Epigenetic Regulation (DNA Methylation, Histone Modifications
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Human Stem Cells from Single Blastomeres Reveal Pathways of Embryonic Or Trophoblast Fate Specification Tamara Zdravkovic1,2,3,4,5,‡, Kristopher L
© 2015. Published by The Company of Biologists Ltd | Development (2015) 142, 4010-4025 doi:10.1242/dev.122846 STEM CELLS AND REGENERATION RESEARCH ARTICLE Human stem cells from single blastomeres reveal pathways of embryonic or trophoblast fate specification Tamara Zdravkovic1,2,3,4,5,‡, Kristopher L. Nazor6,‡, Nicholas Larocque1,2,3,4,5, Matthew Gormley1,2,3,4,5, Matthew Donne1,2,3,7, Nathan Hunkapillar1,2,3,4,5, Gnanaratnam Giritharan8, Harold S. Bernstein4,9, Grace Wei4,10, Matthias Hebrok10, Xianmin Zeng11, Olga Genbacev1,2,3,4,5, Aras Mattis4,12, Michael T. McMaster4,5,13, Ana Krtolica8,*, Diana Valbuena14, Carlos Simón14, Louise C. Laurent6,15, Jeanne F. Loring6 and Susan J. Fisher1,2,3,4,5,7,§ ABSTRACT INTRODUCTION For many reasons, relatively little is known about human Mechanisms of initial cell fate decisions differ among species. To gain preimplantation development. The small number of cells makes insights into lineage allocation in humans, we derived ten human embryos of any species difficult to study. In humans, the technical embryonic stem cell lines (designated UCSFB1-10) from single difficulties are compounded by other challenges. Genetic variation blastomeres of four 8-cell embryos and one 12-cell embryo from a among individuals could contribute to developmental differences, a single couple. Compared with numerous conventional lines from well-appreciated phenomenon in the mouse (Dackor et al., 2009), blastocysts, they had unique gene expression and DNA methylation which is difficult to assess in humans owing to the limited patterns that were, in part, indicative of trophoblast competence. At a availability of embryos that are donated for research. -
Comparative Oncogenomics Identifies Tyrosine Kinase FES As a Tumor Suppressor in Melanoma
RESEARCH ARTICLE The Journal of Clinical Investigation Comparative oncogenomics identifies tyrosine kinase FES as a tumor suppressor in melanoma Michael Olvedy,1,2 Julie C. Tisserand,3 Flavie Luciani,1,2 Bram Boeckx,4,5 Jasper Wouters,6,7 Sophie Lopez,3 Florian Rambow,1,2 Sara Aibar,6,7 Bernard Thienpont,4,5 Jasmine Barra,1,2 Corinna Köhler,1,2 Enrico Radaelli,8 Sophie Tartare-Deckert,9 Stein Aerts,6,7 Patrice Dubreuil,3 Joost J. van den Oord,10 Diether Lambrechts,4,5 Paulo De Sepulveda,3 and Jean-Christophe Marine1,2 1Laboratory for Molecular Cancer Biology, Center for Cancer Biology, Vlaams Instituut voor Biotechnologie (VIB), Leuven, Belgium. 2Laboratory for Molecular Cancer Biology, Department of Oncology, KU Leuven, Leuven, Belgium. 3INSERM, Aix Marseille University, CNRS, Institut Paoli-Calmettes, CRCM, Equipe Labellisée Ligue Contre le Cancer, Marseille, France. 4Laboratory for Translational Genetics, Center for Cancer Biology, VIB, Leuven, Belgium. 5Laboratory for Translational Genetics, and 6Laboratory of Computational Biology, Department of Human Genetics, KU Leuven, Leuven, Belgium. 7Laboratory of Computational Biology, and 8Mouse Histopathology Core Facility, VIB Center for Brain & Disease Research, Leuven, Belgium. 9Centre Méditerranéen de Médecine Moléculaire (C3M), INSERM, U1065, Université Côte d’Azur, Nice, France. 10Laboratory of Translational Cell and Tissue Research, Department of Pathology, KU Leuven and UZ Leuven, Leuven, Belgium. Identification and functional validation of oncogenic drivers are essential steps toward -
An Ontogenetic Switch Drives the Positive and Negative Selection of B Cells
