The Mandibular and Hyoid Arches—From Molecular Patterning to Shaping Bone and Cartilage
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Core Transcriptional Regulatory Circuitries in Cancer
Oncogene (2020) 39:6633–6646 https://doi.org/10.1038/s41388-020-01459-w REVIEW ARTICLE Core transcriptional regulatory circuitries in cancer 1 1,2,3 1 2 1,4,5 Ye Chen ● Liang Xu ● Ruby Yu-Tong Lin ● Markus Müschen ● H. Phillip Koeffler Received: 14 June 2020 / Revised: 30 August 2020 / Accepted: 4 September 2020 / Published online: 17 September 2020 © The Author(s) 2020. This article is published with open access Abstract Transcription factors (TFs) coordinate the on-and-off states of gene expression typically in a combinatorial fashion. Studies from embryonic stem cells and other cell types have revealed that a clique of self-regulated core TFs control cell identity and cell state. These core TFs form interconnected feed-forward transcriptional loops to establish and reinforce the cell-type- specific gene-expression program; the ensemble of core TFs and their regulatory loops constitutes core transcriptional regulatory circuitry (CRC). Here, we summarize recent progress in computational reconstitution and biologic exploration of CRCs across various human malignancies, and consolidate the strategy and methodology for CRC discovery. We also discuss the genetic basis and therapeutic vulnerability of CRC, and highlight new frontiers and future efforts for the study of CRC in cancer. Knowledge of CRC in cancer is fundamental to understanding cancer-specific transcriptional addiction, and should provide important insight to both pathobiology and therapeutics. 1234567890();,: 1234567890();,: Introduction genes. Till now, one critical goal in biology remains to understand the composition and hierarchy of transcriptional Transcriptional regulation is one of the fundamental mole- regulatory network in each specified cell type/lineage. -
Accumulation of Rare Coding Variants in Genes Implicated in Risk of Human Cleft Lip with Or Without Cleft Palate
HHS Public Access Author manuscript Author ManuscriptAuthor Manuscript Author Am J Med Manuscript Author Genet A. Author Manuscript Author manuscript; available in PMC 2020 July 01. Published in final edited form as: Am J Med Genet A. 2019 July ; 179(7): 1260–1269. doi:10.1002/ajmg.a.61183. Accumulation of Rare Coding Variants in Genes Implicated in Risk of Human Cleft Lip with or without Cleft Palate Nicholas J. Marini1,*, Kripa Asrani1, Wei Yang2, Jasper Rine1, Gary M Shaw2 1California Institute for Quantitative Biosciences, Department of Molecular and Cellular Biology, University of California, Berkeley, CA 94720, USA 2Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA Abstract Cleft lip with/without cleft palate (CLP) is a common craniofacial malformation with complex etiologies, reflecting both genetic and environmental factors. Most of the suspected genetic risk for CLP has yet to be identified. To further classify risk loci and estimate the contribution of rare variants, we sequenced the exons in 49 candidate genes in 323 CLP cases and 211 non-malformed controls. Our findings indicated that rare, protein-altering variants displayed markedly higher burdens in CLP cases at relevant loci. First, putative loss-of-function mutations (nonsense, frameshift) were significantly enriched among cases: 13 of 323 cases (~4%) harbored such alleles within these 49 genes, versus one such change in controls (p = 0.01). Second, in gene-level analyses, the burden of rare alleles showed greater case-association for several genes previously implicated in cleft risk. For example, BHMT displayed a 10-fold increase in protein-altering variants in CLP cases (p = 0.03), including multiple case occurrences of a rare frameshift mutation (K400fs). -
Endothelium in the Pharyngeal Arches 3, 4 and 6 Is Derived from the Second Heart Field
