Cryptic Splicing Events in the Iron Transporter ABCB7 and Other Key Target Genes in SF3B1-Mutant Myelodysplastic Syndromes
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Regulation and Dysregulation of Chromosome Structure in Cancer
Regulation and Dysregulation of Chromosome Structure in Cancer The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Hnisz, Denes et al. “Regulation and Dysregulation of Chromosome Structure in Cancer.” Annual Review of Cancer Biology 2, 1 (March 2018): 21–40 © 2018 Annual Reviews As Published https://doi.org/10.1146/annurev-cancerbio-030617-050134 Version Author's final manuscript Citable link http://hdl.handle.net/1721.1/117286 Terms of Use Creative Commons Attribution-Noncommercial-Share Alike Detailed Terms http://creativecommons.org/licenses/by-nc-sa/4.0/ Regulation and dysregulation of chromosome structure in cancer Denes Hnisz1*, Jurian Schuijers1, Charles H. Li1,2, Richard A. Young1,2* 1 Whitehead Institute for Biomedical Research, 455 Main Street, Cambridge, MA 02142, USA 2 Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA * Corresponding authors Corresponding Authors: Denes Hnisz Whitehead Institute for Biomedical Research 455 Main Street Cambridge, MA 02142 Tel: (617) 258-7181 Fax: (617) 258-0376 [email protected] Richard A. Young Whitehead Institute for Biomedical Research 455 Main Street Cambridge, MA 02142 Tel: (617) 258-5218 Fax: (617) 258-0376 [email protected] 1 Summary Cancer arises from genetic alterations that produce dysregulated gene expression programs. Normal gene regulation occurs in the context of chromosome loop structures called insulated neighborhoods, and recent studies have shown that these structures are altered and can contribute to oncogene dysregulation in various cancer cells. We review here the types of genetic and epigenetic alterations that influence neighborhood structures and contribute to gene dysregulation in cancer, present models for insulated neighborhoods associated with the most prominent human oncogenes, and discuss how such models may lead to further advances in cancer diagnosis and therapy. -
ORAI1 and ORAI2 Modulate Murine Neutrophil Calcium Signaling, Cellular Activation, and Host Defense
ORAI1 and ORAI2 modulate murine neutrophil calcium signaling, cellular activation, and host defense Derayvia Grimesa,1, Ryan Johnsona,1, Madeline Pashosa, Celeste Cummingsa, Chen Kangb, Georgia R. Sampedroa, Eric Tycksenc, Helen J. McBrided, Rajan Sahb, Clifford A. Lowelle, and Regina A. Clemensa,2 aDepartment of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110; bDepartment of Internal Medicine, Washington University School of Medicine, St. Louis, MO 63110; cMcDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO 63110; dInflammation Research, Amgen, Thousand Oaks, CA 91320; and eDepartment of Laboratory Medicine, University of California, San Francisco, CA 94143 Edited by Michael D. Cahalan, University of California, Irvine, CA, and approved August 11, 2020 (received for review May 5, 2020) Calcium signals are initiated in immune cells by the process of in isoform features, such as activation or inactivation kinetics and store-operated calcium entry (SOCE), where receptor activation sensitivity to modulatory factors, also influence CRAC-channel triggers transient calcium release from the endoplasmic reticulum, function (2–10). ORAI1 and ORAI2 are broadly expressed in im- followed by opening of plasma-membrane calcium-release acti- mune cells, and humans with ORAI1 mutations develop a severe vated calcium (CRAC) channels. ORAI1, ORAI2, and ORAI3 are known combined immunodeficiency-like immunodeficiency, highlighting to comprise the CRAC channel; however, the contributions of indi- the importance of this isoform in immune function (11, 12). In mice, vidual isoforms to neutrophil function are not well understood. ORAI1 also appears to be the dominant functional isoform in im- Here, we show that loss of ORAI1 partially decreases calcium influx, mune cells, with substantial deficits in ORAI1-deficient T cells, while loss of both ORAI1 and ORAI2 completely abolishes SOCE. -
