The Multifaceted Output of C-Jun Biological Activity: Focus at the Junction of CD8 T Cell Activation and Exhaustion
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Down-Regulation of Stem Cell Genes, Including Those in a 200-Kb Gene Cluster at 12P13.31, Is Associated with in Vivo Differentiation of Human Male Germ Cell Tumors
Research Article Down-Regulation of Stem Cell Genes, Including Those in a 200-kb Gene Cluster at 12p13.31, Is Associated with In vivo Differentiation of Human Male Germ Cell Tumors James E. Korkola,1 Jane Houldsworth,1,2 Rajendrakumar S.V. Chadalavada,1 Adam B. Olshen,3 Debbie Dobrzynski,2 Victor E. Reuter,4 George J. Bosl,2 and R.S.K. Chaganti1,2 1Cell Biology Program and Departments of 2Medicine, 3Epidemiology and Biostatistics, and 4Pathology, Memorial Sloan-Kettering Cancer Center, New York, New York Abstract on the degree and type of differentiation (i.e., seminomas, which Adult male germ cell tumors (GCTs) comprise distinct groups: resemble undifferentiated primitive germ cells, and nonseminomas, seminomas and nonseminomas, which include pluripotent which show varying degrees of embryonic and extraembryonic embryonal carcinomas as well as other histologic subtypes patterns of differentiation; refs. 2, 3). Nonseminomatous GCTs are exhibiting various stages of differentiation. Almost all GCTs further subdivided into embryonal carcinomas, which show early show 12p gain, but the target genes have not been clearly zygotic or embryonal-like differentiation, yolk sac tumors and defined. To identify 12p target genes, we examined Affymetrix choriocarcinomas, which exhibit extraembryonal forms of differ- (Santa Clara, CA) U133A+B microarray (f83% coverage of 12p entiation, and teratomas, which show somatic differentiation along genes) expression profiles of 17 seminomas, 84 nonseminoma multiple lineages (3). Both seminomas and embryonal carcinoma GCTs, and 5 normal testis samples. Seventy-three genes on 12p are known to express stem cell markers, such as POU5F1 (4) and were significantly overexpressed, including GLUT3 and REA NANOG (5). -
TOX2 Is Differentially Expressed in Non-Small Cell Lung Cancer-PDF 092220
1 Tox2 is differentially expressed in non-small cell lung cancer and associates with patient 2 survival. 3 Shahan Mamoor1 4 [email protected] East Islip, NY USA 5 6 Non-small cell lung cancer (NSCLC) is the leading cause of cancer death in the United States1. 7 We mined published microarray data2,3,4 to identify differentially expressed genes in NSCLC. 8 We found that the gene encoding the thymyocyte selection-associated high mobility box protein 9 family member 2 transcription factor Tox2 was among the genes whose expression was most quantitatively different in tumors from patients with NSCLC as compared to the lung. Tox2 10 expression was significantly decreased in NSCLC tumors as compared to the lung, and lower 11 expression of Tox2 in patient tumors was significantly associated with worse overall survival. Tox2 may be important for initiation or progression of non-small cell lung cancer in humans. 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 Keywords: Tox2, NSCLC, non-small cell lung cancer, systems biology of NSCLC, targeted 27 therapeutics in NSCLC. 28 1 OF 16 1 In 2016, lung cancer resulted in the death of 158,000 Americans; 81% of all patients 2 diagnosed with lung cancer will expire within 5 years5. Non-small cell lung cancer (NSCLC) is 3 4 the most common type of lung cancer, diagnosed in 84% of patients with lung cancer, and 76% 5 of all patients with NSCLC will expire within 5 years5. The rational development of targeted 6 therapeutics to treat patients with NSCLC can be supported by an enhanced understanding of 7 8 fundamental transcriptional features of NSCLC tumors. -
Jun Dimerization Protein 2 Activates Mc2r Transcriptional Activity: Role of Phosphorylation and Sumoylation
International Journal of Molecular Sciences Article Jun Dimerization Protein 2 Activates Mc2r Transcriptional Activity: Role of Phosphorylation and SUMOylation Chiung-Min Wang 1, Raymond X. Wang 1, Runhua Liu 2 and Wei-Hsiung Yang 1,* 1 Department of Biomedical Sciences, Mercer University School of Medicine, Savannah, GA 31404, USA; [email protected] (C.