1 1 EBNA3 Proteins Regulate EBNA2 Binding to Distinct RBPJ Genomic
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Mutations and Altered Expression of SERPINF1 in Patients with Familial Otosclerosis Joanna L
Human Molecular Genetics, 2016, Vol. 25, No. 12 2393–2403 doi: 10.1093/hmg/ddw106 Advance Access Publication Date: 7 April 2016 Original Article ORIGINAL ARTICLE Mutations and altered expression of SERPINF1 in patients with familial otosclerosis Joanna L. Ziff1, Michael Crompton1, Harry R.F. Powell2, Jeremy A. Lavy2, Christopher P. Aldren3, Karen P. Steel4,†, Shakeel R. Saeed1,2 and Sally J. Dawson1,* 1UCL Ear Institute, University College London, London WC1X 8EE, UK, 2Royal National Throat Nose and Ear Hospital, London WC1X 8EE, UK, 3Department of ENT Surgery, The Princess Margaret Hospital, Windsor SL4 3SJ, UK and 4Wellcome Trust Sanger Institute, Hinxton CB10 1SA, UK *To whom correspondence should be addressed. Tel: þ44 2076798935; Email: [email protected] Abstract Otosclerosis is a relatively common heterogenous condition, characterized by abnormal bone remodelling in the otic capsule leading to fixation of the stapedial footplate and an associated conductive hearing loss. Although familial linkage and candidate gene association studies have been performed in recent years, little progress has been made in identifying disease- causing genes. Here, we used whole-exome sequencing in four families exhibiting dominantly inherited otosclerosis to identify 23 candidate variants (reduced to 9 after segregation analysis) for further investigation in a secondary cohort of 84 familial cases. Multiple mutations were found in the SERPINF1 (Serpin Peptidase Inhibitor, Clade F) gene which encodes PEDF (pigment epithelium-derived factor), a potent inhibitor of angiogenesis and known regulator of bone density. Six rare heterozygous SERPINF1 variants were found in seven patients in our familial otosclerosis cohort; three are missense mutations predicted to be deleterious to protein function. -
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. -
Cyclin D1 Is a Direct Transcriptional Target of GATA3 in Neuroblastoma Tumor Cells
Oncogene (2010) 29, 2739–2745 & 2010 Macmillan Publishers Limited All rights reserved 0950-9232/10 $32.00 www.nature.com/onc SHORT COMMUNICATION Cyclin D1 is a direct transcriptional target of GATA3 in neuroblastoma tumor cells JJ Molenaar1,2, ME Ebus1, J Koster1, E Santo1, D Geerts1, R Versteeg1 and HN Caron2 1Department of Human Genetics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands and 2Department of Pediatric Oncology, Emma Kinderziekenhuis, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands Almost all neuroblastoma tumors express excess levels of 2000). Several checkpoints normally prevent premature Cyclin D1 (CCND1) compared to normal tissues and cell-cycle progression and cell division. The crucial G1 other tumor types. Only a small percentage of these entry point is controlled by the D-type Cyclins that can neuroblastoma tumors have high-level amplification of the activate CDK4/6 that in turn phosphorylate the pRb Cyclin D1 gene. The other neuroblastoma tumors have protein. This results in a release of the E2F transcription equally high Cyclin D1 expression without amplification. factor that causes transcriptional upregulation of Silencing of Cyclin D1 expression was previously found to numerous genes involved in further progression of the trigger differentiation of neuroblastoma cells. Over- cell cycle (Sherr, 1996). expression of Cyclin D1 is therefore one of the most Neuroblastomas are embryonal tumors that originate frequent mechanisms with a postulated function in neuro- from precursor cells of the sympathetic nervous system. blastoma pathogenesis. The cause for the Cyclin D1 This tumor has a very poor prognosis and despite the overexpression is unknown. -