An ontogenetic switch drives the positive and negative selection of B cells Xijin Xua, Mukta Deobagkar-Lelea, Katherine R. Bulla, Tanya L. Crockforda, Adam J. Meadb, Adam P. Cribbsc, David Simsc, Consuelo Anzilottia, and Richard J. Cornalla,1 aMedical Research Council Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, OX3 9DS Oxford, United Kingdom; bMedical Research Council Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, OX3 9DS Oxford, United Kingdom; and cMedical Research Council, Weatherall Institute of Molecular Medicine, Centre for Computational Biology, Weatherall Institute of Molecular Medicine, University of Oxford, OX3 9DS Oxford, United Kingdom Edited by Michael Reth, University of Freiburg, Freiburg, Germany, and approved January 6, 2020 (received for review September 3, 2019) + Developing B cells can be positively or negatively selected by self- BM HSCs increased CD5 B-1a B cell development (15), while antigens, but the mechanisms that determine these outcomes are expression of let-7b in FL pro-B cells blocked the development of incompletely understood. Here, we show that a B cell intrinsic B-1 B cells (17). These findings support the notion of hard-wired switch between positive and negative selection during ontogeny differences during ontogeny, but possibly downstream of the HSC is determined by a change from Lin28b to let-7 gene expression. commitment stage. Ectopic expression of a Lin28b transgene in murine B cells restored Several lines of evidence also suggest that B-1 B cells can un- the positive selection of autoreactive B-1 B cells by self-antigen in dergo positive selection, which is linked to their B cell receptor adult bone marrow. -
Rare Variants in the DNA Repair Pathway and the Risk of Colorectal Cancer Marco Matejcic1, Hiba A
Author Manuscript Published OnlineFirst on February 24, 2021; DOI: 10.1158/1055-9965.EPI-20-1457 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Rare variants in the DNA repair pathway and the risk of colorectal cancer Marco Matejcic1, Hiba A. Shaban1, Melanie W. Quintana2, Fredrick R. Schumacher3,4, Christopher K. Edlund5, Leah Naghi6, Rish K. Pai7, Robert W. Haile8, A. Joan Levine8, Daniel D. Buchanan9,10,11, Mark A. Jenkins12, Jane C. Figueiredo13, Gad Rennert14, Stephen B. Gruber15, Li Li16, Graham Casey17, David V. Conti18†, Stephanie L. Schmit1,19† † These authors contributed equally to this work. Affiliations 1 Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL 33612, USA 2 Berry Consultants, Austin, TX, 78746, USA 3 Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH 44106, USA 4 Seidman Cancer Center, University Hospitals, Cleveland, OH 44106, USA 5 Department of Preventive Medicine, USC Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA 6 Department of Medicine, Montefiore Medical Center, Albert Einstein College of Medicine, NY 10467, USA 7 Department of Laboratory Medicine and Pathology, Mayo Clinic Arizona, Scottsdale, AZ 85259, USA 8 Department of Medicine, Research Center for Health Equity, Cedars-Sinai Samuel Oschin Comprehensive Cancer Center, Los Angeles, CA 90048, USA 9 Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria 3010, Australia 10 Victorian Comprehensive Cancer Centre, University of Melbourne, Centre for Cancer Research, Parkville, Victoria 3010, Australia 1 Downloaded from cebp.aacrjournals.org on September 29, 2021. -
A Sleeping Beauty Mutagenesis Screen Reveals a Tumor Suppressor
A Sleeping Beauty mutagenesis screen reveals a tumor PNAS PLUS suppressor role for Ncoa2/Src-2 in liver cancer Kathryn A. O’Donnella,b,1,2, Vincent W. Kengc,d,e, Brian Yorkf, Erin L. Reinekef, Daekwan Seog, Danhua Fanc,h, Kevin A. T. Silversteinc,h, Christina T. Schruma,b, Wei Rose Xiea,b,3, Loris Mularonii,j, Sarah J. Wheelani,j, Michael S. Torbensonk, Bert W. O’Malleyf, David A. Largaespadac,d,e, and Jef D. Boekea,b,i,2 Departments of aMolecular Biology and Genetics, iOncology, jDivision of Biostatistics and Bioinformatics, and kPathology and bThe High Throughput Biology Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21205; cMasonic Cancer Center, dDepartment of Genetics, Cell Biology, and Development, eCenter for Genome Engineering, and hBiostatistics and Bioinformatics Core, University of Minnesota, Minneapolis, MN 