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A Multi-Omics Interpretable Machine Learning Model Reveals Modes of Action of Small Molecules Natasha L
www.nature.com/scientificreports OPEN A Multi-Omics Interpretable Machine Learning Model Reveals Modes of Action of Small Molecules Natasha L. Patel-Murray1, Miriam Adam2, Nhan Huynh2, Brook T. Wassie2, Pamela Milani2 & Ernest Fraenkel 2,3* High-throughput screening and gene signature analyses frequently identify lead therapeutic compounds with unknown modes of action (MoAs), and the resulting uncertainties can lead to the failure of clinical trials. We developed an approach for uncovering MoAs through an interpretable machine learning model of transcriptomics, epigenomics, metabolomics, and proteomics. Examining compounds with benefcial efects in models of Huntington’s Disease, we found common MoAs for compounds with unrelated structures, connectivity scores, and binding targets. The approach also predicted highly divergent MoAs for two FDA-approved antihistamines. We experimentally validated these efects, demonstrating that one antihistamine activates autophagy, while the other targets bioenergetics. The use of multiple omics was essential, as some MoAs were virtually undetectable in specifc assays. Our approach does not require reference compounds or large databases of experimental data in related systems and thus can be applied to the study of agents with uncharacterized MoAs and to rare or understudied diseases. Unknown modes of action of drug candidates can lead to unpredicted consequences on efectiveness and safety. Computational methods, such as the analysis of gene signatures, and high-throughput experimental methods have accelerated the discovery of lead compounds that afect a specifc target or phenotype1–3. However, these advances have not dramatically changed the rate of drug approvals. Between 2000 and 2015, 86% of drug can- didates failed to earn FDA approval, with toxicity or a lack of efcacy being common reasons for their clinical trial termination4,5. -
Supplemental Table 1. Complete Gene Lists and GO Terms from Figure 3C
Supplemental Table 1. Complete gene lists and GO terms from Figure 3C. Path 1 Genes: RP11-34P13.15, RP4-758J18.10, VWA1, CHD5, AZIN2, FOXO6, RP11-403I13.8, ARHGAP30, RGS4, LRRN2, RASSF5, SERTAD4, GJC2, RHOU, REEP1, FOXI3, SH3RF3, COL4A4, ZDHHC23, FGFR3, PPP2R2C, CTD-2031P19.4, RNF182, GRM4, PRR15, DGKI, CHMP4C, CALB1, SPAG1, KLF4, ENG, RET, GDF10, ADAMTS14, SPOCK2, MBL1P, ADAM8, LRP4-AS1, CARNS1, DGAT2, CRYAB, AP000783.1, OPCML, PLEKHG6, GDF3, EMP1, RASSF9, FAM101A, STON2, GREM1, ACTC1, CORO2B, FURIN, WFIKKN1, BAIAP3, TMC5, HS3ST4, ZFHX3, NLRP1, RASD1, CACNG4, EMILIN2, L3MBTL4, KLHL14, HMSD, RP11-849I19.1, SALL3, GADD45B, KANK3, CTC- 526N19.1, ZNF888, MMP9, BMP7, PIK3IP1, MCHR1, SYTL5, CAMK2N1, PINK1, ID3, PTPRU, MANEAL, MCOLN3, LRRC8C, NTNG1, KCNC4, RP11, 430C7.5, C1orf95, ID2-AS1, ID2, GDF7, KCNG3, RGPD8, PSD4, CCDC74B, BMPR2, KAT2B, LINC00693, ZNF654, FILIP1L, SH3TC1, CPEB2, NPFFR2, TRPC3, RP11-752L20.3, FAM198B, TLL1, CDH9, PDZD2, CHSY3, GALNT10, FOXQ1, ATXN1, ID4, COL11A2, CNR1, GTF2IP4, FZD1, PAX5, RP11-35N6.1, UNC5B, NKX1-2, FAM196A, EBF3, PRRG4, LRP4, SYT7, PLBD1, GRASP, ALX1, HIP1R, LPAR6, SLITRK6, C16orf89, RP11-491F9.1, MMP2, B3GNT9, NXPH3, TNRC6C-AS1, LDLRAD4, NOL4, SMAD7, HCN2, PDE4A, KANK2, SAMD1, EXOC3L2, IL11, EMILIN3, KCNB1, DOK5, EEF1A2, A4GALT, ADGRG2, ELF4, ABCD1 Term Count % PValue Genes regulation of pathway-restricted GDF3, SMAD7, GDF7, BMPR2, GDF10, GREM1, BMP7, LDLRAD4, SMAD protein phosphorylation 9 6.34 1.31E-08 ENG pathway-restricted SMAD protein GDF3, SMAD7, GDF7, BMPR2, GDF10, GREM1, BMP7, LDLRAD4, phosphorylation -