PARSANA-DISSERTATION-2020.Pdf
DECIPHERING TRANSCRIPTIONAL PATTERNS OF GENE REGULATION: A COMPUTATIONAL APPROACH by Princy Parsana A dissertation submitted to The Johns Hopkins University in conformity with the requirements for the degree of Doctor of Philosophy Baltimore, Maryland July, 2020 © 2020 Princy Parsana All rights reserved Abstract With rapid advancements in sequencing technology, we now have the ability to sequence the entire human genome, and to quantify expression of tens of thousands of genes from hundreds of individuals. This provides an extraordinary opportunity to learn phenotype relevant genomic patterns that can improve our understanding of molecular and cellular processes underlying a trait. The high dimensional nature of genomic data presents a range of computational and statistical challenges. This dissertation presents a compilation of projects that were driven by the motivation to efficiently capture gene regulatory patterns in the human transcriptome, while addressing statistical and computational challenges that accompany this data. We attempt to address two major difficulties in this domain: a) artifacts and noise in transcriptomic data, andb) limited statistical power. First, we present our work on investigating the effect of artifactual variation in gene expression data and its impact on trans-eQTL discovery. Here we performed an in-depth analysis of diverse pre-recorded covariates and latent confounders to understand their contribution to heterogeneity in gene expression measurements. Next, we discovered 673 trans-eQTLs across 16 human tissues using v6 data from the Genotype Tissue Expression (GTEx) project. Finally, we characterized two trait-associated trans-eQTLs; one in Skeletal Muscle and another in Thyroid. Second, we present a principal component based residualization method to correct gene expression measurements prior to reconstruction of co-expression networks. -
Mutated SF3B1 Is Associated with Transcript Isoform Changes of The
bioRxiv preprint doi: https://doi.org/10.1101/000992; this version posted July 13, 2014. 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 4.0 International license. Reyes et al. RESEARCH Mutated SF3B1 is associated with transcript isoform changes of the genes UQCC and RPL31 both in CLLs and uveal melanomas Alejandro Reyes1, Carolin Blume2, Vincent Pelechano1, Petra Jakob1, Lars M Steinmetz1,3, Thorsten Zenz2,4 and Wolfgang Huber1* *Correspondence: [email protected] 1European Molecular Biology Abstract Laboratory, Genome Biology Unit, 69117, Heidelberg Germany Background: Genome sequencing studies of chronic lympoid leukemia (CLL) Full list of author information is have provided a comprehensive overview of recurrent somatic mutations in coding available at the end of the article genes. One of the most intriguing discoveries has been the prevalence of mutations in the HEAT-repeat domain of the splicing factor SF3B1. A frequently observed variant is predicted to cause the substitution of a lysine with a glutamic acid at position 700 of the protein (K700E). However, the molecular consequences of the mutations are largely unknown. Results: To start exploring this question, we sequenced the transcriptomes of six samples: four samples of CLL tumour cells, of which two contained the K700E mutation in SF3B1, and CD19 positive cells from two healthy donors. We identified 41 genes that showed differential usage of exons statistically associated with the mutated status of SF3B1 (false discovery rate of 10%). -
Anti-Phospho-SF3B1 (Sap155) (Ser129) Pab
