Building Bonds Between NHGRI and NICHD • NICHD Has Four ABMGG Boarded Clinical Geneticists • Drs
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Frequent Loss of Heterozygosity Targeting the Inactive X Chromosome in Melanoma
6476 Vol. 9, 6476–6482, December 15, 2003 Clinical Cancer Research Frequent Loss of Heterozygosity Targeting the Inactive X Chromosome in Melanoma James O. Indsto,1 Najah T. Nassif,2 INTRODUCTION Richard F. Kefford,1 and Graham J. Mann1 Chromosomal deletions and amplification events are fre- 1Westmead Institute for Cancer Research, University of Sydney at quent in advanced neoplasms and provide evidence for the Westmead Millennium Institute, Westmead, New South Wales, existence and location of putative tumor suppressor genes Australia, and 2Department of Cell and Molecular Biology, University (TSGs) and oncogenes. In melanoma, 9p and 10q deletions are of Technology, Sydney, New South Wales, Australia most frequent, and losses on 6q, 11q, 1p, 15p, 17q, and 18q are also frequently found (1, 2). However, no studies have focused on the X chromosome. In the human female, random inactiva- ABSTRACT tion of one copy of an X chromosome by hypermethylation is an After previous preliminary observations of paradoxical early event in embryogenesis, resulting in most tissues being a deletion events affecting the inactive X chromosome in mel- mosaic in terms of X inactivation status. Neoplasms, being anoma, we have surveyed the X chromosome for deletions clonal expansions of single precursor cells, usually share a using 23 polymorphic microsatellite markers in 28 inform- common X inactivation status. This can be conveniently assayed ative (female XX) metastatic melanomas. Ten tumors (36%) using the methylation-sensitive restriction enzyme HpaII, which showed at least one loss of heterozygosity (LOH) event, and has a recognition site within the highly polymorphic exon 1 in two cases an entire chromosome showed LOH at all CAG repeat (ARTR) in the androgen receptor (AR) gene. -
Prediction of Human Disease Genes by Human-Mouse Conserved Coexpression Analysis
Prediction of Human Disease Genes by Human-Mouse Conserved Coexpression Analysis Ugo Ala1., Rosario Michael Piro1., Elena Grassi1, Christian Damasco1, Lorenzo Silengo1, Martin Oti2, Paolo Provero1*, Ferdinando Di Cunto1* 1 Molecular Biotechnology Center, Department of Genetics, Biology and Biochemistry, University of Turin, Turin, Italy, 2 Department of Human Genetics and Centre for Molecular and Biomolecular Informatics, University Medical Centre Nijmegen, Nijmegen, The Netherlands Abstract Background: Even in the post-genomic era, the identification of candidate genes within loci associated with human genetic diseases is a very demanding task, because the critical region may typically contain hundreds of positional candidates. Since genes implicated in similar phenotypes tend to share very similar expression profiles, high throughput gene expression data may represent a very important resource to identify the best candidates for sequencing. However, so far, gene coexpression has not been used very successfully to prioritize positional candidates. Methodology/Principal Findings: We show that it is possible to reliably identify disease-relevant relationships among genes from massive microarray datasets by concentrating only on genes sharing similar expression profiles in both human and mouse. Moreover, we show systematically that the integration of human-mouse conserved coexpression with a phenotype similarity map allows the efficient identification of disease genes in large genomic regions. Finally, using this approach on 850 OMIM loci characterized by an unknown molecular basis, we propose high-probability candidates for 81 genetic diseases. Conclusion: Our results demonstrate that conserved coexpression, even at the human-mouse phylogenetic distance, represents a very strong criterion to predict disease-relevant relationships among human genes. Citation: Ala U, Piro RM, Grassi E, Damasco C, Silengo L, et al. -
Network-Based Approach to Identify Biomarkers Predicting Response