-M.W.); [email protected] (R.X.W.) 2 Department of Genetics and Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL 35294, USA; [email protected] * Correspondence: [email protected]; Tel.: +1-912-721-8203; Fax: +1-912-721-8268 Academic Editor: William Chi-shing Cho Received: 15 December 2016; Accepted: 26 January 2017; Published: 31 January 2017 Abstract: Jun dimerization protein 2 (JDP2), a basic leucine zipper transcription factor, is involved in numerous biological and cellular processes such as cancer development and regulation, cell-cycle regulation, skeletal muscle and osteoclast differentiation, progesterone receptor signaling, and antibacterial immunity. Though JDP2 is widely expressed in mammalian tissues, its function in gonads and adrenals (such as regulation of steroidogenesis and adrenal development) is largely unknown. Herein, we find that JDP2 mRNA and proteins are expressed in mouse adrenal gland tissues. Moreover, overexpression of JDP2 in Y1 mouse adrenocortical cancer cells increases the level of melanocortin 2 receptor (MC2R) protein. Notably, Mc2r promoter activity is activated by JDP2 in a dose-dependent manner. Next, by mapping the Mc2r promoter, we show that cAMP response elements (between −1320 and −720-bp) are mainly required for Mc2r activation by JDP2 and demonstrate that −830-bp is the major JDP2 binding site by real-time chromatin immunoprecipitation (ChIP) analysis. -
RNA-Binding Protein Hnrnpll Regulates Mrna Splicing and Stability During B-Cell to Plasma-Cell Differentiation
RNA-binding protein hnRNPLL regulates mRNA splicing and stability during B-cell to plasma-cell differentiation Xing Changa,b, Bin Lic, and Anjana Raoa,b,d,e,1 Divisions of aSignaling and Gene Expression and cVaccine Discovery, La Jolla Institute for Allergy and Immunology, La Jolla, CA 92037; bSanford Consortium for Regenerative Medicine, La Jolla, CA 92037; and dDepartment of Pharmacology and eMoores Cancer Center, University of California at San Diego, La Jolla, CA 92093 Contributed by Anjana Rao, December 2, 2014 (sent for review July 20, 2014) Posttranscriptional regulation is a major mechanism to rewire the RBP-binding sites, thus validating the specificity of RBP binding transcriptomes during differentiation. Heterogeneous nuclear to coprecipitating RNAs and mapping RBP-binding sites on the RNA-binding protein LL (hnRNPLL) is specifically induced in terminally validated RNAs at close to single-nucleotide resolution (8). differentiated lymphocytes, including effector T cells and plasma Heterogeneous nuclear RNA-binding proteins (hnRNPs) is cells. To study the molecular functions of hnRNPLL at a genome- the term applied to a collection of unrelated nuclear RBPs. wide level, we identified hnRNPLL RNA targets and binding sites in hnRNPLL was identified through a targeted lentiviral shRNA plasma cells through integrated Photoactivatable-Ribonucleoside- screen for regulators of CD45RA to CD45RO switching during Enhanced Cross-Linking and Immunoprecipitation (PAR-CLIP) and memory T-cell development (9) and independently through RNA sequencing. hnRNPLL preferentially recognizes CA dinucleo- two separate screens performed by different groups for exclusion tide-containing sequences in introns and 3′ untranslated regions of CD45 exon 4 in a minigene context (10) and for altered CD44 (UTRs), promotes exon inclusion or exclusion in a context-dependent and CD45R expression on T cells in N-ethyl-N-nitrosourea manner, and stabilizes mRNA when associated with 3′ UTRs. -
TGF-Β1 Signaling Targets Metastasis-Associated Protein 1, a New Effector in Epithelial Cells
Oncogene (2011) 30, 2230–2241 & 2011 Macmillan Publishers Limited All rights reserved 0950-9232/11 www.nature.com/onc ORIGINAL ARTICLE TGF-b1 signaling targets metastasis-associated protein 1, a new effector in epithelial cells SB Pakala1, K Singh1,3, SDN Reddy1, K Ohshiro1, D-Q Li1, L Mishra2 and R Kumar1 1Department of Biochemistry and Molecular Biology and Institute of Coregulator Biology, The George Washington University Medical Center, Washington, DC, USA and 2Department of Gastroenterology, Hepatology and Nutrition, The University of Texas MD Anderson Cancer Center, Houston, TX, USA In spite of a large number of transforming growth factor b1 gene chromatin in response to upstream signals. The (TGF-b1)-regulated genes, the nature of its targets with TGF-b1-signaling is largely mediated by Smad proteins roles in transformation continues to be poorly understood. (Massague et al., 2005) where Smad2 and Smad3 are Here, we discovered that TGF-b1 stimulates transcription phosphorylated by TGF-b1-receptors and associate with of metastasis-associated protein 1 (MTA1), a dual master the common mediator Smad4, which translocates to the coregulator, in epithelial cells, and that MTA1 status is a nucleus to participate in the expression of TGF-b1-target determinant of TGF-b1-induced epithelial-to-mesenchymal genes (Deckers et al., 2006). Previous studies have shown transition (EMT) phenotypes. In addition, we found that that CUTL1, also known as CDP (CCAAT displacement MTA1/polymerase II/activator protein-1 (AP-1) co-activator protein), a target of TGF-b1, is needed for its short-term complex interacts with the FosB-gene chromatin and stimu- effects of TGF-b1 on cell motility involving Smad4- lates its transcription, and FosB in turn, utilizes FosB/histone dependent pathway (Michl et al.,2005). -
