CBX3 Regulated by Mir-139 Promoted the Development of HCC by Regulating Cell Cycle Progression
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Table S1. List of Proteins in the BAHD1 Interactome
Table S1. List of proteins in the BAHD1 interactome BAHD1 nuclear partners found in this work yeast two-hybrid screen Name Description Function Reference (a) Chromatin adapters HP1α (CBX5) chromobox homolog 5 (HP1 alpha) Binds histone H3 methylated on lysine 9 and chromatin-associated proteins (20-23) HP1β (CBX1) chromobox homolog 1 (HP1 beta) Binds histone H3 methylated on lysine 9 and chromatin-associated proteins HP1γ (CBX3) chromobox homolog 3 (HP1 gamma) Binds histone H3 methylated on lysine 9 and chromatin-associated proteins MBD1 methyl-CpG binding domain protein 1 Binds methylated CpG dinucleotide and chromatin-associated proteins (22, 24-26) Chromatin modification enzymes CHD1 chromodomain helicase DNA binding protein 1 ATP-dependent chromatin remodeling activity (27-28) HDAC5 histone deacetylase 5 Histone deacetylase activity (23,29,30) SETDB1 (ESET;KMT1E) SET domain, bifurcated 1 Histone-lysine N-methyltransferase activity (31-34) Transcription factors GTF3C2 general transcription factor IIIC, polypeptide 2, beta 110kDa Required for RNA polymerase III-mediated transcription HEYL (Hey3) hairy/enhancer-of-split related with YRPW motif-like DNA-binding transcription factor with basic helix-loop-helix domain (35) KLF10 (TIEG1) Kruppel-like factor 10 DNA-binding transcription factor with C2H2 zinc finger domain (36) NR2F1 (COUP-TFI) nuclear receptor subfamily 2, group F, member 1 DNA-binding transcription factor with C4 type zinc finger domain (ligand-regulated) (36) PEG3 paternally expressed 3 DNA-binding transcription factor with -
Hepatitis C Virus As a Unique Human Model Disease to Define
viruses Review Hepatitis C Virus as a Unique Human Model Disease to Define Differences in the Transcriptional Landscape of T Cells in Acute versus Chronic Infection David Wolski and Georg M. Lauer * Liver Center at the Gastrointestinal Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA * Correspondence: [email protected]; Tel.: +1-617-724-7515 Received: 27 June 2019; Accepted: 23 July 2019; Published: 26 July 2019 Abstract: The hepatitis C virus is unique among chronic viral infections in that an acute outcome with complete viral elimination is observed in a minority of infected patients. This unique feature allows direct comparison of successful immune responses with those that fail in the setting of the same human infection. Here we review how this scenario can be used to achieve better understanding of transcriptional regulation of T-cell differentiation. Specifically, we discuss results from a study comparing transcriptional profiles of hepatitis C virus (HCV)-specific CD8 T-cells during early HCV infection between patients that do and do not control and eliminate HCV. Identification of early gene expression differences in key T-cell differentiation molecules as well as clearly distinct transcriptional networks related to