Thomas Jefferson University Jefferson Digital Commons Center for Translational Medicine Faculty Papers Center for Translational Medicine 1-15-2017 Endothelium in the pharyngeal arches 3, 4 and 6 is derived from the second heart field. Xia Wang Thomas Jefferson University Dongying Chen Thomas Jefferson University Kelley Chen Thomas Jefferson University Ali Jubran Thomas Jefferson University AnnJosette Ramirez Thomas Jefferson University Follow this and additional works at: https://jdc.jefferson.edu/transmedfp Part of the Translational Medical Research Commons LetSee next us page know for additional how authors access to this document benefits ouy Recommended Citation Wang, Xia; Chen, Dongying; Chen, Kelley; Jubran, Ali; Ramirez, AnnJosette; and Astrof, Sophie, "Endothelium in the pharyngeal arches 3, 4 and 6 is derived from the second heart field." (2017). Center for Translational Medicine Faculty Papers. Paper 45. https://jdc.jefferson.edu/transmedfp/45 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 Center for Translational Medicine Faculty Papers by an authorized administrator of the Jefferson Digital Commons. For more information, please contact: [email protected]. Authors Xia Wang, Dongying Chen, Kelley Chen, Ali Jubran, AnnJosette Ramirez, and Sophie Astrof This article is available at Jefferson Digital Commons: https://jdc.jefferson.edu/transmedfp/45 HHS Public Access Author manuscript Author ManuscriptAuthor Manuscript Author Dev Biol Manuscript Author . -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4). -
Supplemental Materials ZNF281 Enhances Cardiac Reprogramming
Supplemental Materials ZNF281 enhances cardiac reprogramming by modulating cardiac and inflammatory gene expression Huanyu Zhou, Maria Gabriela Morales, Hisayuki Hashimoto, Matthew E. Dickson, Kunhua Song, Wenduo Ye, Min S. Kim, Hanspeter Niederstrasser, Zhaoning Wang, Beibei Chen, Bruce A. Posner, Rhonda Bassel-Duby and Eric N. Olson Supplemental Table 1; related to Figure 1. Supplemental Table 2; related to Figure 1. Supplemental Table 3; related to the “quantitative mRNA measurement” in Materials and Methods section. Supplemental Table 4; related to the “ChIP-seq, gene ontology and pathway analysis” and “RNA-seq” and gene ontology analysis” in Materials and Methods section. Supplemental Figure S1; related to Figure 1. Supplemental Figure S2; related to Figure 2. Supplemental Figure S3; related to Figure 3. Supplemental Figure S4; related to Figure 4. Supplemental Figure S5; related to Figure 6. Supplemental Table S1. Genes included in human retroviral ORF cDNA library. Gene Gene Gene Gene Gene Gene Gene Gene Symbol Symbol Symbol Symbol Symbol Symbol Symbol Symbol AATF BMP8A CEBPE CTNNB1 ESR2 GDF3 HOXA5 IL17D ADIPOQ BRPF1 CEBPG CUX1 ESRRA GDF6 HOXA6 IL17F ADNP BRPF3 CERS1 CX3CL1 ETS1 GIN1 HOXA7 IL18 AEBP1 BUD31 CERS2 CXCL10 ETS2 GLIS3 HOXB1 IL19 AFF4 C17ORF77 CERS4 CXCL11 ETV3 GMEB1 HOXB13 IL1A AHR C1QTNF4 CFL2 CXCL12 ETV7 GPBP1 HOXB5 IL1B AIMP1 C21ORF66 CHIA CXCL13 FAM3B GPER HOXB6 IL1F3 ALS2CR8 CBFA2T2 CIR1 CXCL14 FAM3D GPI HOXB7 IL1F5 ALX1 CBFA2T3 CITED1 CXCL16 FASLG GREM1 HOXB9 IL1F6 ARGFX CBFB CITED2 CXCL3 FBLN1 GREM2 HOXC4 IL1F7 -
Pharyngeal Arch Cheat Sheet V3
Pharyngeal Arches v3 (updates in red) Each pharyngeal arch contains: (1) a skeletal component (early on, a cartilaginous rod); (2) a muscular component; (3) an aortic arch; and (4) a nerve. Pharyngeal Arch Skeletal Component Muscles Aortic Arch Nerve First P. Arch Meckel's cartilage (malleus, incus) mm. of mastication, ant. belly 1st aortic arch Trigeminal N “mandibular maxillary prominence (maxilla*) of digastric, mylohyoid, tensor (maxillary AA) V2 and V3 arch” mandibular prominence (mandible*) tympani, tensor veli palatini Second P. Arch Reichert's cartilage (stapes, styloid mm. of facial expression, 2nd aortic arch Facial N “hyoid arch” process, stylohyoid lig.) buccinator, platysma, stapedius, (stapedial AA) VII hyoid, lesser cornua & superior body stylohyoid, post. belly of digastric Third P. Arch hyoid, greater cornua & inferior body stylopharyngeus 3rd aortic arch Glossophar. N (common carotids) IX Fourth P. Arch thyroid cartilage, epiglottic cartilage† cricothyroid, all intrinsic mm. 4th aortic arch Vagus: SLN of soft palate except tensor (aorta, R subclav.‡) & pharyn. plex. veli palatini X Fifth P. Arch - no derivatives - Sixth P. Arch cricoid, arytenoid, and corniculate all intrinsic mm. of larynx 6th aortic arch Vagus: RLN cartilages† except cricothyroid (pulmonary AA, X ductus arteriosus) * The maxillary and mandibular prominences are modeled on the first arch, but the bones develop separately from the first arch cartilage. † According to some sources the corniculate and cuneiform cartilages are derived from the 4th arch, not the 6th; I may revise this later on. ‡ Right subclavian A is derived from 4th aortic arch, right dorsal aorta, and right 7th intersegmental A; left subclavian A is derived from left 7th intersegmental A only, with no aortic arch component. -
Deep Neck Infections 55