Characterization of BRCA1-Deficient Premalignant Tissues and Cancers Identifies Plekha5 As a Tumor Metastasis Suppressor
ARTICLE https://doi.org/10.1038/s41467-020-18637-9 OPEN Characterization of BRCA1-deficient premalignant tissues and cancers identifies Plekha5 as a tumor metastasis suppressor Jianlin Liu1,2, Ragini Adhav1,2, Kai Miao1,2, Sek Man Su1,2, Lihua Mo1,2, Un In Chan1,2, Xin Zhang1,2, Jun Xu1,2, Jianjie Li1,2, Xiaodong Shu1,2, Jianming Zeng 1,2, Xu Zhang1,2, Xueying Lyu1,2, Lakhansing Pardeshi1,3, ✉ ✉ Kaeling Tan1,3, Heng Sun1,2, Koon Ho Wong 1,3, Chuxia Deng 1,2 & Xiaoling Xu 1,2 1234567890():,; Single-cell whole-exome sequencing (scWES) is a powerful approach for deciphering intra- tumor heterogeneity and identifying cancer drivers. So far, however, simultaneous analysis of single nucleotide variants (SNVs) and copy number variations (CNVs) of a single cell has been challenging. By analyzing SNVs and CNVs simultaneously in bulk and single cells of premalignant tissues and tumors from mouse and human BRCA1-associated breast cancers, we discover an evolution process through which the tumors initiate from cells with SNVs affecting driver genes in the premalignant stage and malignantly progress later via CNVs acquired in chromosome regions with cancer driver genes. These events occur randomly and hit many putative cancer drivers besides p53 to generate unique genetic and pathological features for each tumor. Upon this, we finally identify a tumor metastasis suppressor Plekha5, whose deficiency promotes cancer metastasis to the liver and/or lung. 1 Cancer Centre, Faculty of Health Sciences, University of Macau, Macau, SAR, China. 2 Centre for Precision Medicine Research and Training, Faculty of Health Sciences, University of Macau, Macau, SAR, China. -
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. -
A Flexible Microfluidic System for Single-Cell Transcriptome Profiling
www.nature.com/scientificreports OPEN A fexible microfuidic system for single‑cell transcriptome profling elucidates phased transcriptional regulators of cell cycle Karen Davey1,7, Daniel Wong2,7, Filip Konopacki2, Eugene Kwa1, Tony Ly3, Heike Fiegler2 & Christopher R. Sibley 1,4,5,6* Single cell transcriptome profling has emerged as a breakthrough technology for the high‑resolution understanding of complex cellular systems. Here we report a fexible, cost‑efective and user‑ friendly droplet‑based microfuidics system, called the Nadia Instrument, that can allow 3′ mRNA capture of ~ 50,000 single cells or individual nuclei in a single run. The precise pressure‑based system demonstrates highly reproducible droplet size, low doublet rates and high mRNA capture efciencies that compare favorably in the feld. Moreover, when combined with the Nadia Innovate, the system can be transformed into an adaptable setup that enables use of diferent bufers and barcoded bead confgurations to facilitate diverse applications. Finally, by 3′ mRNA profling asynchronous human and mouse cells at diferent phases of the cell cycle, we demonstrate the system’s ability to readily distinguish distinct cell populations and infer underlying transcriptional regulatory networks. Notably this provided supportive evidence for multiple transcription factors that had little or no known link to the cell cycle (e.g. DRAP1, ZKSCAN1 and CEBPZ). In summary, the Nadia platform represents a promising and fexible technology for future transcriptomic studies, and other related applications, at cell resolution. Single cell transcriptome profling has recently emerged as a breakthrough technology for understanding how cellular heterogeneity contributes to complex biological systems. Indeed, cultured cells, microorganisms, biopsies, blood and other tissues can be rapidly profled for quantifcation of gene expression at cell resolution. -
Genome-Wide DNA Methylation Analysis of KRAS Mutant Cell Lines Ben Yi Tew1,5, Joel K