Wild-Type P53 Can Down-Modulate the Activity of Various Promoters
Proc. Natl. Acad. Sci. USA Vol. 88, pp. 9979-9983, November 1991 Biochemistry Wild-type p53 can down-modulate the activity of various promoters DORON GINSBERG*, FATIMA MECHTAt, MOSHE YANIVt, AND MOSHE OREN*t *Department of Chemical Immunology, The Weizmann Institute of Science, Rehovot 76100, Israel; and tDepartment of Biotechnology, Pasteur Institute, 75724 Paris Cedex 15, France Communicated by Robert A. Weinberg, August 16, 1991 ABSTRACT The wild-type (wt) p53 protein is the product out whether it could also modulate c-fos expression. We of a tumor suppressor gene that is a frequent target for report here that wt p53 can inhibit c-fos gene expression. This inactivation in many types of tumors. The nuclear localization effect of wt p53 is rapid, suggesting that it may precede ofthe protein, as well as additional features, suggest that it may growth arrest. In addition, cotransfection experiments indi- be involved in the regulation ofgene expression. To explore this cate that wt p53 can down-modulate the activity of a number possibility, the effects of overproduced wt p53 were investi- of promoters. While the effect of wt p53 appeared to be gated in a number of systems. Induction of growth arrest via relatively nonspecific, it probably did not reflect a general- the antiproliferative effect ofwt p53 greatly impaired the ability ized transcriptional shut-off. Our findings suggest that wt p53 of cells to exhibit an increase in c-fos mRNA upon serum may contribute to growth inhibition by down-modulating, stimulation. Experiments in which cells were cotransfected directly or indirectly, the expression of genes that are re- with p53 expression plasmids together with a reporter gene quired for ongoing cell proliferation. -
TOX As a Potential Target for Immunotherapy in Lymphocytic Malignancies Chaofeng Liang1,2, Shuxin Huang1, Yujie Zhao1, Shaohua Chen1* and Yangqiu Li1*
Liang et al. Biomarker Research (2021) 9:20 https://doi.org/10.1186/s40364-021-00275-y REVIEW Open Access TOX as a potential target for immunotherapy in lymphocytic malignancies Chaofeng Liang1,2, Shuxin Huang1, Yujie Zhao1, Shaohua Chen1* and Yangqiu Li1* Abstract TOX (thymocyte selection-associated HMG BOX) is a member of a family of transcriptional factors that contain the highly conserved high mobility group box (HMG-box) region. Increasing studies have shown that TOX is involved in maintaining tumors and promoting T cell exhaustion. In this review, we summarized the biological functions of TOX and its contribution as related to lymphocytic malignancies. We also discussed the potential role of TOX as an immune biomarker and target in immunotherapy for hematological malignancies. Keywords: Thymocyte selection-associated HMG BOX, Biological function, T cell exhaustion, Lymphocytic malignancies, Immune biomarker, Immunotherapy Background located on different chromosomes and have different TOX (thymocyte selection-associated HMG BOX), a functions (Fig. 1, Table 1)[16]. transcription factor, belongs to the high mobility group box (HMG-box) superfamily. In 2002, Wilkinson et al. TOX demonstrated for the first time that TOX plays an im- TOX, also known as KIAA0808, is located on q12.1 of portant role in the differentiation of CD4 + CD8+ human chromosome 8 and has one transcript. The double-positive thymocytes by gene microarray technol- length of the TOX mRNA is 4076 bp, and it contains ogy. Numerous studies have shown that TOX plays a nine exons that translate into a protein consisting of 526 vital role in the development and formation of various amino acids. -
The Title of the Dissertation