High-Resolution Analysis of Chromosomal Breakpoints and Genomic Instability Identifies PTPRD As a Candidate Tumor Suppressor Gene in Neuroblastoma
Research Article High-Resolution Analysis of Chromosomal Breakpoints and Genomic Instability Identifies PTPRD as a Candidate Tumor Suppressor Gene in Neuroblastoma Raymond L. Stallings,1 Prakash Nair,1 John M. Maris,2 Daniel Catchpoole,3 Michael McDermott,4 Anne O’Meara,5 and Fin Breatnach5 1Children’s Cancer Research Institute and Department of Pediatrics, University of Texas Health Science Center at San Antonio, San Antonio, Texas; 2Division of Oncology, Children’s Hospital of Philadelphia and Department of Pediatrics, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania; 3The Tumor Bank, Children’s Hospital at Westmead, Sydney, New South Wales, Australia; and Departments of 4Pathology and 5Oncology, Our Lady’s Hospital for Sick Children, Dublin, Ireland Abstract and death from disease. Patient age, tumor stage, and several Although neuroblastoma is characterized by numerous different genetic abnormalities are important factors that influence clinical outcome. Loss of 1p and 11q, gain of 17q, and amplification recurrent, large-scale chromosomal imbalances, the genes MYCN targeted by such imbalances have remained elusive. We have of the oncogene are particularly strong genetic indicators of poor disease outcome (2–5). Two of these abnormalities, loss of 11q applied whole-genome oligonucleotide array comparative MYCN genomic hybridization (median probe spacing 6 kb) to 56 and amplification, form the basis for dividing advanced- stage neuroblastomas into genetic subtypes due to their rather neuroblastoma tumors and cell lines to identify genes involved with disease pathogenesis. This set oftumors was selected for striking inverse distribution in tumors (6, 7). Many other recurrent having either 11q loss or MYCN amplification, abnormalities partial chromosomal imbalances, including loss of 3p, 4p, 9p, and that define the two most common genetic subtypes of 14q and gain of 1q, 2p, 7q, and 11p, have been identified by metastatic neuroblastoma. -
Exploring Autophagy with Gene Ontology
Autophagy ISSN: 1554-8627 (Print) 1554-8635 (Online) Journal homepage: https://www.tandfonline.com/loi/kaup20 Exploring autophagy with Gene Ontology Paul Denny, Marc Feuermann, David P. Hill, Ruth C. Lovering, Helene Plun- Favreau & Paola Roncaglia To cite this article: Paul Denny, Marc Feuermann, David P. Hill, Ruth C. Lovering, Helene Plun- Favreau & Paola Roncaglia (2018) Exploring autophagy with Gene Ontology, Autophagy, 14:3, 419-436, DOI: 10.1080/15548627.2017.1415189 To link to this article: https://doi.org/10.1080/15548627.2017.1415189 © 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. View supplementary material Published online: 17 Feb 2018. Submit your article to this journal Article views: 1097 View Crossmark data Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=kaup20 AUTOPHAGY, 2018 VOL. 14, NO. 3, 419–436 https://doi.org/10.1080/15548627.2017.1415189 RESEARCH PAPER - BASIC SCIENCE Exploring autophagy with Gene Ontology Paul Denny a,†,§, Marc Feuermann b,§, David P. Hill c,f,§, Ruth C. Lovering a,§, Helene Plun-Favreau d and Paola Roncaglia e,f,§ aFunctional Gene Annotation, Institute of Cardiovascular Science, University College London, London, UK; bSIB Swiss Institute of Bioinformatics, Geneva, Switzerland; cThe Jackson Laboratory, Bar Harbor, ME, USA; dDepartment of Molecular Neuroscience, UCL Institute of Neurology, London, UK; eEuropean Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Genome Campus, Hinxton, Cambridge, UK; fThe Gene Ontology Consortium ABSTRACT ARTICLE HISTORY Autophagy is a fundamental cellular process that is well conserved among eukaryotes. It is one of the Received 18 May 2017 strategies that cells use to catabolize substances in a controlled way. -