cell metabolism and nucleosomal regulation reveal novel insights into the development of exhausted and memory T-cells. With additional transcriptional studies of HCV-specific CD4 and CD8 T-cells in different stages of infection currently underway, we expect HCV infection to become a valuable model disease to study human immunity to viruses. Keywords: viral hepatitis; hepatitis C virus; T cells; transcriptional regulation; transcription factors; metabolism; nucleosome 1. -
Development and Validation of a Novel Immune-Related Prognostic Model
Wang et al. J Transl Med (2020) 18:67 https://doi.org/10.1186/s12967-020-02255-6 Journal of Translational Medicine RESEARCH Open Access Development and validation of a novel immune-related prognostic model in hepatocellular carcinoma Zheng Wang1, Jie Zhu1, Yongjuan Liu3, Changhong Liu2, Wenqi Wang2, Fengzhe Chen1* and Lixian Ma1* Abstract Background: Growing evidence has suggested that immune-related genes play crucial roles in the development and progression of hepatocellular carcinoma (HCC). Nevertheless, the utility of immune-related genes for evaluating the prognosis of HCC patients are still lacking. The study aimed to explore gene signatures and prognostic values of immune-related genes in HCC. Methods: We comprehensively integrated gene expression data acquired from 374 HCC and 50 normal tissues in The Cancer Genome Atlas (TCGA). Diferentially expressed genes (DEGs) analysis and univariate Cox regression analysis were performed to identify DEGs that related to overall survival. An immune prognostic model was constructed using the Lasso and multivariate Cox regression analyses. Furthermore, Cox regression analysis was applied to identify independent prognostic factors in HCC. The correlation analysis between immune-related signature and immune cells infltration were also investigated. Finally, the signature was validated in an external independent dataset. Results: A total of 329 diferentially expressed immune‐related genes were detected. 64 immune‐related genes were identifed to be markedly related to overall survival in HCC patients using univariate Cox regression analysis. Then we established a TF-mediated network for exploring the regulatory mechanisms of these genes. Lasso and multivariate Cox regression analyses were applied to construct the immune-based prognostic model, which consisted of nine immune‐related genes. -
1714 Gene Comprehensive Cancer Panel Enriched for Clinically Actionable Genes with Additional Biologically Relevant Genes 400-500X Average Coverage on Tumor
xO GENE PANEL 1714 gene comprehensive cancer panel enriched for clinically actionable genes with additional biologically relevant genes 400-500x average coverage on tumor Genes A-C Genes D-F Genes G-I Genes J-L AATK ATAD2B BTG1 CDH7 CREM DACH1 EPHA1 FES G6PC3 HGF IL18RAP JADE1 LMO1 ABCA1 ATF1 BTG2 CDK1 CRHR1 DACH2 EPHA2 FEV G6PD HIF1A IL1R1 JAK1 LMO2 ABCB1 ATM BTG3 CDK10 CRK DAXX EPHA3 FGF1 GAB1 HIF1AN IL1R2 JAK2 LMO7 ABCB11 ATR BTK CDK11A CRKL DBH EPHA4 FGF10 GAB2 HIST1H1E IL1RAP JAK3 LMTK2 ABCB4 ATRX BTRC