Histone Acetyltransferases and Stem Cell Identity
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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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. -
Functional Roles of Bromodomain Proteins in Cancer
cancers Review Functional Roles of Bromodomain Proteins in Cancer Samuel P. Boyson 1,2, Cong Gao 3, Kathleen Quinn 2,3, Joseph Boyd 3, Hana Paculova 3 , Seth Frietze 3,4,* and Karen C. Glass 1,2,4,* 1 Department of Pharmaceutical Sciences, Albany College of Pharmacy and Health Sciences, Colchester, VT 05446, USA; [email protected] 2 Department of Pharmacology, Larner College of Medicine, University of Vermont, Burlington, VT 05405, USA; [email protected] 3 Department of Biomedical and Health Sciences, University of Vermont, Burlington, VT 05405, USA; [email protected] (C.G.); [email protected] (J.B.); [email protected] (H.P.) 4 University of Vermont Cancer Center, Burlington, VT 05405, USA * Correspondence: [email protected] (S.F.); [email protected] (K.C.G.) Simple Summary: This review provides an in depth analysis of the role of bromodomain-containing proteins in cancer development. As readers of acetylated lysine on nucleosomal histones, bromod- omain proteins are poised to activate gene expression, and often promote cancer progression. We examined changes in gene expression patterns that are observed in bromodomain-containing proteins and associated with specific cancer types. We also mapped the protein–protein interaction network for the human bromodomain-containing proteins, discuss the cellular roles of these epigenetic regu- lators as part of nine different functional groups, and identify bromodomain-specific mechanisms in cancer development. Lastly, we summarize emerging strategies to target bromodomain proteins in cancer therapy, including those that may be essential for overcoming resistance. Overall, this review provides a timely discussion of the different mechanisms of bromodomain-containing pro- Citation: Boyson, S.P.; Gao, C.; teins in cancer, and an updated assessment of their utility as a therapeutic target for a variety of Quinn, K.; Boyd, J.; Paculova, H.; cancer subtypes. -
KAT6A Syndrome: Genotype-Phenotype Correlation in 76 Patients with Pathogenic KAT6A Variants
KAT6A Syndrome: genotype-phenotype correlation in 76 patients with pathogenic KAT6A variants. Item Type Article Authors Kennedy, Joanna;Goudie, David;Blair, Edward;Chandler, Kate;Joss, Shelagh;McKay, Victoria;Green, Andrew;Armstrong, Ruth;Lees, Melissa;Kamien, Benjamin;Hopper, Bruce;Tan, Tiong Yang;Yap, Patrick;Stark, Zornitza;Okamoto, Nobuhiko;Miyake, Noriko;Matsumoto, Naomichi;Macnamara, Ellen;Murphy, Jennifer L;McCormick, Elizabeth;Hakonarson, Hakon;Falk, Marni J;Li, Dong;Blackburn, Patrick;Klee, Eric;Babovic- Vuksanovic, Dusica;Schelley, Susan;Hudgins, Louanne;Kant, Sarina;Isidor, Bertrand;Cogne, Benjamin;Bradbury, Kimberley;Williams, Mark;Patel, Chirag;Heussler, Helen;Duff- Farrier, Celia;Lakeman, Phillis;Scurr, Ingrid;Kini, Usha;Elting, Mariet;Reijnders, Margot;Schuurs-Hoeijmakers, Janneke;Wafik, Mohamed;Blomhoff, Anne;Ruivenkamp, Claudia A L;Nibbeling, Esther;Dingemans, Alexander J M;Douine, Emilie D;Nelson, Stanley F;Arboleda, Valerie A;Newbury-Ecob, Ruth DOI 10.1038/s41436-018-0259-2 Journal Genetics in medicine : official journal of the American College of Medical Genetics Download date 30/09/2021 21:53:13 Link to Item http://hdl.handle.net/10147/627191 Find this and similar works at - http://www.lenus.ie/hse HHS Public Access Author manuscript Author ManuscriptAuthor Manuscript Author Genet Med Manuscript Author . Author manuscript; Manuscript Author available in PMC 2019 October 01. Published in final edited form as: Genet Med. 2019 April ; 21(4): 850–860. doi:10.1038/s41436-018-0259-2. KAT6A Syndrome: Genotype-phenotype correlation in 76 patients with pathogenic KAT6A variants A full list of authors and affiliations appears at the end of the article. Abstract Purpose: Mutations in KAT6A have recently been identified as a cause of syndromic developmental delay. -
