TOX3 Is Expressed in Mammary ER+ Epithelial Cells and Regulates ER
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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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. -
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. -
Cited1 (NM 001276466) Mouse Tagged ORF Clone Product Data
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for MR228487 Cited1 (NM_001276466) Mouse Tagged ORF Clone Product data: Product Type: Expression Plasmids Product Name: Cited1 (NM_001276466) Mouse Tagged ORF Clone Tag: Myc-DDK Symbol: Cited1 Synonyms: AI316840; AU019144; Msg1 Vector: pCMV6-Entry (PS100001) E. coli Selection: Kanamycin (25 ug/mL) Cell Selection: Neomycin ORF Nucleotide >MR228487 representing NM_001276466 Sequence: Red=Cloning site Blue=ORF Green=Tags(s) TTTTGTAATACGACTCACTATAGGGCGGCCGGGAATTCGTCGACTGGATCCGGTACCGAGGAGATCTGCC GCCGCGATCGCC ATGCCAACTATGTCGAGGCCTGCACTTGATGTCAAGGGTGGCACCACCTCTGGGAAGGAGGATGCCAACC AGGAGATGAACTCTCTGGCCTACTCCAACCTTGGAGTGAAGGATCGCAAGGCAGTGACTGTCCTGCACTA CCCCGGGGTCACCGCAAATGGAGCCAAAGCCAACGGAGTTCCCACTAGCTCCTCTGGATCGACATCTCCA ATAGGCTCTCCTACTGCCACCCCTTCTTCCAAACCCCCATCCTTCAACCTGCATCCTACCCCTCACCTGA TGGCCAGCATGCAGCTTCAGAAGCTTAATAGCCAGTACCAAGGGGCTGCGGCTACTGCTGCTGCTGCCCT CACTGGTGCAGGCCTACCAGGGGAGGAAGAGCCCATGCAAAACTGGGTCACCGCCCCTCTGGTAGTGGGA GGGTCTCCGGGATCTGTCTCTCCTCCTGCTGGTGCCCAGAGCCCTGCTCTCATTGATTCTGACCCGGTGG ATGAGGAGGTGCTGATGTCTCTGGTGGTTGAATTGGGGCTAGACCGAGCCAATGAGCTTCCCGAGCTGTG GCTGGGGCAGAATGAGTTTGATTTCACTGCAGATTTTCCCTCTGGCTGC ACGCGTACGCGGCCGCTCGAGCAGAAACTCATCTCAGAAGAGGATCTGGCAGCAAATGATATCCTGGATT ACAAGGATGACGACGATAAGGTTTAA Protein Sequence: >MR228487 representing NM_001276466 Red=Cloning site Green=Tags(s) MPTMSRPALDVKGGTTSGKEDANQEMNSLAYSNLGVKDRKAVTVLHYPGVTANGAKANGVPTSSSGSTSP -
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. -
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. -
HSPA8 Antibody (C-Term) Purified Rabbit Polyclonal Antibody (Pab) Catalog # Ap2872b
10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 HSPA8 Antibody (C-term) Purified Rabbit Polyclonal Antibody (Pab) Catalog # AP2872b Specification HSPA8 Antibody (C-term) - Product Information Application IF, WB, IHC-P, FC,E Primary Accession P11142 Other Accession P63018, P63017, P19378, P19120, A2Q0Z1 Reactivity Human, Mouse Predicted Bovine, Hamster, Horse, Rat Host Rabbit Clonality Polyclonal Isotype Rabbit Ig Antigen Region 539-569 HSPA8 Antibody (C-term) - Additional Information Confocal immunofluorescent analysis of Gene ID 3312 HSPA8 Antibody (C-term)(Cat#AP2872b) with Hela cell followed by Alexa Fluor Other Names 488-conjugated goat anti-rabbit lgG (green). Heat shock cognate 71 kDa protein, Heat Actin filaments have been labeled with Alexa shock 70 kDa protein 8, Fluor 555 phalloidin (red). Lipopolysaccharide-associated protein 1, LAP-1, LPS-associated protein 1, HSPA8, HSC70, HSP73, HSPA10 Target/Specificity This HSPA8 antibody is generated from rabbits immunized with a KLH conjugated synthetic peptide between 539-569 amino acids from the C-terminal region of human HSPA8. Dilution IF~~1:10~50 WB~~1:1000 IHC-P~~1:10~50 FC~~1:10~50 Format Purified polyclonal antibody supplied in PBS with 0.09% (W/V) sodium azide. This Western blot analysis of lysates from rat antibody is prepared by Saturated H-4-II-E, mouse NIH/3T3 cell line (from left to Ammonium Sulfate (SAS) precipitation right), using HSPA8 Antibody (C-term) (Cat. # followed by dialysis against PBS. AP2872b). AP2872b was diluted at 1:1000 at each lane. A goat anti-rabbit IgG H&L(HRP) at Page 1/5 10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 Storage 1:5000 dilution was used as the secondary Maintain refrigerated at 2-8°C for up to 2 antibody. -
HSPA8 Antibody (N-Term) Purified Rabbit Polyclonal Antibody (Pab) Catalog # AW5209
10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 HSPA8 Antibody (N-term) Purified Rabbit Polyclonal Antibody (Pab) Catalog # AW5209 Specification HSPA8 Antibody (N-term) - Product Information Application IF, WB, IHC-P, FC,E Primary Accession P11142 Other Accession P63018, P63017, P19378, O73885, P19120, A2Q0Z1 Reactivity Human, Mouse, Rat Predicted Bovine, Chicken, Hamster, Horse Host Rabbit Clonality Polyclonal Calculated MW H=71;M=71;Rat= 71 KDa Isotype Rabbit Ig Antigen Source HUMAN Confocal immunofluorescent analysis of HSPA8 Antibody (N-term)(Cat#AW5209) with HSPA8 Antibody (N-term) - Additional Information A2058 cell followed by Alexa Fluor 488-conjugated goat anti-rabbit lgG (green). Actin filaments have been labeled with Alexa Gene ID 3312 Fluor 555 phalloidin (red).DAPI was used to Antigen Region stain the cell nuclear (blue). 