFA2T2 KIF1A ARL8A ANAPC16 AFF2 BRWD1 CEBPA MACF1 ATP2B2 ANK1 AHCTF1,AHCTF1PBTBD3 CHD1 MYO1D ATP6V1G2 ANKRD12 AKAP2,PALM2 C13orf23 CIT PCNT AUP1 ANKRD33B AKAP6 C14orf43 CLASP2 PDPK1 BCL2L2 ANKRD43 AKAP7 CAPRIN1 CLCN5 PLEKHG4B BHLHE40 ANKRD44 AKAP9 CARM1 CLIP3 PPARA BTBD3 ANKRD52 AKT3 CBX4 COL5A2 PRB1,PRB2,PRB4 BTRC AP1S3 ALG9 CCDC117 CTNS PTPRT C10orf26 APBA1 ANKRD13C CCNJ DCTN4 PYCR1 C14orf1 APLP2 ANKRD20B CDH13 DCUN1D4 RAPGEF1 C16orf45 APOO ANKRD43 CDON DDB1 SRCAP C16orf54 ARID2 ANKRD50 CDYL DDX39B TMEM63C C1orf106 ARL3 AP1G1 CEP350 DIP2C C1orf27 ARRDC3 AP1S3 CHD7 DNAJB3 C22orf29 ATF7 API5 CHIC1 EEPD1 C9orf3 ATG2B ARFGEF2 CLIP1 EIF2C1 CACNA1E ATG7 ARHGAP12 CNOT6L ELFN2 CAPN12 ATP11A ARHGAP26 CNR1 ELK1 CASKIN1 ATP2B3 ARHGAP29 CNTN4 FAM172A CBFA2T3 ATP8B2 ARHGEF3 CNTNAP2
  • Microrna-99 Family Members Suppress Homeobox A1 Expression in Epithelial Cells

    Microrna-99 Family Members Suppress Homeobox A1 Expression in Epithelial Cells

    MicroRNA-99 Family Members Suppress Homeobox A1 Expression in Epithelial Cells Dan Chen1,2, Zujian Chen1,3, Yi Jin1, Dragan Dragas1, Leitao Zhang1,4, Barima S. Adjei1, Anxun Wang1,2, Yang Dai5, Xiaofeng Zhou1,6,7* 1 Center for Molecular Biology of Oral Diseases, College of Dentistry, University of Illinois at Chicago, Chicago, Illinois, United States of America, 2 Department of Oral and Maxillofacial Surgery, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China, 3 Department of Anatomy and Cell Biology, Rush University Medical Center, Chicago, Illinois, United States of America, 4 Department of Oral and Maxillofacial Surgery, Nan Fang Hospital, Southern Medical University, Guangzhou, China, 5 Department of Bioengineering, College of Engineering, University of Illinois at Chicago, Chicago, Illinois, United States of America, 6 UIC Cancer Center, University of Illinois at Chicago, Chicago, Illinois, United States of America, 7 Department of Periodontics, College of Dentistry, University of Illinois at Chicago, Chicago, Illinois, United States of America Abstract The miR-99 family is one of the evolutionarily most ancient microRNA families, and it plays a critical role in developmental timing and the maintenance of tissue identity. Recent studies, including reports from our group, suggested that the miR-99 family regulates various physiological processes in adult tissues, such as dermal wound healing, and a number of disease processes, including cancer. By combining 5 independent genome-wide expression profiling experiments, we identified a panel of 266 unique transcripts that were down-regulated in epithelial cells transfected with miR-99 family members. A comprehensive bioinformatics analysis using 12 different sequence-based microRNA target prediction algorithms revealed that 81 out of these 266 down-regulated transcripts are potential direct targets for the miR-99 family.