DNA Methylation Regulates Discrimination of Enhancers From
Sharifi-Zarchi et al. BMC Genomics (2017) 18:964 DOI 10.1186/s12864-017-4353-7 RESEARCHARTICLE Open Access DNA methylation regulates discrimination of enhancers from promoters through a H3K4me1-H3K4me3 seesaw mechanism Ali Sharifi-Zarchi1,2,3,4†, Daniela Gerovska5†, Kenjiro Adachi6, Mehdi Totonchi3, Hamid Pezeshk7,8, Ryan J. Taft9, Hans R. Schöler6,10, Hamidreza Chitsaz2, Mehdi Sadeghi8,11, Hossein Baharvand3,12* and Marcos J. Araúzo-Bravo5,13,14* Abstract Background: DNA methylation at promoters is largely correlated with inhibition of gene expression. However, the role of DNA methylation at enhancers is not fully understood, although a crosstalk with chromatin marks is expected. Actually, there exist contradictory reports about positive and negative correlations between DNA methylation and H3K4me1, a chromatin hallmark of enhancers. Results: We investigated the relationship between DNA methylation and active chromatin marks through genome- wide correlations, and found anti-correlation between H3K4me1 and H3K4me3 enrichment at low and intermediate DNA methylation loci. We hypothesized “seesaw” dynamics between H3K4me1 and H3K4me3 in the low and intermediate DNA methylation range, in which DNA methylation discriminates between enhancers and promoters, marked by H3K4me1 and H3K4me3, respectively. Low methylated regions are H3K4me3 enriched, while those with intermediate DNA methylation levels are progressively H3K4me1 enriched. Additionally, the enrichment of H3K27ac, distinguishing active from primed enhancers, follows a plateau in the lower range of the intermediate DNA methylation level, corresponding to active enhancers, and decreases linearly in the higher range of the intermediate DNA methylation. Thus, the decrease of the DNA methylation switches smoothly the state of the enhancers from a primed to an active state. -
ONCOPANEL (Popv3)
ONCOPANEL (POPv3) TEST INFORMATION BACKGROUND: Somatic genetic alterations in oncogenes and tumor-suppressor genes contribute to the pathogenesis and evolution of human cancers. These alterations can provide prognostic and predictive information and stratify cancers for targeted therapeutic information. We classify these alterations into five tiers using the following guidelines: Tier 1: The alteration has well-established published evidence confirming clinical utility in this tumor type, in at least one of the following contexts: predicting response to treatment with an FDA-approved therapy; assessing prognosis; establishing a definitive diagnosis; or conferring an inherited increased risk of cancer to this patient and family. Tier 2: The alteration may have clinical utility in at least one of the following contexts: selection of an investigational therapy in clinical trials for this cancer type; limited evidence of prognostic association; supportive of a specific diagnosis; proven association of response to treatment with an FDA-approved therapy in a different type of cancer; or similar to a different mutation with a proven association with response to treatment with an FDA-approved therapyin this type of cancer. Tier 3: The alteration is of uncertain clinical utility, but may have a role as suggested by at least one of the following: demonstration of association with response to treatment in this cancer type in preclinical studies (e.g., in vitro studies or animal models); alteration in a biochemical pathway that has other known, therapeutically-targetable alterations; alteration in a highly conserved region of the protein predicted, in silico, to alter protein function; or selection of an investigational therapy for a different cancer type. -