CDK11B CRLF2 DCC EPHA5 FGF11 GABPA HIST1H3B IL20RA JARID2 LMTK3 ABCC1 AURKA BUB1 CDK12 CRTC1 DCUN1D1 EPHA6 FGF12 GALNT12 HIST1H4E IL20RB JAZF1 LPHN2 ABCC2 AURKB BUB1B CDK13 CRTC2 DCUN1D2 EPHA7 FGF13 GATA1 HLA-A IL21R JMJD1C LPHN3 ABCG1 AURKC BUB3 CDK14 CRTC3 DDB2 EPHA8 FGF14 GATA2 HLA-B IL22RA1 JMJD4 LPP ABCG2 AXIN1 C11orf30 CDK15 CSF1 DDIT3 EPHB1 FGF16 GATA3 HLF IL22RA2 JMJD6 LRP1B ABI1 AXIN2 CACNA1C CDK16 CSF1R DDR1 EPHB2 FGF17 GATA5 HLTF IL23R JMJD7 LRP5 ABL1 AXL CACNA1S CDK17 CSF2RA DDR2 EPHB3 FGF18 GATA6 HMGA1 IL2RA JMJD8 LRP6 ABL2 B2M CACNB2 CDK18 CSF2RB DDX3X EPHB4 FGF19 GDNF HMGA2 IL2RB JUN LRRK2 ACE BABAM1 CADM2 CDK19 CSF3R DDX5 EPHB6 FGF2 GFI1 HMGCR IL2RG JUNB LSM1 ACSL6 BACH1 CALR CDK2 CSK DDX6 EPOR FGF20 GFI1B HNF1A IL3 JUND LTK ACTA2 BACH2 CAMTA1 CDK20 CSNK1D DEK ERBB2 FGF21 GFRA4 HNF1B IL3RA JUP LYL1 ACTC1 BAG4 CAPRIN2 CDK3 CSNK1E DHFR ERBB3 FGF22 GGCX HNRNPA3 IL4R KAT2A LYN ACVR1 BAI3 CARD10 CDK4 CTCF DHH ERBB4 FGF23 GHR HOXA10 IL5RA KAT2B LZTR1 ACVR1B BAP1 CARD11 CDK5 CTCFL DIAPH1 ERCC1 FGF3 GID4 HOXA11 IL6R KAT5 ACVR2A -
Xo GENE PANEL
xO GENE PANEL Targeted panel of 1714 genes | Tumor DNA Coverage: 500x | RNA reads: 50 million Onco-seq panel includes clinically relevant genes and a wide array of biologically relevant genes Genes A-C Genes D-F Genes G-I Genes J-L AATK ATAD2B BTG1 CDH7 CREM DACH1 EPHA1 FES G6PC3 HGF IL18RAP JADE1 LMO1 ABCA1 ATF1 BTG2 CDK1 CRHR1 DACH2 EPHA2 FEV G6PD HIF1A IL1R1 JAK1 LMO2 ABCB1 ATM BTG3 CDK10 CRK DAXX EPHA3 FGF1 GAB1 HIF1AN IL1R2 JAK2 LMO7 ABCB11 ATR BTK CDK11A CRKL DBH EPHA4 FGF10 GAB2 HIST1H1E IL1RAP JAK3 LMTK2 ABCB4 ATRX BTRC CDK11B CRLF2 DCC EPHA5 FGF11 GABPA HIST1H3B IL20RA JARID2 LMTK3 ABCC1 AURKA BUB1 CDK12 CRTC1 DCUN1D1 EPHA6 FGF12 GALNT12 HIST1H4E IL20RB JAZF1 LPHN2 ABCC2 AURKB BUB1B CDK13 CRTC2 DCUN1D2 EPHA7 FGF13 GATA1 HLA-A IL21R JMJD1C LPHN3 ABCG1 AURKC BUB3 CDK14 CRTC3 DDB2 EPHA8 FGF14 GATA2 HLA-B IL22RA1 JMJD4 LPP ABCG2 AXIN1 C11orf30 CDK15 CSF1 DDIT3 EPHB1 FGF16 GATA3 HLF IL22RA2 JMJD6 LRP1B ABI1 AXIN2 CACNA1C CDK16 CSF1R DDR1 EPHB2 FGF17 GATA5 HLTF IL23R JMJD7 LRP5 ABL1 AXL CACNA1S CDK17 CSF2RA DDR2 EPHB3 FGF18 GATA6 HMGA1 IL2RA JMJD8 LRP6 ABL2 B2M CACNB2 CDK18 CSF2RB DDX3X EPHB4 FGF19 GDNF HMGA2 IL2RB JUN LRRK2 ACE BABAM1 CADM2 CDK19 CSF3R DDX5 EPHB6 FGF2 GFI1 HMGCR IL2RG JUNB LSM1 ACSL6 BACH1 CALR CDK2 CSK DDX6 EPOR FGF20 GFI1B HNF1A IL3 JUND LTK ACTA2 BACH2 CAMTA1 CDK20 CSNK1D DEK ERBB2 FGF21 GFRA4 HNF1B IL3RA JUP LYL1 ACTC1 BAG4 CAPRIN2 CDK3 CSNK1E DHFR ERBB3 FGF22 GGCX HNRNPA3 IL4R KAT2A LYN ACVR1 BAI3 CARD10 CDK4 CTCF DHH ERBB4 FGF23 GHR HOXA10 IL5RA KAT2B LZTR1 ACVR1B BAP1 CARD11 CDK5 CTCFL DIAPH1 ERCC1 FGF3 GID4 -
Downloaded 13/6/12) (Kanehisa Et Al, 2010)