55455; fDepartment of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030; and gLaboratory of Experimental Carcinogenesis, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892 Edited by Harold Varmus, National Cancer Institute, Bethesda, MD, and approved March 23, 2012 (received for review September 21, 2011) The Sleeping Beauty (SB) transposon mutagenesis system is a pow- alterations have been documented in liver cancer, the key genetic erful tool that facilitates the discovery of mutations that accelerate alterations that drive hepatocellular transformation remain tumorigenesis. In this study, we sought to identify mutations that poorly understood. Nevertheless, a unifying feature of human cooperate with MYC, one of the most commonly dysregulated HCC is amplification or overexpression of the MYC oncogene (8, genes in human malignancy. -
Oncogenomics: Clinical Pathogenesis Approach
International Journal of Genetics, ISSN: 0975–2862, Volume 1, Issue 2, 2009, pp-25-43 Oncogenomics: Clinical pathogenesis approach Gupta G. 1, Gupta N. 2, Trivedi S. 3, Patil P. 5, Gupta M. 2, Jhadav A. 4, Vamsi K.K.6, Khairnar Y. 4, Boraste A. 4, Mujapara A.K. 7, Joshi B.8 1S.D.S.M. College Palghar, Mumbai 2Sindhu Mahavidyalaya Panchpaoli Nagpur 3V.V.P. Engineering College, Rajkot, Gujrat 4Padmashree Dr. D.Y. Patil University, Navi Mumbai, 400614, India 5Dr. D. Y. Patil ACS College, Pimpri, Pune 6Rai foundations College CBD Belapur Navi Mumbai 7Sir PP Institute of Science, Bhavnagar 8Rural College of Pharmacy, D.S Road, Bevanahalli, Banglore Abstract - Oncogenomics is new research sub-field of genomics, which applies high throughput technologies to characterize genes associated with cancer and synonymous with cancer genomics. The goal of oncogenomics is to identify new oncogenes or tumor suppressor genes that may provide new insights into cancer diagnosis, predicting clinical outcome of cancers, and new targets for cancer therapies. Oncoproteomics is the term used to describe the application of proteomic technologies in oncology and parallels the related field of oncogenomics. It is now contributing to the development of personalized management of cancer. Genomics has generated a wealth of data that is now being used to identify additional molecular alterations associated with cancer development. Mapping these alterations in the cancer genome is a critical first step in dissecting oncological pathways. Keywords - Biomarkers, Drug development, Drug resistance, Gene therapy, Oncogenomics Introduction Oncogenomics applies high throughput technologies to characterize genes associated transducing cellular signals of cell growth or with cancer and is used to identify new death. -
Appendix 2. Significantly Differentially Regulated Genes in Term Compared with Second Trimester Amniotic Fluid Supernatant
Appendix 2. Significantly Differentially Regulated Genes in Term Compared With Second Trimester Amniotic Fluid Supernatant Fold Change in term vs second trimester Amniotic Affymetrix Duplicate Fluid Probe ID probes Symbol Entrez Gene Name 1019.9 217059_at D MUC7 mucin 7, secreted 424.5 211735_x_at D SFTPC surfactant protein C 416.2 206835_at STATH statherin 363.4 214387_x_at D SFTPC surfactant protein C 295.5 205982_x_at D SFTPC surfactant protein C 288.7 1553454_at RPTN repetin solute carrier family 34 (sodium 251.3 204124_at SLC34A2 phosphate), member 2 238.9 206786_at HTN3 histatin 3 161.5 220191_at GKN1 gastrokine 1 152.7 223678_s_at D SFTPA2 surfactant protein A2 130.9 207430_s_at D MSMB microseminoprotein, beta- 99.0 214199_at SFTPD surfactant protein D major histocompatibility complex, class II, 96.5 210982_s_at D HLA-DRA DR alpha 96.5 221133_s_at D CLDN18 claudin 18 94.4 238222_at GKN2 gastrokine 2 93.7 1557961_s_at D LOC100127983 uncharacterized LOC100127983 93.1 229584_at LRRK2 leucine-rich repeat kinase 2 HOXD cluster antisense RNA 1 (non- 88.6 242042_s_at D HOXD-AS1 protein coding) 86.0 205569_at LAMP3 lysosomal-associated membrane protein 3 85.4 232698_at BPIFB2 BPI fold containing family B, member 2 84.4 205979_at SCGB2A1 secretoglobin, family 2A, member 1 84.3 230469_at RTKN2 rhotekin 2 82.2 204130_at HSD11B2 hydroxysteroid (11-beta) dehydrogenase 2 81.9 222242_s_at KLK5 kallikrein-related peptidase 5 77.0 237281_at AKAP14 A kinase (PRKA) anchor protein 14 76.7 1553602_at MUCL1 mucin-like 1 76.3 216359_at D MUC7 mucin 7, -