KAT6A Amplifications Are Associated with Shorter Progression-Free Survival and Overall Survival in Patients with Endometrial Serous Carcinoma
PLOS ONE RESEARCH ARTICLE KAT6A amplifications are associated with shorter progression-free survival and overall survival in patients with endometrial serous carcinoma 1 2 2 2 2 Ozlen Saglam , Zhenya Tang , Guilin Tang , L. Jeffrey Medeiros , Gokce A. TorunerID * 1 Department of Surgical Pathology, Moffitt Cancer Center, Tampa, Florida, United States of America, 2 Department of Hematopathology, Section of Clinical Cytogenetics, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America * [email protected] a1111111111 a1111111111 Abstract a1111111111 a1111111111 Somatic copy number alterations (CNA) are common in endometrial serous carcinoma a1111111111 (ESC). We used the Tumor Cancer Genome Atlas Pan Cancer dataset (TCGA Pan Can) to explore the impact of somatic CNA and gene expression levels (mRNA) of cancer-related genes in ESC. Results were correlated with clinico-pathologic parameters such as age of onset, disease stage, progression-free survival (PFS) and overall survival (OS) (n = 108). OPEN ACCESS 1,449 genes with recurrent somatic CNA were identified, observed in 10% or more tumor Citation: Saglam O, Tang Z, Tang G, Medeiros LJ, samples. Somatic CNA and mRNA expression levels were highly correlated (r> = 0.6) for Toruner GA (2020) KAT6A amplifications are 383 genes. Among these, 45 genes were classified in the Tier 1 category of Cancer associated with shorter progression-free survival and overall survival in patients with endometrial Genome Census-Catalogue of Somatic Mutations in Cancer. Eighteen of 45 Tier 1 genes serous carcinoma. PLoS ONE 15(9): e0238477. had highly correlated somatic CNA and mRNA expression levels including ARNT, PIK3CA, https://doi.org/10.1371/journal.pone.0238477 TBLXR1, ASXL1, EIF4A2, HOOK3, IKBKB, KAT6A, TCEA1, KAT6B, ERBB2, BRD4, Editor: JesuÂs Maria Paramio, CIEMAT, SPAIN KEAP1, PRKACA, DNM2, SMARCA4, AKT2, SS18L1. -
Recognition of Cancer Mutations in Histone H3K36 by Epigenetic Writers and Readers Brianna J
EPIGENETICS https://doi.org/10.1080/15592294.2018.1503491 REVIEW Recognition of cancer mutations in histone H3K36 by epigenetic writers and readers Brianna J. Kleina, Krzysztof Krajewski b, Susana Restrepoa, Peter W. Lewis c, Brian D. Strahlb, and Tatiana G. Kutateladzea aDepartment of Pharmacology, University of Colorado School of Medicine, Aurora, CO, USA; bDepartment of Biochemistry & Biophysics, The University of North Carolina School of Medicine, Chapel Hill, NC, USA; cWisconsin Institute for Discovery, University of Wisconsin, Madison, WI, USA ABSTRACT ARTICLE HISTORY Histone posttranslational modifications control the organization and function of chromatin. In Received 30 May 2018 particular, methylation of lysine 36 in histone H3 (H3K36me) has been shown to mediate gene Revised 1 July 2018 transcription, DNA repair, cell cycle regulation, and pre-mRNA splicing. Notably, mutations at or Accepted 12 July 2018 near this residue have been causally linked to the development of several human cancers. These KEYWORDS observations have helped to illuminate the role of histones themselves in disease and to clarify Histone; H3K36M; cancer; the mechanisms by which they acquire oncogenic properties. This perspective focuses on recent PTM; methylation advances in discovery and characterization of histone H3 mutations that impact H3K36 methyla- tion. We also highlight findings that the common cancer-related substitution of H3K36 to methionine (H3K36M) disturbs functions of not only H3K36me-writing enzymes but also H3K36me-specific readers. The latter case suggests that the oncogenic effects could also be linked to the inability of readers to engage H3K36M. Introduction from yeast to humans and has been shown to have a variety of functions that range from the control Histone proteins are main components of the of gene transcription and DNA repair, to cell cycle nucleosome, the fundamental building block of regulation and nutrient stress response [8]. -