PD043 Page 1 For Research Use Only. Not for use in diagnostic procedures. Anti-Phospho-SF3B1 (Sap155) (Ser129) pAb CODE No. PD043 CLONALITY Polyclonal ISOTYPE Rabbit Ig, affinity purified QUANTITY 100 L SOURCE Purified IgG from rabbit serum IMMUNOGEN KLH conjugated synthetic peptide, RTMII(pS)PERL (corresponding to amino acid residues 124-133 of human SF3B1) FORMURATION PBS containing 50% Glycerol (pH 7.2). No preservative is contained. STORAGE This antibody solution is stable for one year from the date of purchase when stored at -20°C. APPLICATION-CONFIRMED Western blotting 1:1000 for chemiluminescence detection system SPECIES CROSS REACTIVITY on WB Species Human Mouse Rat Hamster Cell HeLa, Raji NIH/3T3, WR19L Not tested Not tested Reactivity Entrez Gene ID 23451 (Human), 81898 (Mouse) REFERENCES 1) Wang, C., et al., Genes Dev. 12, 1409-1414 (1998) 2) Shi, Y., et al., Mol Cell 23, 819-829 (2006) 3) Tanuma, N., et al., J. Biol. Chem., 283, 35805-35814 (2008) 4) Yoshida, K., et al., Nature 478, 64-69 (2011) 5) Rossi, D., et al., Blood 118, 6904-6908 (2011) 6) Quesada, V., et al., Nat Genet 44, 47-52 (2011) 7) Wang, L., et al., N Engl J Med. 365, 2497-2506 (2011) 8) Biankin, A. V., et al., Nature 491, 399-405 (2012) For more information, please visit our web site http://ruo.mbl.co.jp/ MEDICAL & BIOLOGICAL LABORATORIES CO., LTD. URL http://ruo.mbl.co.jp/ e-mail [email protected], TEL 052-238-1904 PD043 Page 2 P a g RELATED PRODUCTS e PD043 Anti-Phospho-SF3B1 (Sap155) (Ser129) pAb D138-3 Anti-Sap155 (SF3B12) mAb D221-3 Anti-Sap155 (SF3B1) -
Monoclonal B-Cell Lymphocytosis Is Characterized by Mutations in CLL Putative Driver Genes and Clonal Heterogeneity Many Years Before Disease Progression
Leukemia (2014) 28, 2395–2424 © 2014 Macmillan Publishers Limited All rights reserved 0887-6924/14 www.nature.com/leu LETTERS TO THE EDITOR Monoclonal B-cell lymphocytosis is characterized by mutations in CLL putative driver genes and clonal heterogeneity many years before disease progression Leukemia (2014) 28, 2395–2398; doi:10.1038/leu.2014.226 (Beckton Dickinson) and data analyzed using Cell Quest software. On the basis of FACS (fluorescence-activated cell sorting) analysis, we observed after enrichment an average of 91% of CD19+ cells Monoclonal B-cell lymphocytosis (MBL) is defined as an asympto- (range 76–99%) and 91% of the CD19+ fraction were CD19+/CD5+ matic expansion of clonal B cells with less than 5 × 109/L cells in the cells (range 66–99%). We used the values of the CD19+/CD5+ peripheral blood and without other manifestations of chronic fraction to calculate the leukemic B-cell fraction and reduce any lymphocytic leukemia (CLL; for example, lymphadenopathy, cyto- significant contamination of non-clonal B cells in each biopsy. DNA penias, constitutional symptoms).1 Approximately 1% of the MBL was extracted from the clonal B cells and non-clonal (that is, T cells) cohort develops CLL per year. Evidence suggests that nearly all CLL cells using the Gentra Puregene Cell Kit (Qiagen, Hilden, Germany). 2 fi fi cases are preceded by an MBL state. Our understanding of the Extracted DNAs were ngerprinted to con rm the relationship genetic basis, clonal architecture and evolution in CLL pathogenesis between samples of the same MBL individual and to rule out sample has undergone significant improvements in the last few years.3–8 In cross-contamination between individuals. -
SF3B2-Mediated RNA Splicing Drives Human Prostate Cancer Progression