82-110 Other Names HSPA8; HSC70; HSP73; HSPA10; Heat shock cognate 71 kDa protein; Heat shock 70 kDa protein 8 Dilution IF~~1:10~50 WB~~1:1000 IHC-P~~1:10~50 FC~~1:10~50 Target/Specificity This HSPA8 antibody is generated from rabbits immunized with a KLH conjugated synthetic peptide between 82-110 amino acids from the N-terminal region of human HSPA8. Western blot analysis of lysates from Hela,A431,mouse NIH/3T3,rat H-4-Ⅱ-E cell line Format (from left to right), using HSPA8 Antibody Purified polyclonal antibody supplied in PBS (N-term)(Cat. #AW5209). AW5209 was Page 1/5 10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 with 0.09% (W/V) sodium azide. -
A Genomic Atlas of Human Adrenal and Gonad Development [Version 2; Referees: 4 Approved] Ignacio Del Valle1, Federica Buonocore1, Andrew J
Wellcome Open Research 2017, 2:25 Last updated: 08 NOV 2017 RESEARCH ARTICLE A genomic atlas of human adrenal and gonad development [version 2; referees: 4 approved] Ignacio del Valle1, Federica Buonocore1, Andrew J. Duncan1, Lin Lin1, Martino Barenco2, Rahul Parnaik1, Sonia Shah3,4, Mike Hubank5, Dianne Gerrelli2, John C. Achermann 1 1Genetics and Genomic Medicine, UCL Great Ormond Street Institute of Child Health, London, UK 2Developmental Biology and Cancer, UCL Great Ormond Street Institute of Child Health, London, UK 3Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia 4Institute of Cardiovascular Science, University College London, London, UK 5The Centre for Molecular Pathology, Royal Marsden Hospital, Sutton, UK v2 First published: 07 Apr 2017, 2:25 (doi: 10.12688/wellcomeopenres.11253.1) Open Peer Review Latest published: 23 Oct 2017, 2:25 (doi: 10.12688/wellcomeopenres.11253.2) Referee Status: Abstract Background: In humans, the adrenal glands and gonads undergo distinct biological events between 6-10 weeks post conception (wpc), such as testis Invited Referees determination, the onset of steroidogenesis and primordial germ cell 1 2 3 4 development. However, relatively little is currently known about the genetic mechanisms underlying these processes. We therefore aimed to generate a detailed genomic atlas of adrenal and gonad development across these critical version 2 report report stages of human embryonic and fetal development. published Methods: RNA was extracted from 53 tissue samples between 6-10 wpc 23 Oct 2017 (adrenal, testis, ovary and control). Affymetrix array analysis was performed and differential gene expression was analysed using Bioconductor. A version 1 mathematical model was constructed to investigate time-series changes across published report report report report 07 Apr 2017 the dataset. -
TOX3 Is a Favorable Prognostic Indicator and Potential Immunomodulatory Factor in Lung Adenocarcinoma
4144 ONCOLOGY LETTERS 18: 4144-4152, 2019 TOX3 is a favorable prognostic indicator and potential immunomodulatory factor in lung adenocarcinoma DE ZENG1, HAOYU LIN2, JIANXIONG CUI2 and WEIQUAN LIANG2 1Department of Medical Oncology, Cancer Hospital of Shantou University Medical College; 2Department of Breast and Thyroid Surgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong 515000, P.R. China Received February 13, 2018; Accepted January 14, 2019 DOI: 10.3892/ol.2019.10748 Abstract. Thymocyte selection-associated high mobility and cytotoxic T lymphocyte-associated protein 4 (CTLA4), as group box (TOX) genes represent a novel family of genes. well as the development of novel immunotherapy agents, lung Deregulated expression of TOXs has been reported in a cancer treatments have improved notably in terms of disease variety of cancer types, including lung cancer. It has also control and survival outcomes (3). However, the success rate been reported that TOXs are crucial regulators of the immune of immunotherapy remains low, and a large number of cancer system. The present study systematically evaluated the prog- types, including lung cancer, remain largely insensitive or nostic values of TOX family members using a set of publicly refractory to PD-1, PD-L1 and CTLA4 blockade (2,4-6). accessible databases, including Oncomine, Kaplan-Meier Therefore, research has focused on identifying novel immu- plotter and cBioPortal. It was revealed that TOX expression notherapy targets or immunomodulatory factors that can profiles differed between lung cancer and normal tissues, be exploited to enhance the response to current immuno- and high expression of TOX mRNAs generally predicted therapeutic agents and address immunotherapy resistance in improved survival outcomes.