Downloaded Per Proteome Cohort Via the Web- Site Links of Table 1, Also Providing Information on the Deposited Spectral Datasets
www.nature.com/scientificreports OPEN Assessment of a complete and classifed platelet proteome from genome‑wide transcripts of human platelets and megakaryocytes covering platelet functions Jingnan Huang1,2*, Frauke Swieringa1,2,9, Fiorella A. Solari2,9, Isabella Provenzale1, Luigi Grassi3, Ilaria De Simone1, Constance C. F. M. J. Baaten1,4, Rachel Cavill5, Albert Sickmann2,6,7,9, Mattia Frontini3,8,9 & Johan W. M. Heemskerk1,9* Novel platelet and megakaryocyte transcriptome analysis allows prediction of the full or theoretical proteome of a representative human platelet. Here, we integrated the established platelet proteomes from six cohorts of healthy subjects, encompassing 5.2 k proteins, with two novel genome‑wide transcriptomes (57.8 k mRNAs). For 14.8 k protein‑coding transcripts, we assigned the proteins to 21 UniProt‑based classes, based on their preferential intracellular localization and presumed function. This classifed transcriptome‑proteome profle of platelets revealed: (i) Absence of 37.2 k genome‑ wide transcripts. (ii) High quantitative similarity of platelet and megakaryocyte transcriptomes (R = 0.75) for 14.8 k protein‑coding genes, but not for 3.8 k RNA genes or 1.9 k pseudogenes (R = 0.43–0.54), suggesting redistribution of mRNAs upon platelet shedding from megakaryocytes. (iii) Copy numbers of 3.5 k proteins that were restricted in size by the corresponding transcript levels (iv) Near complete coverage of identifed proteins in the relevant transcriptome (log2fpkm > 0.20) except for plasma‑derived secretory proteins, pointing to adhesion and uptake of such proteins. (v) Underrepresentation in the identifed proteome of nuclear‑related, membrane and signaling proteins, as well proteins with low‑level transcripts. -
Lipopolysaccharide Treatment Induces Genome-Wide Pre-Mrna Splicing
The Author(s) BMC Genomics 2016, 17(Suppl 7):509 DOI 10.1186/s12864-016-2898-5 RESEARCH Open Access Lipopolysaccharide treatment induces genome-wide pre-mRNA splicing pattern changes in mouse bone marrow stromal stem cells Ao Zhou1,2, Meng Li3,BoHe3, Weixing Feng3, Fei Huang1, Bing Xu4,6, A. Keith Dunker1, Curt Balch5, Baiyan Li6, Yunlong Liu1,4 and Yue Wang4* From The International Conference on Intelligent Biology and Medicine (ICIBM) 2015 Indianapolis, IN, USA. 13-15 November 2015 Abstract Background: Lipopolysaccharide (LPS) is a gram-negative bacterial antigen that triggers a series of cellular responses. LPS pre-conditioning was previously shown to improve the therapeutic efficacy of bone marrow stromal cells/bone-marrow derived mesenchymal stem cells (BMSCs) for repairing ischemic, injured tissue. Results: In this study, we systematically evaluated the effects of LPS treatment on genome-wide splicing pattern changes in mouse BMSCs by comparing transcriptome sequencing data from control vs. LPS-treated samples, revealing 197 exons whose BMSC splicing patterns were altered by LPS. Functional analysis of these alternatively spliced genes demonstrated significant enrichment of phosphoproteins, zinc finger proteins, and proteins undergoing acetylation. Additional bioinformatics analysis strongly suggest that LPS-induced alternatively spliced exons could have major effects on protein functions by disrupting key protein functional domains, protein-protein