Benefits of Cancerplex
CancerPlexSM is a comprehensive genetic assessment of a patient’s tumor that guides oncologists towards effective treatment options. What is CancerPlex? CancerPlex is a next generation DNA sequencing test for solid SM tumors. The specific coding regions of over 400 known cancer Potential outcomes from CancerPlex genes are simultaneously determined using a small amount of Identification of variants associated with response or resis- DNA extracted from tumor samples, including formalin-fixed, tance to an FDA-approved therapy for the patient’s disease. paraffin-embedded (FFPE) tissue and cell blocks from fine-needle aspirates or effusions. This analysis is performed in a single assay, Identification of variants associated with response or resis- simplifying and streamlining the test ordering process, and eliminat- tance to a therapy associated with another clinical indication. ing time consuming serial testing. Clinically actionable information unique to each patient’s tumor is consolidated into a simple report. Identification of variants associated with a therapy(s) in CancerPlex reveals missense changes, insertions and deletions, clinical development. and previously described rearrangements of ALK, RET, and ROS. Benefits of CancerPlex: CancerPlex genes were selected because of their importance in tumor The average turn-around-time for CancerPlex is under 10 biology. Analyzing more genes increases the chance of discovering business days, dramatically shortening the waiting period for actionable findings that lead to more choices for treatment. Our initial the start of treatment. results indicate that CancerPlex analysis identifies actionable findings up to 20% more frequently than previously published studies. CancerPlex ordering is simple: KEW provides all necessary shipping materials, can facilitate tissue retrieval and return with Since knowledge of tumor biology changes rapidly, CancerPlex pathologists, and manages 3rd party payment for the test. -
Understanding Chronic Kidney Disease: Genetic and Epigenetic Approaches
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2017 Understanding Chronic Kidney Disease: Genetic And Epigenetic Approaches Yi-An Ko Ko University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Bioinformatics Commons, Genetics Commons, and the Systems Biology Commons Recommended Citation Ko, Yi-An Ko, "Understanding Chronic Kidney Disease: Genetic And Epigenetic Approaches" (2017). Publicly Accessible Penn Dissertations. 2404. https://repository.upenn.edu/edissertations/2404 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/2404 For more information, please contact [email protected]. Understanding Chronic Kidney Disease: Genetic And Epigenetic Approaches Abstract The work described in this dissertation aimed to better understand the genetic and epigenetic factors influencing chronic kidney disease (CKD) development. Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) significantly associated with chronic kidney disease. However, these studies have not effectively identified target genes for the CKD variants. Most of the identified variants are localized to non-coding genomic regions, and how they associate with CKD development is not well-understood. As GWAS studies only explain a small fraction of heritability, we hypothesized that epigenetic changes could explain part of this missing heritability. To identify potential gene targets of the genetic variants, we performed expression quantitative loci (eQTL) analysis, using genotyping arrays and RNA sequencing from human kidney samples. To identify the target genes of CKD-associated SNPs, we integrated the GWAS-identified SNPs with the eQTL results using a Bayesian colocalization method, coloc. This resulted in a short list of target genes, including PGAP3 and CASP9, two genes that have been shown to present with kidney phenotypes in knockout mice. -