Published OnlineFirst August 20, 2019; DOI: 10.1158/0008-5472.CAN-18-3965 Cancer Molecular Cell Biology Research SF3B2-Mediated RNA Splicing Drives Human Prostate Cancer Progression Norihiko Kawamura1,2, Keisuke Nimura1, Kotaro Saga1, Airi Ishibashi1, Koji Kitamura1,3, Hiromichi Nagano1, Yusuke Yoshikawa4, Kyoso Ishida1,5, Norio Nonomura2, Mitsuhiro Arisawa4, Jun Luo6, and Yasufumi Kaneda1 Abstract Androgen receptor splice variant-7 (AR-V7) is a General RNA splicing SF3B2 complex-mediated alternative RNA splicing constitutively active AR variant implicated in U2 castration-resistant prostate cancers. Here, we show U2 snRNA that the RNA splicing factor SF3B2, identified by 3’ 3’ in silico and CRISPR/Cas9 analyses, is a critical 5’ 3’ splice site 5’ SF3B7 AR-V7 5’ A U2AF2 AGA Exon ? determinant of expression and is correlated SF3B6(p14) SF3B4 SF3B1 SF3B4 SF3B1 with aggressive cancer phenotypes. Transcriptome SF3B5 SF3B2 SF3B3 SF3B2 SF3B3 and PAR-CLIP analyses revealed that SF3B2 con- SF3A3 SF3B2 complex SF3A3 SF3A1 SF3A1 SF3b complex trols the splicing of target genes, including AR, to AR pre-mRNA drive aggressive phenotypes. SF3B2-mediated CE3 aggressive phenotypes in vivo were reversed by AR-V7 mRNA AR mRNA AR-V7 knockout. Pladienolide B, an inhibitor of CE3 a splicing modulator of the SF3b complex, sup- Drive malignancy pressed the growth of tumors addicted to high While the SF3b complex is critical for general RNA splicing, SF3B2 promotes inclusion of the target exon through recognizing a specific RNA motif. SF3B2 expression. These findings support the idea © 2019 American Association for Cancer Research that alteration of the splicing pattern by high SF3B2 expression is one mechanism underlying prostate cancer progression and therapeutic resistance. -
DNA Replication Stress Response Involving PLK1, CDC6, POLQ
DNA replication stress response involving PLK1, CDC6, POLQ, RAD51 and CLASPIN upregulation prognoses the outcome of early/mid-stage non-small cell lung cancer patients C. Allera-Moreau, I. Rouquette, B. Lepage, N. Oumouhou, M. Walschaerts, E. Leconte, V. Schilling, K. Gordien, L. Brouchet, Mb Delisle, et al. To cite this version: C. Allera-Moreau, I. Rouquette, B. Lepage, N. Oumouhou, M. Walschaerts, et al.. DNA replica- tion stress response involving PLK1, CDC6, POLQ, RAD51 and CLASPIN upregulation prognoses the outcome of early/mid-stage non-small cell lung cancer patients. Oncogenesis, Nature Publishing Group: Open Access Journals - Option C, 2012, 1, pp.e30. 10.1038/oncsis.2012.29. hal-00817701 HAL Id: hal-00817701 https://hal.archives-ouvertes.fr/hal-00817701 Submitted on 9 Jun 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Distributed under a Creative Commons Attribution - NonCommercial - NoDerivatives| 4.0 International License Citation: Oncogenesis (2012) 1, e30; doi:10.1038/oncsis.2012.29 & 2012 Macmillan Publishers Limited All rights reserved 2157-9024/12 www.nature.com/oncsis ORIGINAL ARTICLE DNA replication stress response involving PLK1, CDC6, POLQ, RAD51 and CLASPIN upregulation prognoses the outcome of early/mid-stage non-small cell lung cancer patients C Allera-Moreau1,2,7, I Rouquette2,7, B Lepage3, N Oumouhou3, M Walschaerts4, E Leconte5, V Schilling1, K Gordien2, L Brouchet2, MB Delisle1,2, J Mazieres1,2, JS Hoffmann1, P Pasero6 and C Cazaux1 Lung cancer is the leading cause of cancer deaths worldwide. -
Supplemental Information
Supplemental information Dissection of the genomic structure of the miR-183/96/182 gene. Previously, we showed that the miR-183/96/182 cluster is an intergenic miRNA cluster, located in a ~60-kb interval between the genes encoding nuclear respiratory factor-1 (Nrf1) and ubiquitin-conjugating enzyme E2H (Ube2h) on mouse chr6qA3.3 (1). To start to uncover the genomic structure of the miR- 183/96/182 gene, we first studied genomic features around miR-183/96/182 in the UCSC genome browser (http://genome.UCSC.edu/), and identified two CpG islands 3.4-6.5 kb 5’ of pre-miR-183, the most 5’ miRNA of the cluster (Fig. 1A; Fig. S1 and Seq. S1). A cDNA clone, AK044220, located at 3.2-4.6 kb 5’ to pre-miR-183, encompasses the second CpG island (Fig. 1A; Fig. S1). We hypothesized that this cDNA clone was derived from 5’ exon(s) of the primary transcript of the miR-183/96/182 gene, as CpG islands are often associated