UNIVERSITY OF CALIFORNIA SAN DIEGO Novel network-based integrated analyses of multi-omics data reveal new insights into CD8+ T cell differentiation and mouse embryogenesis A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Bioinformatics and Systems Biology by Kai Zhang Committee in charge: Professor Wei Wang, Chair Professor Pavel Arkadjevich Pevzner, Co-Chair Professor Vineet Bafna Professor Cornelis Murre Professor Bing Ren 2018 Copyright Kai Zhang, 2018 All rights reserved. The dissertation of Kai Zhang is approved, and it is accept- able in quality and form for publication on microfilm and electronically: Co-Chair Chair University of California San Diego 2018 iii EPIGRAPH The only true wisdom is in knowing you know nothing. —Socrates iv TABLE OF CONTENTS Signature Page ....................................... iii Epigraph ........................................... iv Table of Contents ...................................... v List of Figures ........................................ viii List of Tables ........................................ ix Acknowledgements ..................................... x Vita ............................................. xi Abstract of the Dissertation ................................. xii Chapter 1 General introduction ............................ 1 1.1 The applications of graph theory in bioinformatics ......... 1 1.2 Leveraging graphs to conduct integrated analyses .......... 4 1.3 References .............................. 6 Chapter 2 Systematic -
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. -
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. -
Susceptibility of Heterozygous and Nullizygous P53 Knockout Mice to Chemical Carcinogens: Tissue Dependence and Role of P53 Gene Mutations
J Toxicol Pathol 2005; 18: 121–134 Review Susceptibility of Heterozygous and Nullizygous p53 Knockout Mice to Chemical Carcinogens: Tissue Dependence and Role of p53 Gene Mutations Tetsuya Tsukamoto1, Akihiro Hirata1, and Masae Tatematsu1 1Division of Oncological Pathology, Aichi Cancer Center Research Institute, 1–1 Kanokoden, Chikusa-ku, Nagoya 464–8681, Japan Abstract: Mutations of the p53 tumor suppressor gene constitute one of the most frequent molecular changes in a wide variety of human cancers and mice deficient in p53 have recently attracted attention for their potential to identify chemical genotoxins. In this article, we review the data on the susceptibility of p53 nullizygote (–/–), heterozygote (+/ –), and wild type (+/+) mice to various carcinogens. Induction of esophageal and tongue squamous cell carcinomas (SCCs) by methyl-n-amylnitrosamine was shown to be increased in p53 (+/–) mice, in addition to the high sensitivity shown by p53 (–/–) littermates. N,N-dibutylnitrosamine (DBN) treatment also caused more tumor development in p53 (+/–) than wild-type mice, as with N-butyl-N-(4-hydroxybutyl)nitrosamine (BBN) in the urinary bladder. In addition, p53 (+/–) heterozygotes proved more sensitive than wild type littermates to the induction of stromal cell tumors like hemangiomas/hemangiosarcomas by N-bis(2-hydroxypropyl)nitrosamine (BHP) or lymphomas and fibrosarcomas with other carcinogens. Analysis of exons 5–8 of the p53 gene demonstrated mutations in approximately one half of the lesions. With N-methyl-N-nitrosourea, preneoplastic lesions of the stomach, pepsinogen altered pyloric glands (PAPG), and a gastric adenocarcinoma, were found after only 15 weeks in p53 (–/–) mice, although there was no significant difference in the incidence of gastric tumors between p53 (+/+) and (+/–) mice in the longer-term. -
Transcriptional Control of Tissue-Resident Memory T Cell Generation
Transcriptional control of tissue-resident memory T cell generation Filip Cvetkovski Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2019 © 2019 Filip Cvetkovski All rights reserved ABSTRACT Transcriptional control of tissue-resident memory T cell generation Filip Cvetkovski Tissue-resident memory T cells (TRM) are a non-circulating subset of memory that are maintained at sites of pathogen entry and mediate optimal protection against reinfection. Lung TRM can be generated in response to respiratory infection or vaccination, however, the molecular pathways involved in CD4+TRM establishment have not been defined. Here, we performed transcriptional profiling of influenza-specific lung CD4+TRM following influenza infection to identify pathways implicated in CD4+TRM generation and homeostasis. Lung CD4+TRM displayed a unique transcriptional profile distinct from spleen memory, including up-regulation of a gene network induced by the transcription factor IRF4, a known regulator of effector T cell differentiation. In addition, the gene expression profile of lung CD4+TRM was enriched in gene sets previously described in tissue-resident regulatory T cells. Up-regulation of immunomodulatory molecules such as CTLA-4, PD-1, and ICOS, suggested a potential regulatory role for CD4+TRM in tissues. Using loss-of-function genetic experiments in mice, we demonstrate that IRF4 is required for the generation of lung-localized pathogen-specific effector CD4+T cells during acute influenza infection. Influenza-specific IRF4−/− T cells failed to fully express CD44, and maintained high levels of CD62L compared to wild type, suggesting a defect in complete differentiation into lung-tropic effector T cells.