Review Article TOX Gene: a Novel Target for Human Cancer Gene Therapy
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Screening and Identification of Key Biomarkers in Clear Cell Renal Cell Carcinoma Based on Bioinformatics Analysis
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Screening and identification of key biomarkers in clear cell renal cell carcinoma based on bioinformatics analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.21.423889; this version posted December 23, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract Clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignancy of the urinary system. The pathogenesis and effective diagnosis of ccRCC have become popular topics for research in the previous decade. In the current study, an integrated bioinformatics analysis was performed to identify core genes associated in ccRCC. An expression dataset (GSE105261) was downloaded from the Gene Expression Omnibus database, and included 26 ccRCC and 9 normal kideny samples. Assessment of the microarray dataset led to the recognition of differentially expressed genes (DEGs), which was subsequently used for pathway and gene ontology (GO) enrichment analysis. -
A Prelude to the Proximity Interaction Mapping of CXXC5
www.nature.com/scientificreports OPEN A prelude to the proximity interaction mapping of CXXC5 Gamze Ayaz1,4,6*, Gizem Turan1,6, Çağla Ece Olgun1,6, Gizem Kars1, Burcu Karakaya1, Kerim Yavuz1, Öykü Deniz Demiralay1, Tolga Can2, Mesut Muyan1,3* & Pelin Yaşar1,5,6 CXXC5 is a member of the zinc-fnger CXXC family proteins that interact with unmodifed CpG dinucleotides through a conserved ZF-CXXC domain. CXXC5 is involved in the modulation of gene expressions that lead to alterations in diverse cellular events. However, the underlying mechanism of CXXC5-modulated gene expressions remains unclear. Proteins perform their functions in a network of proteins whose identities and amounts change spatiotemporally in response to various stimuli in a lineage-specifc manner. Since CXXC5 lacks an intrinsic transcription regulatory function or enzymatic activity but is a DNA binder, CXXC5 by interacting with proteins could act as a scafold to establish a chromatin state restrictive or permissive for transcription. To initially address this, we utilized the proximity-dependent biotinylation approach. Proximity interaction partners of CXXC5 include DNA and chromatin modifers, transcription factors/co-regulators, and RNA processors. Of these, CXXC5 through its CXXC domain interacted with EMD, MAZ, and MeCP2. Furthermore, an interplay between CXXC5 and MeCP2 was critical for a subset of CXXC5 target gene expressions. It appears that CXXC5 may act as a nucleation factor in modulating gene expressions. Providing a prelude for CXXC5 actions, our results could also contribute to a better understanding of CXXC5-mediated cellular processes in physiology and pathophysiology. Te methylation of mammalian genomic DNA, which predominantly arises post-replicatively at the 5’ posi- tion of the cytosine base in the context of CpG dinucleotides, varies across cell types, developmental stages, physiological and pathophysiological conditions 1. -
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. -
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. -
Molecular Mechanisms Involved Involved in the Interaction Effects of HCV and Ethanol on Liver Cirrhosis
Virginia Commonwealth University VCU Scholars Compass Theses and Dissertations Graduate School 2010 Molecular Mechanisms Involved Involved in the Interaction Effects of HCV and Ethanol on Liver Cirrhosis Ryan Fassnacht Virginia Commonwealth University Follow this and additional works at: https://scholarscompass.vcu.edu/etd Part of the Physiology Commons © The Author Downloaded from https://scholarscompass.vcu.edu/etd/2246 This Thesis is brought to you for free and open access by the Graduate School at VCU Scholars Compass. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of VCU Scholars Compass. For more information, please contact [email protected]. Ryan C. Fassnacht 2010 All Rights Reserved Molecular Mechanisms Involved in the Interaction Effects of HCV and Ethanol on Liver Cirrhosis A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science at Virginia Commonwealth University. by Ryan Christopher Fassnacht, B.S. Hampden Sydney University, 2005 M.S. Virginia Commonwealth University, 2010 Director: Valeria Mas, Ph.D., Associate Professor of Surgery and Pathology Division of Transplant Department of Surgery Virginia Commonwealth University Richmond, Virginia July 9, 2010 Acknowledgement The Author wishes to thank his family and close friends for their support. He would also like to thank the members of the molecular transplant team for their help and advice. This project would not have been possible with out the help of Dr. Valeria Mas and her endearing -