Deep Neck Infections 55 Behrad B. Aynehchi Gady Har-El Deep neck space infections (DNSIs) are a relatively penetrating trauma, surgical instrument trauma, spread infrequent entity in the postpenicillin era. Their occur- from superfi cial infections, necrotic malignant nodes, rence, however, poses considerable challenges in diagnosis mastoiditis with resultant Bezold abscess, and unknown and treatment and they may result in potentially serious causes (3–5). In inner cities, where intravenous drug or even fatal complications in the absence of timely rec- abuse (IVDA) is more common, there is a higher preva- ognition. The advent of antibiotics has led to a continu- lence of infections of the jugular vein and carotid sheath ing evolution in etiology, presentation, clinical course, and from contaminated needles (6–8). The emerging practice antimicrobial resistance patterns. These trends combined of “shotgunning” crack cocaine has been associated with with the complex anatomy of the head and neck under- retropharyngeal abscesses as well (9). These purulent col- score the importance of clinical suspicion and thorough lections from direct inoculation, however, seem to have a diagnostic evaluation. Proper management of a recog- more benign clinical course compared to those spreading nized DNSI begins with securing the airway. Despite recent from infl amed tissue (10). Congenital anomalies includ- advances in imaging and conservative medical manage- ing thyroglossal duct cysts and branchial cleft anomalies ment, surgical drainage remains a mainstay in the treat- must also be considered, particularly in cases where no ment in many cases. apparent source can be readily identifi ed. Regardless of the etiology, infection and infl ammation can spread through- Q1 ETIOLOGY out the various regions via arteries, veins, lymphatics, or direct extension along fascial planes. -
Bedside Neuro-Otological Examination and Interpretation of Commonly
J Neurol Neurosurg Psychiatry: first published as 10.1136/jnnp.2004.054478 on 24 November 2004. Downloaded from BEDSIDE NEURO-OTOLOGICAL EXAMINATION AND INTERPRETATION iv32 OF COMMONLY USED INVESTIGATIONS RDavies J Neurol Neurosurg Psychiatry 2004;75(Suppl IV):iv32–iv44. doi: 10.1136/jnnp.2004.054478 he assessment of the patient with a neuro-otological problem is not a complex task if approached in a logical manner. It is best addressed by taking a comprehensive history, by a Tphysical examination that is directed towards detecting abnormalities of eye movements and abnormalities of gait, and also towards identifying any associated otological or neurological problems. This examination needs to be mindful of the factors that can compromise the value of the signs elicited, and the range of investigative techniques available. The majority of patients that present with neuro-otological symptoms do not have a space occupying lesion and the over reliance on imaging techniques is likely to miss more common conditions, such as benign paroxysmal positional vertigo (BPPV), or the failure to compensate following an acute unilateral labyrinthine event. The role of the neuro-otologist is to identify the site of the lesion, gather information that may lead to an aetiological diagnosis, and from there, to formulate a management plan. c BACKGROUND Balance is maintained through the integration at the brainstem level of information from the vestibular end organs, and the visual and proprioceptive sensory modalities. This processing takes place in the vestibular nuclei, with modulating influences from higher centres including the cerebellum, the extrapyramidal system, the cerebral cortex, and the contiguous reticular formation (fig 1). -
Association of Gene Ontology Categories with Decay Rate for Hepg2 Experiments These Tables Show Details for All Gene Ontology Categories
Supplementary Table 1: Association of Gene Ontology Categories with Decay Rate for HepG2 Experiments These tables show details for all Gene Ontology categories. Inferences for manual classification scheme shown at the bottom. Those categories used in Figure 1A are highlighted in bold. Standard Deviations are shown in parentheses. P-values less than 1E-20 are indicated with a "0". Rate r (hour^-1) Half-life < 2hr. Decay % GO Number Category Name Probe Sets Group Non-Group Distribution p-value In-Group Non-Group Representation p-value GO:0006350 transcription 1523 0.221 (0.009) 0.127 (0.002) FASTER 0 13.1 (0.4) 4.5 (0.1) OVER 0 GO:0006351 transcription, DNA-dependent 1498 0.220 (0.009) 0.127 (0.002) FASTER 