Network-based approach to identify biomarkers predicting response and prognosis for HER2-negative breast cancer treatment with taxane-anthracycline neoadjuvant chemotherapy Cui Jiang1, Shuo Wu1, Lei Jiang1, Zhichao Gao1, Xiaorui Li1, Yangyang Duan1, Na Li2 and Tao Sun1 1 Department of Medical Oncology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang, Liaoning, China 2 Institute of Translational Medicine, China Medical University, Shenyang, Liaoning, China ABSTRACT Objective. This study aims to identify effective gene networks and biomarkers to predict response and prognosis for HER2-negative breast cancer patients who received sequential taxane-anthracycline neoadjuvant chemotherapy. Materials and Methods. Transcriptome data of training dataset including 310 HER2- negative breast cancer who received taxane-anthracycline treatment and an indepen- dent validation set with 198 samples were analyzed by weighted gene co-expression network analysis (WGCNA) approach in R language. Gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis were performed for the selected genes. Module-clinical trait relationships were analyzed to explore the genes and pathways that associated with clinicopathological parameters. Log-rank tests and COX regression were used to identify the prognosis-related genes. Results. We found a significant correlation of an expression module with distant Submitted 15 January 2019 D D − Accepted 18 July 2019 relapse–free survival (HR 0.213, 95% CI [0.131–0.347], P 4.80E 9). This blue Published 3 September 2019 module contained genes enriched in biological process of hormone levels regulation, Corresponding author reproductive system, response to estradiol, cell growth and mammary gland develop- Tao Sun, ment as well as pathways including estrogen, apelin, cAMP, the PPAR signaling pathway [email protected] and fatty acid metabolism. -
C9orf72-Associated SMCR8 Protein Binds in the Ubiquitin Pathway and with Proteins Linked with Neurological Disease John L
Goodier et al. Acta Neuropathologica Communications (2020) 8:110 https://doi.org/10.1186/s40478-020-00982-x RESEARCH Open Access C9orf72-associated SMCR8 protein binds in the ubiquitin pathway and with proteins linked with neurological disease John L. Goodier1*, Alisha O. Soares1, Gavin C. Pereira1, Lauren R. DeVine2, Laura Sanchez3, Robert N. Cole2 and Jose Luis García-Pérez3,4 Abstract A pathogenic GGGCCC hexanucleotide expansion in the first intron/promoter region of the C9orf72 gene is the most common mutation associated with amyotrophic lateral sclerosis (ALS). The C9orf72 gene product forms a complex with SMCR8 (Smith-Magenis Syndrome Chromosome Region, Candidate 8) and WDR41 (WD Repeat domain 41) proteins. Recent studies have indicated roles for the complex in autophagy regulation, vesicle trafficking, and immune response in transgenic mice, however a direct connection with ALS etiology remains unclear. With the aim of increasing understanding of the multi-functional C9orf72-SMCR8-WDR41 complex, we determined by mass spectrometry analysis the proteins that directly associate with SMCR8. SMCR8 protein binds many components of the ubiquitin-proteasome system, and we demonstrate its poly-ubiquitination without obvious degradation. Evidence is also presented for localization of endogenous SMCR8 protein to cytoplasmic stress granules. However, in several cell lines we failed to reproduce previous observations that C9orf72 protein enters these granules. SMCR8 protein associates with many products of genes associated with various Mendelian neurological disorders in addition to ALS, implicating SMCR8-containing complexes in a range of neuropathologies. We reinforce previous observations that SMCR8 and C9orf72 protein levels are positively linked, and now show in vivo that SMCR8 protein levels are greatly reduced in brain tissues of C9orf72 gene expansion carrier individuals. -
Analyses of PDE-Regulated Phosphoproteomes Reveal Unique
Analyses of PDE-regulated phosphoproteomes reveal PNAS PLUS unique and specific cAMP-signaling modules in T cells Michael-Claude G. Beltejara, Ho-Tak Laua, Martin G. Golkowskia, Shao-En Onga, and Joseph A. Beavoa,1 aDepartment of Pharmacology, University of Washington, Seattle, WA 98195 Contributed by Joseph A. Beavo, May 28, 2017 (sent for review March 10, 2017; reviewed by Paul M. Epstein, Donald H. Maurice, and Kjetil Tasken) Specific functions for different cyclic nucleotide phosphodiester- to bias T-helper polarization toward Th2, Treg, or Th17 pheno- ases (PDEs) have not yet been identified in most cell types. types (13, 14). In a few cases increased cAMP may even potentiate Conventional approaches to study PDE function typically rely on the T-cell