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). -
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. -
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. -
Host-Parasite Interaction of Atlantic Salmon (Salmo Salar) and the Ectoparasite Neoparamoeba Perurans in Amoebic Gill Disease
ORIGINAL RESEARCH published: 31 May 2021 doi: 10.3389/fimmu.2021.672700 Host-Parasite Interaction of Atlantic salmon (Salmo salar) and the Ectoparasite Neoparamoeba perurans in Amoebic Gill Disease † Natasha A. Botwright 1*, Amin R. Mohamed 1 , Joel Slinger 2, Paula C. Lima 1 and James W. Wynne 3 1 Livestock and Aquaculture, CSIRO Agriculture and Food, St Lucia, QLD, Australia, 2 Livestock and Aquaculture, CSIRO Agriculture and Food, Woorim, QLD, Australia, 3 Livestock and Aquaculture, CSIRO Agriculture and Food, Hobart, TAS, Australia Marine farmed Atlantic salmon (Salmo salar) are susceptible to recurrent amoebic gill disease Edited by: (AGD) caused by the ectoparasite Neoparamoeba perurans over the growout production Samuel A. M. Martin, University of Aberdeen, cycle. The parasite elicits a highly localized response within the gill epithelium resulting in United Kingdom multifocal mucoid patches at the site of parasite attachment. This host-parasite response Reviewed by: drives a complex immune reaction, which remains poorly understood. To generate a model Diego Robledo, for host-parasite interaction during pathogenesis of AGD in Atlantic salmon the local (gill) and University of Edinburgh, United Kingdom systemic transcriptomic response in the host, and the parasite during AGD pathogenesis was Maria K. Dahle, explored. A dual RNA-seq approach together with differential gene expression and system- Norwegian Veterinary Institute (NVI), Norway wide statistical analyses of gene and transcription factor networks was employed. A multi- *Correspondence: tissue transcriptomic data set was generated from the gill (including both lesioned and non- Natasha A. Botwright lesioned tissue), head kidney and spleen tissues naïve and AGD-affected Atlantic salmon [email protected] sourced from an in vivo AGD challenge trial. -
TOX3 Is Expressed in Mammary ER+ Epithelial Cells and Regulates ER
Seksenyan et al. BMC Cancer (2015) 15:22 DOI 10.1186/s12885-015-1018-2 RESEARCH ARTICLE Open Access TOX3 is expressed in mammary ER+ epithelial cells and regulates ER target genes in luminal breast cancer Akop Seksenyan1, Asha Kadavallore1, Ann E Walts2, Brian de la Torre1, Dror Berel3,4, Samuel P Strom5,6, Parinaz Aliahmad1, Vincent A Funari5 and Jonathan Kaye1,3,7* Abstract Background: A breast cancer susceptibility locus has been mapped to the gene encoding TOX3. Little is known regarding the expression pattern or biological role of TOX3 in breast cancer or in the mammary gland. Here we analyzed TOX3 expression in murine and human mammary glands and in molecular subtypes of breast cancer, and assessed its ability to alter the biology of breast cancer cells. Methods: We used a cell sorting strategy, followed by quantitative real-time PCR, to study TOX3 gene expression in the mouse mammary gland. To study the expression of this nuclear protein in human mammary glands and breast tumors, we generated a rabbit monoclonal antibody specific for human TOX3. In vitro studies were performed on MCF7, BT474 and MDA-MB-231 cell lines to study the effects of TOX3 modulation on gene expression in the context of breast cancer cells. Results: We found TOX3 expression in estrogen receptor-positive mammary epithelial cells, including progenitor cells. A subset of breast tumors also highly expresses TOX3, with poor outcome associated with high expression of TOX3 in luminal B breast cancers. We also demonstrate the ability of TOX3 to alter gene expression in MCF7 luminal breast cancer cells, including cancer relevant genes TFF1 and CXCR4.