interactions, and post-translational modifications. Conclusion: Although it is still to be determined whether such proteome modifications improve BMSC therapeutic efficacy, our comprehensive splicing characterizations provide greater understanding of the intracellular mechanisms that underlie the therapeutic potential of BMSCs. Keywords: Alternative splicing, Lipopolysaccharide, Mesenchymal stem cells Background developmental pathways, and other processes associated Alternative splicing (AS) is important for gene regulation with multicellular organisms. -
A Radiation Hybrid Map of Chicken Chromosome 4
A radiation hybrid map of chicken Chromosome 4 Tarik S.K.M. Rabie,1* Richard P.M.A. Crooijmans,1 Mireille Morisson,2 Joanna Andryszkiewicz,1 Jan J. van der Poel,1 Alain Vignal,2 Martien A.M. Groenen1 1Wageningen Institute of Animal Sciences, Animal Breeding and Genetics Group, Wageningen University, Marijkeweg 40, 6709 PG Wageningen, The Netherlands 2Laboratoire de ge´ne´tique cellulaire, Institut national de la recherche agronomique, 31326 Castanet-Tolosan, France Received: 15 December 2003 / Accepted: 16 March 2004 Comparative genomics plays an important role in Abstract the understanding of genome dynamics during ev- The mapping resolution of the physical map for olution and as a tool for the transfer of mapping chicken Chromosome 4 (GGA4) was improved by a information from species with gene-dense maps to combination of radiation hybrid (RH) mapping and species whose maps are less well developed (O‘Bri- bacterial artificial chromosome (BAC) mapping. The en et al. 1993, 1999). For farm animals, therefore, ChickRH6 hybrid panel was used to construct an RH the human and mouse have been the logical choice map of GGA4. Eleven microsatellites known to be as the model species used for this comparison. located on GGA4 were included as anchors to the Medium-resolution comparative maps have been genetic linkage map for this chromosome. Based on published for many of the livestock species, in- the known conserved synteny between GGA4 and cluding pig, cattle, sheep, and horse, identifying human Chromosomes 4 and X, sequences were large regions of conserved synteny between these identified for the orthologous chicken genes from species and man and mouse. -
Molecular Targeting and Enhancing Anticancer Efficacy of Oncolytic HSV-1 to Midkine Expressing Tumors
University of Cincinnati Date: 12/20/2010 I, Arturo R Maldonado , hereby submit this original work as part of the requirements for the degree of Doctor of Philosophy in Developmental Biology. It is entitled: Molecular Targeting and Enhancing Anticancer Efficacy of Oncolytic HSV-1 to Midkine Expressing Tumors Student's name: Arturo R Maldonado This work and its defense approved by: Committee chair: Jeffrey Whitsett Committee member: Timothy Crombleholme, MD Committee member: Dan Wiginton, PhD Committee member: Rhonda Cardin, PhD Committee member: Tim Cripe 1297 Last Printed:1/11/2011 Document Of Defense Form Molecular Targeting and Enhancing Anticancer Efficacy of Oncolytic HSV-1 to Midkine Expressing Tumors A dissertation submitted to the Graduate School of the University of Cincinnati College of Medicine in partial fulfillment of the requirements for the degree of DOCTORATE OF PHILOSOPHY (PH.D.) in the Division of Molecular & Developmental Biology 2010 By Arturo Rafael Maldonado B.A., University of Miami, Coral Gables, Florida June 1993 M.D., New Jersey Medical School, Newark, New Jersey June 1999 Committee Chair: Jeffrey A. Whitsett, M.D. Advisor: Timothy M. Crombleholme, M.D. Timothy P. Cripe, M.D. Ph.D. Dan Wiginton, Ph.D. Rhonda D. Cardin, Ph.D. ABSTRACT Since 1999, cancer has surpassed heart disease as the number one cause of death in the US for people under the age of 85. Malignant Peripheral Nerve Sheath Tumor (MPNST), a common malignancy in patients with Neurofibromatosis, and colorectal cancer are midkine- producing tumors with high mortality rates. In vitro and preclinical xenograft models of MPNST were utilized in this dissertation to study the role of midkine (MDK), a tumor-specific gene over- expressed in these tumors and to test the efficacy of a MDK-transcriptionally targeted oncolytic HSV-1 (oHSV). -