bioRxiv preprint doi: https://doi.org/10.1101/455709; this version posted October 30, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Coherent Transcription Factor Target Networks Illuminate Epithelial Remodelling and Oncogenic Notch Ian M. Overton1,2,3,4*, Andrew H. Sims1, Jeremy A. Owen2,5, Bret S. E. Heale1,6, Matthew J. Ford1,7, Alexander L. R. Lubbock1,8, Erola Pairo-Castineira1, Abdelkader Essafi1,9 1. MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK 2. Department of Systems Biology, Harvard University, Boston MA 02115, USA 3. Centre for Synthetic and Systems Biology (SynthSys), University of Edinburgh, Edinburgh EH9 3BF, UK 4. Centre for Cancer Research and Cell Biology, Queen’s University Belfast, Belfast BT9 7AE, UK 5. Department of Physics, Massachusetts Institute of Technology, Cambridge MA 02139, USA 6. Current address: Intermountain Healthcare, 3930 River Walk, West Valley City UT 84120, USA 7. Current address: Rosalind & Morris Goodman Cancer Research Centre, McGill University, Montreal H3A 0G4, Canada 8. Current address: Department of Biochemistry, Vanderbilt University, Nashville TN 37232, USA 9. Current address: School of Cellular and Molecular Medicine, University of Bristol, Bristol BS8 1TD, UK *Corresponding author: [email protected] Running title: Mapping Transcription Factor Networks Subject categories: Network biology; Chromatin, Epigenetics, Genomics & Functional Genomics Manuscript character count: 168,671 1 bioRxiv preprint doi: https://doi.org/10.1101/455709; this version posted October 30, 2018. -
Cbx3 Maintains Lineage Specificity During Neural Differentiation
Downloaded from genesdev.cshlp.org on September 27, 2021 - Published by Cold Spring Harbor Laboratory Press RESEARCH COMMUNICATION et al. 2013). However, Cbx3 is also enriched at promoters Cbx3 maintains lineage of mouse embryonic fibroblast (MEF)-derived pre-iPSCs specificity during neural (preinduced pluripotent stem cells), where it does not cor- relate with H3K9 methylation (Sridharan et al. 2013). differentiation RNAi knockdown of Cbx3 promotes reprogramming of fi- broblasts to iPSCs (Sridharan et al. 2013). Chengyang Huang,1,2 Trent Su,1 Yong Xue,1 1 3 1 Cbx3 plays important roles in developmental processes Chen Cheng, Fides D. Lay, Robin A. McKee, (Morikawa et al. 2013). In model systems, Cbx3 promotes Meiyang Li,2 Ajay Vashisht,1 James Wohlschlegel,1 neuronal maturation, kidney development, differentia- Bennett G. Novitch,4 Kathrin Plath,1 tion of ESCs to smooth muscle in culture, and embryonic Siavash K. Kurdistani,1 and Michael Carey1 arteriogenesis (Xiao et al. 2011; Dihazi et al. 2015; Oshiro et al. 2015). Little is known of how Cbx3 functions in dif- 1Department of Biological Chemistry, Eli and Edythe Broad ferentiation, but its promoter localization suggested that Center for Regenerative Medicine and Stem Cell Research, David it might directly affect transcription through the preinitia- Geffen School of Medicine, University of California at Los tion complex (PIC) (Grunberg and Hahn 2013; Allen and Angeles, Los Angeles California 90095, USA; 2Department of Taatjes 2015). The PIC is assembled in response to activa- Neurobiology, Shantou University Medical College, Shantou tors and requires the Mediator coactivator complex to re- 515041, China; 3Department of Molecular, Cell, and cruit the general transcription factors and Pol II (Chen Developmental Biology, University of California at Los Angeles, et al. -