www.nature.com/scientificreports OPEN Genome-wide DNA methylation analysis of KRAS mutant cell lines Ben Yi Tew1,5, Joel K. Durand2,5, Kirsten L. Bryant2, Tikvah K. Hayes2, Sen Peng3, Nhan L. Tran4, Gerald C. Gooden1, David N. Buckley1, Channing J. Der2, Albert S. Baldwin2 ✉ & Bodour Salhia1 ✉ Oncogenic RAS mutations are associated with DNA methylation changes that alter gene expression to drive cancer. Recent studies suggest that DNA methylation changes may be stochastic in nature, while other groups propose distinct signaling pathways responsible for aberrant methylation. Better understanding of DNA methylation events associated with oncogenic KRAS expression could enhance therapeutic approaches. Here we analyzed the basal CpG methylation of 11 KRAS-mutant and dependent pancreatic cancer cell lines and observed strikingly similar methylation patterns. KRAS knockdown resulted in unique methylation changes with limited overlap between each cell line. In KRAS-mutant Pa16C pancreatic cancer cells, while KRAS knockdown resulted in over 8,000 diferentially methylated (DM) CpGs, treatment with the ERK1/2-selective inhibitor SCH772984 showed less than 40 DM CpGs, suggesting that ERK is not a broadly active driver of KRAS-associated DNA methylation. KRAS G12V overexpression in an isogenic lung model reveals >50,600 DM CpGs compared to non-transformed controls. In lung and pancreatic cells, gene ontology analyses of DM promoters show an enrichment for genes involved in diferentiation and development. Taken all together, KRAS-mediated DNA methylation are stochastic and independent of canonical downstream efector signaling. These epigenetically altered genes associated with KRAS expression could represent potential therapeutic targets in KRAS-driven cancer. Activating KRAS mutations can be found in nearly 25 percent of all cancers1. -
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. -
Targets TFIID and TFIIA to Prevent Activated Transcription
Downloaded from genesdev.cshlp.org on September 26, 2021 - Published by Cold Spring Harbor Laboratory Press The mammalian transcriptional repressor RBP (CBF1) targets TFIID and TFIIA to prevent activated transcription Ivan Olave, Danny Reinberg,1 and Lynne D. Vales2 Department of Biochemistry and 1Howard Hughes Medical Institute, University of Medicine and Dentistry of New Jersey, Robert Wood Johnson Medical School, Piscataway, New Jersey 08854 USA RBP is a cellular protein that functions as a transcriptional repressor in mammalian cells. RBP has elicited great interest lately because of its established roles in regulating gene expression, in Drosophila and mouse development, and as a component of the Notch signal transduction pathway. This report focuses on the mechanism by which RBP represses transcription and thereby regulates expression of a relatively simple, but natural, promoter. The results show that, irrespective of the close proximity between RBP and other transcription factors bound to the promoter, RBP does not occlude binding by these other transcription factors. Instead, RBP interacts with two transcriptional coactivators: dTAFII110, a subunit of TFIID, and TFIIA to repress transcription. The domain of dTAFII110 targeted by RBP is the same domain that interacts with TFIIA, but is disparate from the domain that interacts with Sp1. Repression can be thwarted when stable transcription preinitiation complexes are formed before RBP addition, suggesting that RBP interaction with TFIIA and TFIID perturbs optimal interactions between these coactivators. Consistent with this, interaction between RBP and TFIIA precludes interaction with dTAFII110. This is the first report of a repressor specifically targeting these two coactivators to subvert activated transcription. [Key Words: RBP; transcriptional repression; TFIIA/TFIID targeting] Received November 17, 1997; revised version accepted April 1, 1998. -
An RBPJ-Drosophila Model Reveals Dependence of RBPJ Protein Stability on the Formation of Transcription–Regulator Complexes