Single Cell Regulatory Landscape of the Mouse Kidney Highlights Cellular Differentiation Programs and Disease Targets
ARTICLE https://doi.org/10.1038/s41467-021-22266-1 OPEN Single cell regulatory landscape of the mouse kidney highlights cellular differentiation programs and disease targets Zhen Miao 1,2,3,8, Michael S. Balzer 1,2,8, Ziyuan Ma 1,2,8, Hongbo Liu1,2, Junnan Wu 1,2, Rojesh Shrestha 1,2, Tamas Aranyi1,2, Amy Kwan4, Ayano Kondo 4, Marco Pontoglio 5, Junhyong Kim6, ✉ Mingyao Li 7, Klaus H. Kaestner2,4 & Katalin Susztak 1,2,4 1234567890():,; Determining the epigenetic program that generates unique cell types in the kidney is critical for understanding cell-type heterogeneity during tissue homeostasis and injury response. Here, we profile open chromatin and gene expression in developing and adult mouse kidneys at single cell resolution. We show critical reliance of gene expression on distal regulatory elements (enhancers). We reveal key cell type-specific transcription factors and major gene- regulatory circuits for kidney cells. Dynamic chromatin and expression changes during nephron progenitor differentiation demonstrates that podocyte commitment occurs early and is associated with sustained Foxl1 expression. Renal tubule cells follow a more complex differentiation, where Hfn4a is associated with proximal and Tfap2b with distal fate. Mapping single nucleotide variants associated with human kidney disease implicates critical cell types, developmental stages, genes, and regulatory mechanisms. The single cell multi-omics atlas reveals key chromatin remodeling events and gene expression dynamics associated with kidney development. 1 Renal, Electrolyte, and Hypertension Division, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA. 2 Institute for Diabetes, Obesity, and Metabolism, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA. -
A KLF4/Pihl/EZH2/HMGA2 Regulatory Axis and Its Function in Promoting
Deng et al. Cell Death and Disease (2021) 12:485 https://doi.org/10.1038/s41419-021-03753-1 Cell Death & Disease ARTICLE Open Access A KLF4/PiHL/EZH2/HMGA2 regulatory axis and its function in promoting oxaliplatin-resistance of colorectal cancer Xuan Deng1, Fanyang Kong2,SiLi3,HaoqinJiang1,LiuDong1,XiaoXu1, Xinju Zhang1,HongYuan3,YingXu4, Yimin Chu4,HaixiaPeng4 andMingGuan 1 Abstract Long noncoding RNAs (lncRNAs) have emerged as a new class of regulatory molecules implicated in therapeutic resistance, yet the mechanisms underlying lncRNA-mediated oxaliplatin resistance in colorectal cancer (CRC) are poorly understood. In this study, lncRNA P53 inHibiting LncRNA (PiHL) was shown to be highly induced in oxaliplatin- resistant CRC cells and tumor tissues. In vitro and in vivo models clarified PiHL’s role in conferring resistance to oxaliplatin-induced apoptosis. PiHL antagonized chemosensitivity through binding with EZH2, repressing location of EZH2 to HMGA2 promoter, and downregulating methylation of histone H3 lysine 27 (H3K27me3) level in HMGA2 promoter, thus activating HMGA2 expression. Furthermore, HMGA2 upregulation induced by PiHL promotes PI3K/Akt phosphorylation, which resulted in increased oxaliplatin resistance. We also found that transcription factor KLF4 was downregulated in oxaliplatin-resistant cells, and KLF4 negatively regulated PiHL expression by binding to PiHL promoter. In vivo models further demonstrated that treatment of oxaliplatin-resistant CRC with locked nucleic acids targeting PiHL restored oxaliplatin response. Collectively, this study established lncRNA PiHL as a chemoresistance 1234567890():,; 1234567890():,; 1234567890():,; 1234567890():,; promoter in CRC, and targeting PiHL/EZH2/HMGA2/PI3K/Akt signaling axis represents a novel choice in the investigation of drug resistance. Introduction eventually cause cell cycle arrest and apoptosis2. -