with promoters (2). Supporting this hypothesis, multiple expressed sequences detected by gene-trap clones, including clone D016D06 (3, 4), were co-localized with the cDNA clone AK044220 (Fig. 1A; Fig. S1). Clone D016D06, deposited by the German GeneTrap Consortium (GGTC) (http://tikus.gsf.de) (3, 4), was derived from insertion of a retroviral construct, rFlpROSAβgeo in 129S2 ES cells (Fig. 1A and C). The rFlpROSAβgeo construct carries a promoterless reporter gene, the β−geo cassette - an in-frame fusion of the β-galactosidase and neomycin resistance (Neor) gene (5), with a splicing acceptor (SA) immediately upstream, and a polyA signal downstream of the β−geo cassette (Fig. -
Investigation of the Underlying Hub Genes and Molexular Pathogensis in Gastric Cancer by Integrated Bioinformatic Analyses
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.20.423656; this version posted December 22, 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. Investigation of the underlying hub genes and molexular pathogensis in gastric cancer by integrated bioinformatic analyses Basavaraj Vastrad1, Chanabasayya Vastrad*2 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.20.423656; this version posted December 22, 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 The high mortality rate of gastric cancer (GC) is in part due to the absence of initial disclosure of its biomarkers. The recognition of important genes associated in GC is therefore recommended to advance clinical prognosis, diagnosis and and treatment outcomes. The current investigation used the microarray dataset GSE113255 RNA seq data from the Gene Expression Omnibus database to diagnose differentially expressed genes (DEGs). Pathway and gene ontology enrichment analyses were performed, and a proteinprotein interaction network, modules, target genes - miRNA regulatory network and target genes - TF regulatory network were constructed and analyzed. Finally, validation of hub genes was performed. The 1008 DEGs identified consisted of 505 up regulated genes and 503 down regulated genes. -
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. -
Statistical and Bioinformatic Analysis of Hemimethylation Patterns in Non-Small Cell Lung Cancer
Statistical and Bioinformatic Analysis of Hemimethylation Patterns in Non-Small Cell Lung Cancer Shuying Sun ( [email protected] ) Texas State University San Marcos https://orcid.org/0000-0003-3974-6996 Austin Zane Texas A&M University College Station Carolyn Fulton Schreiner University Jasmine Philipoom Case Western Reserve University Research article Keywords: Methylation, Hemimethylation, Lung Cancer, Bioinformatics, Epigenetics Posted Date: October 12th, 2020 DOI: https://doi.org/10.21203/rs.3.rs-17794/v2 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Version of Record: A version of this preprint was published on March 12th, 2021. See the published version at https://doi.org/10.1186/s12885-021-07990-7. Page 1/29 Abstract Background: DNA methylation is an epigenetic event involving the addition of a methyl-group to a cytosine-guanine base pair (i.e., CpG site). It is associated with different cancers. Our research focuses on studying non- small cell lung cancer hemimethylation, which refers to methylation occurring on only one of the two DNA strands. Many studies often assume that methylation occurs on both DNA strands at a CpG site. However, recent publications show the existence of hemimethylation and its signicant impact. Therefore, it is important to identify cancer hemimethylation patterns. Methods: In this paper, we use the Wilcoxon signed rank test to identify hemimethylated CpG sites based on publicly available non-small cell lung cancer methylation sequencing data. We then identify two types of hemimethylated CpG clusters, regular and polarity clusters, and genes with large numbers of hemimethylated sites.