activation signal (15), particularly at early stages of measurements of global cAMP, general increases in cAMP- activation. Recent MS-based proteomic studies have been useful dependent protein kinase (PKA), or the activity of exchange in characterizing changes in the phosphoproteome of T cells under protein activated by cAMP (EPAC). Although newer approaches various stimuli such as T-cell receptor stimulation (16), prosta- using subcellularly targeted FRET reporter sensors have helped glandin signaling (17), and oxidative stress (18), so much of the define more compartmentalized regulation of cAMP, PKA, and total Jurkat phosphoproteome is known. Until now, however, no EPAC, they have limited ability to link this regulation to down- information on the regulation of phosphopeptides by PDEs has stream effector molecules and biological functions. To address this been available in these cells. problem, we have begun to use an unbiased mass spectrometry- Inhibitors of cAMP PDEs are useful tools to study PKA/EPAC- based approach coupled with treatment using PDE isozyme- mediated signaling, and selective inhibitors for each of the 11 PDE – selective inhibitors to characterize the phosphoproteomes of the families have been developed (19 21). -
Dynamic Erasure of Random X-Chromosome Inactivation During Ipsc Reprogramming
bioRxiv preprint doi: https://doi.org/10.1101/545558; this version posted February 9, 2019. 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 4.0 International license. Dynamic Erasure of Random X-Chromosome Inactivation during iPSC Reprogramming Adrian Janiszewski1,*, Irene Talon1,*, Juan Song1, Natalie De Geest1, San Kit To1, Greet Bervoets2,3, Jean-Christophe Marine2,3, Florian Rambow2,3, Vincent Pasque1,✉. 1 KU Leuven - University of Leuven, Department of Development and Regeneration, Herestraat 49, B-3000 Leuven, Belgium. 2 Laboratory for Molecular Cancer Biology, VIB Center for Cancer Biology 3 Department of Oncology, KU Leuven, Belgium ✉ Correspondence to: [email protected] (V.P.) * These authors contributed equally Format: Research paper ABSTRACT Background: Induction and reversal of chromatin silencing is critical for successful development, tissue homeostasis and the derivation of induced pluripotent stem cells (iPSCs). X-chromosome inactivation (XCI) and reactivation (XCR) in female cells represent chromosome-wide transitions between active and inactive chromatin states. While XCI has long been studied and provided important insights into gene regulation, the dynamics and mechanisms underlying the reversal of stable chromatin silencing of X-linked genes are much less understood. Here, we use allele- specific transcriptomic approaches to study XCR during mouse iPSC reprogramming in order to elucidate the timing and mechanisms of chromosome-wide reversal of gene silencing. Results: We show that XCR is hierarchical, with subsets of genes reactivating early, late and very late. -
Content Based Search in Gene Expression Databases and a Meta-Analysis of Host Responses to Infection
Content Based Search in Gene Expression Databases and a Meta-analysis of Host Responses to Infection A Thesis Submitted to the Faculty of Drexel University by Francis X. Bell in partial fulfillment of the requirements for the degree of Doctor of Philosophy November 2015 c Copyright 2015 Francis X. Bell. All Rights Reserved. ii Acknowledgments I would like to acknowledge and thank my advisor, Dr. Ahmet Sacan. Without his advice, support, and patience I would not have been able to accomplish all that I have. I would also like to thank my committee members and the Biomed Faculty that have guided me. I would like to give a special thanks for the members of the bioinformatics lab, in particular the members of the Sacan lab: Rehman Qureshi, Daisy Heng Yang, April Chunyu Zhao, and Yiqian Zhou. Thank you for creating a pleasant and friendly environment in the lab. I give the members of my family my sincerest gratitude for all that they have done for me. I cannot begin to repay my parents for their sacrifices. I am eternally grateful for everything they have done. The support of my sisters and their encouragement gave me the strength to persevere to the end. iii Table of Contents LIST OF TABLES.......................................................................... vii LIST OF FIGURES ........................................................................ xiv ABSTRACT ................................................................................ xvii 1. A BRIEF INTRODUCTION TO GENE EXPRESSION............................. 1 1.1 Central Dogma of Molecular Biology........................................... 1 1.1.1 Basic Transfers .......................................................... 1 1.1.2 Uncommon Transfers ................................................... 3 1.2 Gene Expression ................................................................. 4 1.2.1 Estimating Gene Expression ............................................ 4 1.2.2 DNA Microarrays ...................................................... -