Further Delineation of the Clinical Spectrum of KAT6B Disorders and Allelic Series of Pathogenic Variants
ARTICLE © American College of Medical Genetics and Genomics Further delineation of the clinical spectrum of KAT6B disorders and allelic series of pathogenic variants Li Xin Zhang1, Gabrielle Lemire, MD2, Claudia Gonzaga-Jauregui, PhD3, Sirinart Molidperee, Gr. Cert1, Carolina Galaz-Montoya, MD3, David S. Liu, MD3, Alain Verloes, MD PhD4, Amelle G. Shillington, DO5, Kosuke Izumi, MD PhD6, Alyssa L. Ritter, MS LCGC7, Beth Keena, MS LCGC6, Elaine Zackai, MD7,8, Dong Li, PhD9, Elizabeth Bhoj, MD PhD7, Jennifer M. Tarpinian, MS CGC10, Emma Bedoukian, MS LCGC10, Mary K. Kukolich, MD11, A. Micheil Innes, MD12, Grace U. Ediae, BSc13, Sarah L. Sawyer, MD PhD14, Karippoth Mohandas Nair, MD15, Para Chottil Soumya, MD15, Kinattinkara R. Subbaraman, MD15, Frank J. Probst, MD PhD3,16, Jennifer A. Bassetti, MD3,16, Reid V. Sutton, MD3,16, Richard A. Gibbs, PhD3, Chester Brown, MD PhD17, Philip M. Boone, MD PhD18, Ingrid A. Holm, MD MPH18, Marco Tartaglia, PhD19, Giovanni Battista Ferrero, MD PhD20, Marcello Niceta, MD PhD19, Maria Lisa Dentici, MD19, Francesca Clementina Radio, MD PhD19, Boris Keren, MD21, Constance F. Wells, MD22, Christine Coubes, MD22, Annie Laquerrière, MD PhD23, Jacqueline Aziza, MD24, Charlotte Dubucs, MD24, Sheela Nampoothiri, MD25, David Mowat, MD26, Millan S. Patel, MD27, Ana Bracho, MD28, Francisco Cammarata-Scalisi, MD29, Alper Gezdirici, MD30, Alberto Fernandez-Jaen, MD31, Natalie Hauser, MD32, Yuri A. Zarate, MD33, Katherine A. Bosanko, MS CGC33, Klaus Dieterich, MD PhD34, John C. Carey, MD MPH35, Jessica X. Chong, PhD36,37, Deborah A. Nickerson, PhD37,38, Michael J. Bamshad, MD36,37, Brendan H. Lee, MD PhD3, Xiang-Jiao Yang, PhD39, James R. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Supplementary Material
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 Neurol Neurosurg Psychiatry Page 1 / 45 SUPPLEMENTARY MATERIAL Appendix A1: Neuropsychological protocol. Appendix A2: Description of the four cases at the transitional stage. Table A1: Clinical status and center proportion in each batch. Table A2: Complete output from EdgeR. Table A3: List of the putative target genes. Table A4: Complete output from DIANA-miRPath v.3. Table A5: Comparison of studies investigating miRNAs from brain samples. Figure A1: Stratified nested cross-validation. Figure A2: Expression heatmap of miRNA signature. Figure A3: Bootstrapped ROC AUC scores. Figure A4: ROC AUC scores with 100 different fold splits. Figure A5: Presymptomatic subjects probability scores. Figure A6: Heatmap of the level of enrichment in KEGG pathways. Kmetzsch V, et al. J Neurol Neurosurg Psychiatry 2021; 92:485–493. doi: 10.1136/jnnp-2020-324647 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 Neurol Neurosurg Psychiatry Appendix A1. Neuropsychological protocol The PREV-DEMALS cognitive evaluation included standardized neuropsychological tests to investigate all cognitive domains, and in particular frontal lobe functions. The scores were provided previously (Bertrand et al., 2018). Briefly, global cognitive efficiency was evaluated by means of Mini-Mental State Examination (MMSE) and Mattis Dementia Rating Scale (MDRS). Frontal executive functions were assessed with Frontal Assessment Battery (FAB), forward and backward digit spans, Trail Making Test part A and B (TMT-A and TMT-B), Wisconsin Card Sorting Test (WCST), and Symbol-Digit Modalities test.