T Cell Subtypes T Cells Cells T 6 G D Subsets Were by Distinguished Modules Unique Transcription-Factor Γ Γ Δ Δ 1 ------, Catherine C Yin
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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. -
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. -
Genetics of Interleukin 1 Receptor-Like 1 in Immune and Inflammatory Diseases
Current Genomics, 2010, 11, 591-606 591 Genetics of Interleukin 1 Receptor-Like 1 in Immune and Inflammatory Diseases Loubna Akhabir and Andrew Sandford* Department of Medicine, University of British Columbia, UBC James Hogg Research Centre, Providence Heart + Lung Institute, Room 166, St. Paul's Hospital, 1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada Abstract: Interleukin 1 receptor-like 1 (IL1RL1) is gaining in recognition due to its involvement in immune/inflamma- tory disorders. Well-designed animal studies have shown its critical role in experimental allergic inflammation and human in vitro studies have consistently demonstrated its up-regulation in several conditions such as asthma and rheumatoid ar- thritis. The ligand for IL1RL1 is IL33 which emerged as playing an important role in initiating eosinophilic inflammation and activating other immune cells resulting in an allergic phenotype. An IL1RL1 single nucleotide polymorphism (SNP) was among the most significant results of a genome-wide scan inves- tigating eosinophil counts; in the same study, this SNP associated with asthma in 10 populations. The IL1RL1 gene resides in a region of high linkage disequilibrium containing interleukin 1 receptor genes as well as in- terleukin 18 receptor and accessory genes. This poses a challenge to researchers interested in deciphering genetic associa- tion signals in the region as all of the genes represent interesting candidates for asthma and allergic disease. The IL1RL1 gene and its resulting soluble and receptor proteins have emerged as key regulators of the inflammatory proc- ess implicated in a large variety of human pathologies We review the function and expression of the IL1RL1 gene. -
Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model
Downloaded from http://www.jimmunol.org/ by guest on September 25, 2021 T + is online at: average * The Journal of Immunology , 34 of which you can access for free at: 2016; 197:1477-1488; Prepublished online 1 July from submission to initial decision 4 weeks from acceptance to publication 2016; doi: 10.4049/jimmunol.1600589 http://www.jimmunol.org/content/197/4/1477 Molecular Profile of Tumor-Specific CD8 Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. Waugh, Sonia M. Leach, Brandon L. Moore, Tullia C. Bruno, Jonathan D. Buhrman and Jill E. Slansky J Immunol cites 95 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html http://www.jimmunol.org/content/suppl/2016/07/01/jimmunol.160058 9.DCSupplemental This article http://www.jimmunol.org/content/197/4/1477.full#ref-list-1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material References Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 25, 2021. The Journal of Immunology Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. -
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. -
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 -
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. -
The E–Id Protein Axis Modulates the Activities of the PI3K–AKT–Mtorc1
Downloaded from genesdev.cshlp.org on October 6, 2021 - Published by Cold Spring Harbor Laboratory Press The E–Id protein axis modulates the activities of the PI3K–AKT–mTORC1– Hif1a and c-myc/p19Arf pathways to suppress innate variant TFH cell development, thymocyte expansion, and lymphomagenesis Masaki Miyazaki,1,8 Kazuko Miyazaki,1,8 Shuwen Chen,1 Vivek Chandra,1 Keisuke Wagatsuma,2 Yasutoshi Agata,2 Hans-Reimer Rodewald,3 Rintaro Saito,4 Aaron N. Chang,5 Nissi Varki,6 Hiroshi Kawamoto,7 and Cornelis Murre1 1Department of Molecular Biology, University of California at San Diego, La Jolla, California 92093, USA; 2Department of Biochemistry and Molecular Biology, Shiga