Figure S17 Figure S16
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Published OnlineFirst April 9, 2015; DOI: 10.1158/0008-5472.CAN-14-2215 Cancer Tumor and Stem Cell Biology Research Lin28B/Let-7 Regulates Expression of Oct4 and Sox2 and Reprograms Oral Squamous Cell Carcinoma Cells to a Stem-like State Chian-Shiu Chien1, Mong-Lien Wang2,3, Pen-Yuan Chu4,5, Yuh-Lih Chang2,6, Wei-Hsiu Liu7, Cheng-Chia Yu8, Yuan-Tzu Lan3,6, Pin-I. Huang3,9, Yi-Yen Lee3,9, Yi-Wei Chen3,9, Wen-Liang Lo1,10, and Shih-Hwa Chiou2,3,4,6,11 Abstract Lin28, a key factor for cellular reprogramming and generation HMGA2 and suppressed their expression, whereas ARID3B and of induced pluripotent stem cell (iPSC), makes a critical con- HMGA2 increased the transcription of Oct4 and Sox2, respec- tribution to tumorigenicity by suppressing Let-7. However, it is tively, through promoter binding. Chromatin immunoprecipi- unclear whether Lin28 is involved in regulating cancer stem–like tation assays revealed a direct association between ARID3B and cells (CSC), including in oral squamous carcinoma cells aspecific ARID3B-binding sequence in the Oct4 promoter. (OSCC). In this study, we demonstrate a correlation between Notably, by modulating Oct4/Sox2 expression, the Lin28B–Let7 high levels of Lin28B, Oct4, and Sox2, and a high percentage of pathway not only regulated stemness properties in OSCC but þ þ CD44 ALDH1 CSC in OSCC. Ectopic Lin28B expression also determined the efficiency by which normal human oral À À in CD44 ALDH1 /OSCC cells was sufficient to enhance keratinocytes could be reprogrammed to iPSC. Clinically, a Oct4/Sox2 expression and CSC properties, whereas Let7 co- Lin28Bhigh-Let7low expression pattern was highly correlated with overexpression effectively reversed these phenomena. -
Supporting Information
Supporting Information Sutherland et al. 10.1073/pnas.1319963111 SI Materials and Methods (SPC) (rabbit polyclonal, 1:2,000, Chemicon), and anti-sex Histology and Immunohistochemistry. For histological analysis, determining region Y-box 2 (Sox2) (rabbit polyclonal, 1:1,000, lungs were inflated with ethanol–acetic acid–formalin (EAF) and Millipore). fixed for 24 h in EAF. Fixed tissues were subsequently dehy- Immunofluorescence Microscopy. For immunofluorescence mi- drated, embedded in paraffin, and sections (4 μm) prepared and + croscopy, Ad5–Cre-infected K-Raslox-Stop-lox-G12D/ lungs were stained by hematoxylin and eosin (H&E). For immunohisto- inflated and fixed with EAF overnight. Fixed lungs were em- chemistry, tissue sections were rehydrated, blocked in BSA con- bedded in paraffin. For immunofluorescence, tissue sections were taining PBS, and sequentially incubated with specific primary rehydrated, blocked in normal donkey serum containing PBS/ antibodies and with biotinylated secondary antibodies (DAKO). 0.2% tween-20, and incubated with specific primary antibodies Streptavidin-peroxidase (DAKO) or Powervision Poly-HRP (Leica and with Alexa Fluor-coupled secondary antibodies. Paraffin Microsystems) was used for visualization and diaminoben- sections were stained with the following primary antibodies: goat zidine as a chromagen (DAKO). The following antibodies were anti-CC10 (1:200; Santa Cruz: sc-9972) and rabbit anti–pro-SPC used: anti-Clara cell antigen 10 (CC10) (goat polyclonal, 1:5,000), (1:1,000; Chemicon; AB3786). Alexa Fluor-coupled secondary anti-high mobility group AT-hook 2 (Hmga2) (rabbit polyclonal, antibodies (Invitrogen) were used at a 1:200 dilution. Images 1:1,000, BioCheck: 59170AP), anti-NK2 homeobox 1 (Nkx2-1) were captured on a Leica SP5C Spectral Confocal Laser Scan- (mouse monoclonal, 1:1,000), anti–pro-Surfactant Protein C ning Microscope.