1 Title 1 Loss of PABPC1 Is Compensated by Elevated PABPC4
bioRxiv preprint doi: https://doi.org/10.1101/2021.02.07.430165; this version posted February 8, 2021. 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. 1 1 Title 2 Loss of PABPC1 is compensated by elevated PABPC4 and correlates with transcriptome 3 changes 4 5 Jingwei Xie1, Xiaoyu Wei1, Yu Chen1, Kalle Gehring1, 2 6 7 1 Department of Biochemistry and Groupe de recherche axé sur la structure des 8 protéines, McGill University, Montreal, Quebec H3G 0B1, Canada 9 10 2 To whom correspondence should be addressed: Dept. of Biochemistry, McGill 11 University, 3649 Promenade Sir William Osler, Rm. 473, Montreal, QC H3G 0B1, 12 Canada. Tel.: 514-398-7287; Fax: 514-398-2983; E-mail: [email protected]. 13 14 15 16 Abstract 17 Cytoplasmic poly(A) binding protein (PABP) is an essential translation factor that binds to 18 the 3' tail of mRNAs to promote translation and regulate mRNA stability. PABPC1 is the 19 most abundant of several PABP isoforms that exist in mammals. Here, we used the 20 CRISPR/Cas genome editing system to shift the isoform composition in HEK293 cells. 21 Disruption of PABPC1 elevated PABPC4 levels. Transcriptome analysis revealed that the 22 shift in the dominant PABP isoform was correlated with changes in key transcriptional 23 regulators. This study provides insight into understanding the role of PABP isoforms in 24 development and differentiation. 25 Keywords 26 PABPC1, PABPC4, c-Myc 27 bioRxiv preprint doi: https://doi.org/10.1101/2021.02.07.430165; this version posted February 8, 2021. -
A Comprehensive Analysis of the MAGE Family As Prognostic and Diagnostic Markers for Hepatocellular Carcinoma
A Comprehensive Analysis of the MAGE Family as Prognostic and Diagnostic Markers for Hepatocellular Carcinoma Rong Li Guangdong Provincial Key Laboratory of Liver Disease Research, Guangdong province engineering laboratory for transplantation medicine, Third Aliated Hospital of Sun Yat-sen University Jiao Gong Department of Laboratory Medicine, Third Aliated Hospital of Sun Yat-sen University Cuicui Xiao Department of Anesthesiology, Cell-Gene therapy Translational Medicine Research Center, Third Aliated Hospital of Sun Yat-sen University Shuguang Zhu Department of Hepatic Surgery and Liver Transplantation Center, The Third Aliated Hospital of Sun Yat-sen University Zhongying Hu Guangdong provincial Key Laboratory of Liver Disease Research, Third Aliated Hospital of Sun Yat- sen University Jinliang Liang Guangdong Provincial Key Laboratory of Liver Disease Research, Third Aliated Hospital of Sun Yat- sen University Xuejiao Li Guangdong Provincial Key Laboratory of Liver Disease Research, Third Aliated Hospital of Sun Yat- sen University Xijing Yan Department of Hepatic Surgery and Liver Transplantation Center, Third Aliated Hospital of Sun Yat-sen University Xijian Zhang Department of Hepatic Surgery and Liver Transplantation Center, Third Aliated Hospital of Sun Yat-sen University Danyang Li Department of Infectious Diseases, Third Aliated Hospital of Sun Yat-sen University Wei Liu Guangdong Provincial Key Laboratory of Liver Disease Research, Guangdong province engineering laboratory for transplantation medicine, Third Aliated Hospital -
A Network Inference Approach to Understanding Musculoskeletal