University of Medical School, Shiga 520-2192, Japan; 3Division of Cellular Immunology, German Cancer Research Center, D-69120 Heidelberg, Germany; 4Department of Medicine, University of California at San Diego, La Jolla, California 92093, USA; 5Center for Computational Biology, Institute for Genomic Medicine, University of California at San Diego, La Jolla, California 92093, USA; 6Department of Pathology, University of California at San Diego, La Jolla, California 92093, USA; 7Department of Immunology, Institute for Frontier Medical Sciences, Kyoto University, Kyoto 606-8507, Japan It is now well established that the E and Id protein axis regulates multiple steps in lymphocyte development. However, it remains unknown how E and Id proteins mechanistically enforce and maintain the naı¨ve T-cell fate. Here we show that Id2 and Id3 suppressed the development and expansion of innate variant follicular helper T (TFH) cells. Innate variant TFH cells required major histocompatibility complex (MHC) class I-like signaling and were associated with germinal center B cells. -
Supplementary Table S5. Differentially Expressed Gene Lists of PD-1High CD39+ CD8 Tils According to 4-1BB Expression Compared to PD-1+ CD39- CD8 Tils
BMJ Publishing Group Limited (BMJ) disclaims all liability and responsibility arising from any reliance Supplemental material placed on this supplemental material which has been supplied by the author(s) J Immunother Cancer Supplementary Table S5. Differentially expressed gene lists of PD-1high CD39+ CD8 TILs according to 4-1BB expression compared to PD-1+ CD39- CD8 TILs Up- or down- regulated genes in Up- or down- regulated genes Up- or down- regulated genes only PD-1high CD39+ CD8 TILs only in 4-1BBneg PD-1high CD39+ in 4-1BBpos PD-1high CD39+ CD8 compared to PD-1+ CD39- CD8 CD8 TILs compared to PD-1+ TILs compared to PD-1+ CD39- TILs CD39- CD8 TILs CD8 TILs IL7R KLRG1 TNFSF4 ENTPD1 DHRS3 LEF1 ITGA5 MKI67 PZP KLF3 RYR2 SIK1B ANK3 LYST PPP1R3B ETV1 ADAM28 H2AC13 CCR7 GFOD1 RASGRP2 ITGAX MAST4 RAD51AP1 MYO1E CLCF1 NEBL S1PR5 VCL MPP7 MS4A6A PHLDB1 GFPT2 TNF RPL3 SPRY4 VCAM1 B4GALT5 TIPARP TNS3 PDCD1 POLQ AKAP5 IL6ST LY9 PLXND1 PLEKHA1 NEU1 DGKH SPRY2 PLEKHG3 IKZF4 MTX3 PARK7 ATP8B4 SYT11 PTGER4 SORL1 RAB11FIP5 BRCA1 MAP4K3 NCR1 CCR4 S1PR1 PDE8A IFIT2 EPHA4 ARHGEF12 PAICS PELI2 LAT2 GPRASP1 TTN RPLP0 IL4I1 AUTS2 RPS3 CDCA3 NHS LONRF2 CDC42EP3 SLCO3A1 RRM2 ADAMTSL4 INPP5F ARHGAP31 ESCO2 ADRB2 CSF1 WDHD1 GOLIM4 CDK5RAP1 CD69 GLUL HJURP SHC4 GNLY TTC9 HELLS DPP4 IL23A PITPNC1 TOX ARHGEF9 EXO1 SLC4A4 CKAP4 CARMIL3 NHSL2 DZIP3 GINS1 FUT8 UBASH3B CDCA5 PDE7B SOGA1 CDC45 NR3C2 TRIB1 KIF14 TRAF5 LIMS1 PPP1R2C TNFRSF9 KLRC2 POLA1 CD80 ATP10D CDCA8 SETD7 IER2 PATL2 CCDC141 CD84 HSPA6 CYB561 MPHOSPH9 CLSPN KLRC1 PTMS SCML4 ZBTB10 CCL3 CA5B PIP5K1B WNT9A CCNH GEM IL18RAP GGH SARDH B3GNT7 C13orf46 SBF2 IKZF3 ZMAT1 TCF7 NECTIN1 H3C7 FOS PAG1 HECA SLC4A10 SLC35G2 PER1 P2RY1 NFKBIA WDR76 PLAUR KDM1A H1-5 TSHZ2 FAM102B HMMR GPR132 CCRL2 PARP8 A2M ST8SIA1 NUF2 IL5RA RBPMS UBE2T USP53 EEF1A1 PLAC8 LGR6 TMEM123 NEK2 SNAP47 PTGIS SH2B3 P2RY8 S100PBP PLEKHA7 CLNK CRIM1 MGAT5 YBX3 TP53INP1 DTL CFH FEZ1 MYB FRMD4B TSPAN5 STIL ITGA2 GOLGA6L10 MYBL2 AHI1 CAND2 GZMB RBPJ PELI1 HSPA1B KCNK5 GOLGA6L9 TICRR TPRG1 UBE2C AURKA Leem G, et al. -
Supplemental Material For
Supplemental material for Epithelial to mesenchymal transition rewires the molecular path to PI3-Kinase-dependent proliferation Megan B. Salt1,2, Sourav Bandyopadhyay1,3 and Frank McCormick1 Authors Affiliations: 1-Helen Diller Family Comprehensive Cancer Center; 2-Biomedical Sciences Graduate Program, University of California San Francisco, San Francisco, California; 3-California Institute for Quantitative Biosciences, San Francisco, California. Supplemental Figure Legends Table S1. EMT associated changes in gene expression. Significantly (A) up- and (B) down- regulated genes in comparing H358-TwistER cells to control H358-GFP expressing cells treated with 100nM 4OHT for 12 days. The four columns on the right are associated with significantly upregulated genes, while the four columns