Promoterless Transposon Mutagenesis Drives Solid Cancers Via Tumor Suppressor Inactivation
bioRxiv preprint doi: https://doi.org/10.1101/2020.08.17.254565; this version posted August 17, 2020. 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. 1 Promoterless Transposon Mutagenesis Drives Solid Cancers via Tumor Suppressor Inactivation 2 Aziz Aiderus1, Ana M. Contreras-Sandoval1, Amanda L. Meshey1, Justin Y. Newberg1,2, Jerrold M. Ward3, 3 Deborah Swing4, Neal G. Copeland2,3,4, Nancy A. Jenkins2,3,4, Karen M. Mann1,2,3,4,5,6,7, and Michael B. 4 Mann1,2,3,4,6,7,8,9 5 1Department of Molecular Oncology, Moffitt Cancer Center & Research Institute, Tampa, FL, USA 6 2Cancer Research Program, Houston Methodist Research Institute, Houston, Texas, USA 7 3Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), 8 Singapore, Republic of Singapore 9 4Mouse Cancer Genetics Program, Center for Cancer Research, National Cancer Institute, Frederick, 10 Maryland, USA 11 5Departments of Gastrointestinal Oncology & Malignant Hematology, Moffitt Cancer Center & Research 12 Institute, Tampa, FL, USA 13 6Cancer Biology and Evolution Program, Moffitt Cancer Center & Research Institute, Tampa, FL, USA 14 7Department of Oncologic Sciences, Morsani College of Medicine, University of South Florida, Tampa, FL, 15 USA. 16 8Donald A. Adam Melanoma and Skin Cancer Research Center of Excellence, Moffitt Cancer Center, Tampa, 17 FL, USA 18 9Department of Cutaneous Oncology, Moffitt Cancer Center & Research Institute, Tampa, FL, USA 19 These authors contributed equally: Aziz Aiderus, Ana M. -
RNA Sequencing Analyses Reveal Differentially Expressed Genes and Pathways As Notch2 Targets in B-Cell Lymphoma
www.oncotarget.com Oncotarget, 2020, Vol. 11, (No. 48), pp: 4527-4540 Research Paper RNA sequencing analyses reveal differentially expressed genes and pathways as Notch2 targets in B-cell lymphoma Ashok Arasu1, Pavithra Balakrishnan1 and Thirunavukkarasu Velusamy1 1Department of Biotechnology, School of Biotechnology and Genetic Engineering, Bharathiar University, Coimbatore, India Correspondence to: Thirunavukkarasu Velusamy, email: [email protected] Keywords: SMZL; Notch2; RNA sequencing; PI3K/AKT; NF-kB Received: August 04, 2020 Accepted: October 17, 2020 Published: December 01, 2020 Copyright: © 2020 Arasu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT Splenic marginal zone lymphoma (SMZL) is a low grade, indolent B-cell neoplasm that comprises approximately 10% of all lymphoma. Notch2, a pivotal gene for marginal zone differentiation is found to be mutated in SMZL. Deregulated Notch2 signaling has been involved in tumorigenesis and also in B-cell malignancies. However the role of Notch2 and the downstream pathways that it influences for development of B-cell lymphoma remains unclear. In recent years, RNA sequencing (RNA-Seq) has become a functional and convincing technology for profiling gene expression and to discover new genes and transcripts that are involved in disease development in a single experiment. In the present study, using transcriptome sequencing approach, we have identified key genes and pathways that are probably the underlying cause in the development of B-cell lymphoma. We have identified a total of 15,083 differentially expressed genes (DEGs) and 1067 differentially expressed transcripts (DETs) between control and Notch2 knockdown B cells. -