0 13.0 (0.4) 4.5 (0.1) OVER 0 GO:0006355 regulation of transcription, DNA-dependent 1163 0.230 (0.011) 0.128 (0.002) FASTER 5.00E-21 14.2 (0.5) 4.6 (0.1) OVER 0 GO:0006366 transcription from Pol II promoter 845 0.225 (0.012) 0.130 (0.002) FASTER 1.88E-14 13.0 (0.5) 4.8 (0.1) OVER 0 GO:0006139 nucleobase, nucleoside, nucleotide and nucleic acid metabolism3004 0.173 (0.006) 0.127 (0.002) FASTER 1.28E-12 8.4 (0.2) 4.5 (0.1) OVER 0 GO:0006357 regulation of transcription from Pol II promoter 487 0.231 (0.016) 0.132 (0.002) FASTER 6.05E-10 13.5 (0.6) 4.9 (0.1) OVER 0 GO:0008283 cell proliferation 625 0.189 (0.014) 0.132 (0.002) FASTER 1.95E-05 10.1 (0.6) 5.0 (0.1) OVER 1.50E-20 GO:0006513 monoubiquitination 36 0.305 (0.049) 0.134 (0.002) FASTER 2.69E-04 25.4 (4.4) 5.1 (0.1) OVER 2.04E-06 GO:0007050 cell cycle arrest 57 0.311 (0.054) 0.133 (0.002) -
FOXE1-Dependent Regulation of Macrophage Chemotaxis by Thyroid Cells in Vitro and in Vivo
International Journal of Molecular Sciences Article FOXE1-Dependent Regulation of Macrophage Chemotaxis by Thyroid Cells In Vitro and In Vivo Sara C. Credendino 1,2, Marta De Menna 1,3, Irene Cantone 1 , Carmen Moccia 1 , Matteo Esposito 1, Luigi Di Guida 1, Mario De Felice 1,2 and Gabriella De Vita 1,* 1 Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, 80131 Naples, Italy; [email protected] (S.C.C.); [email protected] (M.D.M.); [email protected] (I.C.); [email protected] (C.M.); [email protected] (M.E.); [email protected] (L.D.G.); [email protected] (M.D.F.) 2 Institute of Experimental Endocrinology and Oncology “G. Salvatore”, National Research Council (CNR), 80131 Naples, Italy 3 DBMR-Department for BioMedical Research, University of Bern, 3012 Bern, Switzerland * Correspondence: [email protected]; Tel.: +39-081-746-3240 Abstract: Forkhead box E1 (FOXE1) is a lineage-restricted transcription factor involved in thyroid cancer susceptibility. Cancer-associated polymorphisms map in regulatory regions, thus affecting the extent of gene expression. We have recently shown that genetic reduction of FOXE1 dosage modifies multiple thyroid cancer phenotypes. To identify relevant effectors playing roles in thyroid cancer development, here we analyse FOXE1-induced transcriptional alterations in thyroid cells that do not express endogenous FOXE1. Expression of FOXE1 elicits cell migration, while transcriptome analysis reveals that several immune cells-related categories are highly enriched in differentially Citation: Credendino, S.C.; expressed genes, including several upregulated chemokines involved in macrophage recruitment. De Menna, M.; Cantone, I.; Moccia, C.; Accordingly, FOXE1-expressing cells induce chemotaxis of co-cultured monocytes. -
Supplemental Methods Proband and Control Lung Samples Lung Sections from Both the Proband and Age-Matched Controls Were Obtained
Supplementary material J Med Genet Supplemental Methods Proband and Control Lung Samples Lung sections from both the proband and age-matched controls were obtained in the form of fixed formalin paraffin embedded (FFPE) samples. Control lung samples were obtained from the BRINDL biorepository at the University of Rochester(1). RNA expression analyses RNA was obtained for mRNA expression studies using the RNeasy FFPE kit (Qiagen) according to manufacturer’s instructions. cDNA was then generated using iScrpit kit (biorad), and quantitative PCR was done as previously published (2). Primers for qPCR are listed in supplemental table 1. Chromatin Immunoprecipitation of FFPE for Fixed Formalin Paraffin Embedded samples Chromatin immunoprecipitation was done on FFPE sections using a protocol modified from Fanelli and colleagues, Nature Methods, 2011(3) Samples were deparaffinized by incubating 10uM sections in 1ml of Xylene for 10 minutes at room temperature. The tissue was then pelleted at 17,000 x gravity for 3 min at room temperature. This process was repeated 3 times. Samples were then rehydrated by incubating with 1 ml of 100% Ethanol for 10 minutes at RT. Cells were pelleted and resuspended in progressively increasing percentage of water as follows: 95% ethanol, 70% ethanol, 50% ethanol, 20% ethanol. The sample was then resuspended in 1x PBS and the tissue dissociated by sonicating with a Bioruptor (Diagnode, NJ USA) for 30 seconds on the medium setting. Cells then resuspended in Collagenase digestion buffer and treated with collagenase A (Roche 11 088 785 103) to a final concentration of 2mg/ml and digested at 37 C for 45 minutes.