furthest left described significantly downregulated genes. The first column for the up- and downregulated genes shows the Probe ID associated with each gene from the Affymetric Human Gene 1.0 ST microarrays. The gene name are shown in the next column, followed by the log2(fold change) in expression for each gene after 4OHT treatment in the H358-TwistER cells. The final column shows the p-value for each gene adjusted for the false discovery rate. Figure S1. Akt inhibition reduces serum-independent proliferation. (A) Proliferation of H358- TwistER cells with increasing concentrations (uM) of GSK-690693 (top) or MK-2206 (bottom). (B) Lysates from H358-TwistER cells treated for 48hrs in serum free media with indicated concentrations of GSK-690693 (top), or MK-2206 (bottom). Figure S2. The effects of TGFβ1 are specific to epithelial cells and lead to reduced serum- independent proliferation. (A) Proliferation of untreated (top) or TGFβ1 pre-treated (bottom) H358 and H441 cells in the presence (10%) or absence (SS) of serum. -
How Relevant Are Bone Marrow-Derived Mast Cells (Bmmcs) As Models for Tissue Mast Cells? a Comparative Transcriptome Analysis of Bmmcs and Peritoneal Mast Cells
cells Article How Relevant Are Bone Marrow-Derived Mast Cells (BMMCs) as Models for Tissue Mast Cells? A Comparative Transcriptome Analysis of BMMCs and Peritoneal Mast Cells 1, 2, 1 1 2,3 Srinivas Akula y , Aida Paivandy y, Zhirong Fu , Michael Thorpe , Gunnar Pejler and Lars Hellman 1,* 1 Department of Cell and Molecular Biology, Uppsala University, The Biomedical Center, Box 596, SE-751 24 Uppsala, Sweden; [email protected] (S.A.); [email protected] (Z.F.); [email protected] (M.T.) 2 Department of Medical Biochemistry and Microbiology, Uppsala University, The Biomedical Center, Box 589, SE-751 23 Uppsala, Sweden; [email protected] (A.P.); [email protected] (G.P.) 3 Department of Anatomy, Physiology and Biochemistry, Swedish University of Agricultural Sciences, Box 7011, SE-75007 Uppsala, Sweden * Correspondence: [email protected]; Tel.: +46-(0)18-471-4532; Fax: +46-(0)18-471-4862 These authors contributed equally to this work. y Received: 29 July 2020; Accepted: 16 September 2020; Published: 17 September 2020 Abstract: Bone marrow-derived mast cells (BMMCs) are often used as a model system for studies of the role of MCs in health and disease. These cells are relatively easy to obtain from total bone marrow cells by culturing under the influence of IL-3 or stem cell factor (SCF). After 3 to 4 weeks in culture, a nearly homogenous cell population of toluidine blue-positive cells are often obtained. However, the question is how relevant equivalents these cells are to normal tissue MCs. By comparing the total transcriptome of purified peritoneal MCs with BMMCs, here we obtained a comparative view of these cells. -
Supplementary Table S1. Correlation Between the Mutant P53-Interacting Partners and PTTG3P, PTTG1 and PTTG2, Based on Data from Starbase V3.0 Database
Supplementary Table S1. Correlation between the mutant p53-interacting partners and PTTG3P, PTTG1 and PTTG2, based on data from StarBase v3.0 database. PTTG3P PTTG1 PTTG2 Gene ID Coefficient-R p-value Coefficient-R p-value Coefficient-R p-value NF-YA ENSG00000001167 −0.077 8.59e-2 −0.210 2.09e-6 −0.122 6.23e-3 NF-YB ENSG00000120837 0.176 7.12e-5 0.227 2.82e-7 0.094 3.59e-2 NF-YC ENSG00000066136 0.124 5.45e-3 0.124 5.40e-3 0.051 2.51e-1 Sp1 ENSG00000185591 −0.014 7.50e-1 −0.201 5.82e-6 −0.072 1.07e-1 Ets-1 ENSG00000134954 −0.096 3.14e-2 −0.257 4.83e-9 0.034 4.46e-1 VDR ENSG00000111424 −0.091 4.10e-2 −0.216 1.03e-6 0.014 7.48e-1 SREBP-2 ENSG00000198911 −0.064 1.53e-1 −0.147 9.27e-4 −0.073 1.01e-1 TopBP1 ENSG00000163781 0.067 1.36e-1 0.051 2.57e-1 −0.020 6.57e-1 Pin1 ENSG00000127445 0.250 1.40e-8 0.571 9.56e-45 0.187 2.52e-5 MRE11 ENSG00000020922 0.063 1.56e-1 −0.007 8.81e-1 −0.024 5.93e-1 PML ENSG00000140464 0.072 1.05e-1 0.217 9.36e-7 0.166 1.85e-4 p63 ENSG00000073282 −0.120 7.04e-3 −0.283 1.08e-10 −0.198 7.71e-6 p73 ENSG00000078900 0.104 2.03e-2 0.258 4.67e-9 0.097 3.02e-2 Supplementary Table S2.