A NETWORK INFERENCE APPROACH TO UNDERSTANDING MUSCULOSKELETAL DISORDERS by NIL TURAN A thesis submitted to The University of Birmingham for the degree of Doctor of Philosophy College of Life and Environmental Sciences School of Biosciences The University of Birmingham June 2013 University of Birmingham Research Archive e-theses repository This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder. ABSTRACT Musculoskeletal disorders are among the most important health problem affecting the quality of life and contributing to a high burden on healthcare systems worldwide. Understanding the molecular mechanisms underlying these disorders is crucial for the development of efficient treatments. In this thesis, musculoskeletal disorders including muscle wasting, bone loss and cartilage deformation have been studied using systems biology approaches. Muscle wasting occurring as a systemic effect in COPD patients has been investigated with an integrative network inference approach. This work has lead to a model describing the relationship between muscle molecular and physiological response to training and systemic inflammatory mediators. This model has shown for the first time that oxygen dependent changes in the expression of epigenetic modifiers and not chronic inflammation may be causally linked to muscle dysfunction. -
Establishment of a Typing Model for Diffuse Large B-Cell Lymphoma Based on B-Cell Receptor Repertoire Sequencing
Jiang et al. BMC Cancer (2021) 21:297 https://doi.org/10.1186/s12885-021-08015-z RESEARCH ARTICLE Open Access Establishment of a typing model for diffuse large B-cell lymphoma based on B-cell receptor repertoire sequencing Wenhua Jiang1†, Hailong Wang2†, Shiyong Zhou3†, Guoqing Zhu4, Mingyou Gao5, Kuo Zhao5, Limeng Zhang5, Xiaojing Xie5, Ning Zhao5, Caijuan Tian6, Zhenzhen Zhang6, Fang Yan6, Yi Pan7* and Pengfei Liu2* Abstract Background: The purpose of this study was to construct a new typing model for diffuse large B-cell lymphoma (DLBCL) patients based on the B-cell receptor (BCR) and explore its potential molecular mechanism. Methods: BCR repertoire sequencing and whole-exome sequencing were performed on formalin-fixed paraffin- embedded samples from 12 DLBCL patients. Subsequently, a typing model was built with cluster analysis, and prognostic indicators between the two groups were compared to verify the typing model. Then, mutation and bioinformatics analyses were conducted to investigate the potential biomarkers of prognostic differences between the two groups. Results: Based on BCR sequencing data, we divided patients into two clusters (cluster 1 and cluster 2); this classification differed from the traditional typing method (GCB and non-GCB), in which cluster 1 included some non-GCB patients. The progression-free survival (PFS), overall survival (OS), metastasis and Shannon diversity index of IGH V-J and survival after chemotherapy were significantly different (P < 0.05) between the two clusters, but no statistical significance was found between the GCB and non-GCB groups. The mutation status of 248 genes was significantly different between cluster 1 and cluster 2. -
Meta-Analysis of Human Cancer Microarrays Reveals GATA3 Is Integral to the Estrogen Receptor Alpha Pathway Brian J Wilson and Vincent Giguère*
Molecular Cancer BioMed Central Research Open Access Meta-analysis of human cancer microarrays reveals GATA3 is integral to the estrogen receptor alpha pathway Brian J Wilson and Vincent Giguère* Address: Molecular Oncology Group, Room H5-45, McGill University Health Centre, 687 Pine Avenue West, Montréal, Québec, H3A 1A1, Canada Email: Brian J Wilson - [email protected]; Vincent Giguère* - [email protected] * Corresponding author Published: 4 June 2008 Received: 28 November 2007 Accepted: 4 June 2008 Molecular Cancer 2008, 7:49 doi:10.1186/1476-4598-7-49 This article is available from: http://www.molecular-cancer.com/content/7/1/49 © 2008 Wilson and Giguère; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background: The transcription factor GATA3 has recently been shown to be necessary for mammary gland morphogenesis and luminal cell differentiation. There is also an increasing body of data linking GATA3 to the estrogen receptor α (ERα) pathway. Among these it was shown that GATA3 associates with the promoter of the ERα gene and ERα can reciprocally associate with the GATA3 gene. GATA3 has also been directly implicated in a differentiated phenotype in mouse models of mammary tumourigenesis. The purpose of our study was to compare coexpressed genes, by meta-analysis, of GATA3 and relate these to a similar analysis for ERα to determine the depth of overlap. Results: We have used a newly described method of meta-analysis of multiple cancer studies within the Oncomine database, focusing here predominantly upon breast cancer studies.