Differentially Expressed Genes in Aneurysm Tissue Compared With
On-line Table: Differentially expressed genes in aneurysm tissue compared with those in control tissue Fold False Discovery Direction of Gene Entrez Gene Name Function Change P Value Rate (q Value) Expression AADAC Arylacetamide deacetylase Positive regulation of triglyceride 4.46 1.33E-05 2.60E-04 Up-regulated catabolic process ABCA6 ATP-binding cassette, subfamily A (ABC1), Integral component of membrane 3.79 9.15E-14 8.88E-12 Up-regulated member 6 ABCC3 ATP-binding cassette, subfamily C (CFTR/MRP), ATPase activity, coupled to 6.63 1.21E-10 7.33E-09 Up-regulated member 3 transmembrane movement of substances ABI3 ABI family, member 3 Peptidyl-tyrosine phosphorylation 6.47 2.47E-05 4.56E-04 Up-regulated ACKR1 Atypical chemokine receptor 1 (Duffy blood G-protein–coupled receptor signaling 3.80 7.95E-10 4.18E-08 Up-regulated group) pathway ACKR2 Atypical chemokine receptor 2 G-protein–coupled receptor signaling 0.42 3.29E-04 4.41E-03 Down-regulated pathway ACSM1 Acyl-CoA synthetase medium-chain family Energy derivation by oxidation of 9.87 1.70E-08 6.52E-07 Up-regulated member 1 organic compounds ACTC1 Actin, ␣, cardiac muscle 1 Negative regulation of apoptotic 0.30 7.96E-06 1.65E-04 Down-regulated process ACTG2 Actin, ␥2, smooth muscle, enteric Blood microparticle 0.29 1.61E-16 2.36E-14 Down-regulated ADAM33 ADAM domain 33 Integral component of membrane 0.23 9.74E-09 3.95E-07 Down-regulated ADAM8 ADAM domain 8 Positive regulation of tumor necrosis 4.69 2.93E-04 4.01E-03 Up-regulated factor (ligand) superfamily member 11 production ADAMTS18 -
The Promise of Whole-Exome Sequencing in Medical Genetics
Journal of Human Genetics (2014) 59, 5–15 & 2014 The Japan Society of Human Genetics All rights reserved 1434-5161/14 www.nature.com/jhg REVIEW The promise of whole-exome sequencing in medical genetics Bahareh Rabbani1, Mustafa Tekin2 and Nejat Mahdieh3 Massively parallel DNA-sequencing systems provide sequence of huge numbers of different DNA strands at once. These technologies are revolutionizing our understanding in medical genetics, accelerating health-improvement projects, and ushering to a fully understood personalized medicine in near future. Whole-exome sequencing (WES) is application of the next-generation technology to determine the variations of all coding regions, or exons, of known genes. WES provides coverage of more than 95% of the exons, which contains 85% of disease-causing mutations in Mendelian disorders and many disease-predisposing SNPs throughout the genome. The role of more than 150 genes has been distinguished by means of WES, and this statistics is quickly growing. In this review, the impacts of WES in medical genetics as well as its consequences leading to improve health care are summarized. Journal of Human Genetics (2014) 59, 5–15; doi:10.1038/jhg.2013.114; published online 7 November 2013 Keywords: cancer; common disease; medical genomics; Mendelian disorder; whole-exome sequencing INTRODUCTION VALUE OF WES IN MEDICINE DNA sequencing is one of the main concerns of medical research Human genome comprises B3 Â 109 bases having coding and nowadays. Union of chain termination sequencing by Sanger et al.1 noncoding sequences. About 3 Â 107 base pairs (1%) (30 Mb) of and the polymerase chain reaction (PCR) by Mullis et al.2 established the genome are the coding sequences.