cells Article An RBPJ-Drosophila Model Reveals Dependence of RBPJ Protein Stability on the Formation of Transcription–Regulator Complexes Bernd M. Gahr 1,2, Franziska Brändle 1, Mirjam Zimmermann 1 and Anja C. Nagel 1,* 1 Institute of Genetics (240), University of Hohenheim, Garbenstr. 30, 70599 Stuttgart, Germany; [email protected] (B.M.G.); [email protected] (F.B.); [email protected] (M.Z.) 2 Present address: Molecular Cardiology, Department of Internal Medicine II, University of Ulm, Albert-Einstein-Allee 23, 89081 Ulm, Germany * Correspondence: [email protected]; Tel.: +49-711-45922210 Received: 23 August 2019; Accepted: 10 October 2019; Published: 14 October 2019 Abstract: Notch signaling activity governs widespread cellular differentiation in higher animals, including humans, and is involved in several congenital diseases and different forms of cancer. Notch signals are mediated by the transcriptional regulator RBPJ in a complex with activated Notch (NICD). Analysis of Notch pathway regulation in humans is hampered by a partial redundancy of the four Notch receptor copies, yet RBPJ is solitary, allowing its study in model systems. In Drosophila melanogaster, the RBPJ orthologue is encoded by Suppressor of Hairless [Su(H)]. Using genome engineering, we replaced Su(H) by murine RBPJ in order to study its function in the fly. In fact, RBPJ largely substitutes for Su(H)’s function, yet subtle phenotypes reflect increased Notch signaling activity. Accordingly, the binding of RBPJ to Hairless (H) protein, the general Notch antagonist in Drosophila, was considerably reduced compared to that of Su(H). An H-binding defective RBPJLLL mutant matched the respective Su(H)LLL allele: homozygotes were lethal due to extensive Notch hyperactivity. -
Detection of Enhancer-Associated Rearrangements Reveals Mechanisms of Oncogene Dysregulation in B-Cell Lymphoma
Published OnlineFirst July 30, 2015; DOI: 10.1158/2159-8290.CD-15-0370 ReseaRch aRticle Detection of Enhancer-Associated Rearrangements Reveals Mechanisms of Oncogene Dysregulation in B-cell Lymphoma Russell J.H. Ryan1,2, Yotam Drier1,2, Holly Whitton2, M. Joel Cotton1,2, Jasleen Kaur1,2, Robbyn Issner2, Shawn Gillespie1,2, Charles B. Epstein2, Valentina Nardi1, Aliyah R. Sohani1, Ephraim P. Hochberg3, and Bradley E. Bernstein1,2 abstRact B-cell lymphomas frequently contain genomic rearrangements that lead to onco- gene activation by heterologous distal regulatory elements. We used a novel approach called “pinpointing enhancer-associated rearrangements by chromatin immunoprecipitation,” or PEAR- ChIP, to simultaneously map enhancer activity and proximal rearrangements in lymphoma cell lines and patient biopsies. This method detects rearrangements involving known cancer genes, including CCND1, BCL2, MYC, PDCD1LG2, NOTCH1, CIITA, and SGK1, as well as novel enhancer duplication events of likely oncogenic significance. We identify lymphoma subtype–specific enhancers in the MYC locus that are silenced in lymphomas with MYC-activating rearrangements and are associated with germline polymorphisms that alter lymphoma risk. We show that BCL6-locus enhancers are acetylated by the BCL6-activating transcription factor MEF2B, and can undergo genomic duplication, or target the MYC promoter for activation in the context of a “pseudo-double-hit” t(3;8)(q27;q24) rearrangement linking the BCL6 and MYC loci. Our work provides novel insights regarding enhancer-driven oncogene activa- tion in lymphoma. SIGNIFICANCE: We demonstrate a novel approach for simultaneous detection of genomic rearrange- ments and enhancer activity in tumor biopsies. We identify novel mechanisms of enhancer-driven regu- lation of the oncogenes MYC and BCL6, and show that the BCL6 locus can serve as an enhancer donor in an “enhancer hijacking” translocation. -
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