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      Assessment of the performance of the TGx‐DDI biomarker to detect DNA damage‐inducing agents using quantitative RT‐PCR in TK6 cells

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          Abstract

          Gene expression biomarkers are now available for application in the identification of genotoxic hazards. The TGx‐DDI transcriptomic biomarker can accurately distinguish DNA damage‐inducing (DDI) from non‐DDI exposures based on changes in the expression of 64 biomarker genes. The 64 genes were previously derived from whole transcriptome DNA microarray profiles of 28 reference agents (14 DDI and 14 non‐DDI) after 4 h treatments of TK6 human lymphoblastoid cells. To broaden the applicability of TGx‐DDI, we tested the biomarker using quantitative RT‐PCR (qPCR), which is accessible to most molecular biology laboratories. First, we selectively profiled the expression of the 64 biomarker genes using TaqMan qPCR assays in 96‐well arrays after exposing TK6 cells to the 28 reference agents for 4 h. To evaluate the classification capability of the qPCR profiles, we used the reference qPCR signature to classify 24 external validation chemicals using two different methods—a combination of three statistical analyses and an alternative, the Running Fisher test. The qPCR results for the reference set were comparable to the original microarray biomarker; 27 of the 28 reference agents (96%) were accurately classified. Moreover, the two classification approaches supported the conservation of TGx‐DDI classification capability using qPCR; the combination of the two approaches accurately classified 21 of the 24 external validation chemicals, demonstrating 100% sensitivity, 81% specificity, and 91% balanced accuracy. This study demonstrates that qPCR can be used when applying the TGx‐DDI biomarker and will improve the accessibility of TGx‐DDI for genotoxicity screening. Environ. Mol. Mutagen. 60: 122–133, 2019. © 2018 Her Majesty the Queen in Right of Canada Environmental and Molecular Mutagenesis.

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          Ontology-Based Meta-Analysis of Global Collections of High-Throughput Public Data

          Background The investigation of the interconnections between the molecular and genetic events that govern biological systems is essential if we are to understand the development of disease and design effective novel treatments. Microarray and next-generation sequencing technologies have the potential to provide this information. However, taking full advantage of these approaches requires that biological connections be made across large quantities of highly heterogeneous genomic datasets. Leveraging the increasingly huge quantities of genomic data in the public domain is fast becoming one of the key challenges in the research community today. Methodology/Results We have developed a novel data mining framework that enables researchers to use this growing collection of public high-throughput data to investigate any set of genes or proteins. The connectivity between molecular states across thousands of heterogeneous datasets from microarrays and other genomic platforms is determined through a combination of rank-based enrichment statistics, meta-analyses, and biomedical ontologies. We address data quality concerns through dataset replication and meta-analysis and ensure that the majority of the findings are derived using multiple lines of evidence. As an example of our strategy and the utility of this framework, we apply our data mining approach to explore the biology of brown fat within the context of the thousands of publicly available gene expression datasets. Conclusions Our work presents a practical strategy for organizing, mining, and correlating global collections of large-scale genomic data to explore normal and disease biology. Using a hypothesis-free approach, we demonstrate how a data-driven analysis across very large collections of genomic data can reveal novel discoveries and evidence to support existing hypothesis.
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            Microarrays and toxicology: the advent of toxicogenomics.

            The availability of genome-scale DNA sequence information and reagents has radically altered life-science research. This revolution has led to the development of a new scientific subdiscipline derived from a combination of the fields of toxicology and genomics. This subdiscipline, termed toxicogenomics, is concerned with the identification of potential human and environmental toxicants, and their putative mechanisms of action, through the use of genomics resources. One such resource is DNA microarrays or "chips," which allow the monitoring of the expression levels of thousands of genes simultaneously. Here we propose a general method by which gene expression, as measured by cDNA microarrays, can be used as a highly sensitive and informative marker for toxicity. Our purpose is to acquaint the reader with the development and current state of microarray technology and to present our view of the usefulness of microarrays to the field of toxicology.
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              The Japanese toxicogenomics project: application of toxicogenomics.

              Biotechnology advances have provided novel methods for the risk assessment of chemicals. The application of microarray technologies to toxicology, known as toxicogenomics, is becoming an accepted approach for identifying chemicals with potential safety problems. Gene expression profiling is expected to identify the mechanisms that underlie the potential toxicity of chemicals. This technology has also been applied to identify biomarkers of toxicity to predict potential hazardous chemicals. Ultimately, toxicogenomics is expected to aid in risk assessment. The following discussion explores potential applications and features of the Japanese Toxicogenomics Project.
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                Author and article information

                Contributors
                carole.yauk@canada.ca
                Journal
                Environ Mol Mutagen
                Environ. Mol. Mutagen
                10.1002/(ISSN)1098-2280
                EM
                Environmental and Molecular Mutagenesis
                John Wiley & Sons, Inc. (Hoboken, USA )
                0893-6692
                1098-2280
                29 November 2018
                March 2019
                : 60
                : 2 ( doiID: 10.1002/em.v60.2 )
                : 122-133
                Affiliations
                [ 1 ] Environmental Health Science and Research Bureau Health Canada Ottawa Ontario Canada
                [ 2 ] Department of Biology Carleton University Ottawa Ontario Canada
                [ 3 ] Department of Oncology, Lombardi Comprehensive Cancer Center Georgetown University Medical Center Washington District of Columbia
                [ 4 ] Department of Biochemistry and Molecular and Cellular Biology Georgetown University Medical Center Washington District of Columbia
                [ 5 ] Integrated Systems Toxicology Division NHEERL, US‐EPA Durham North Carolina
                [ 6 ] Takeda Pharmaceuticals USA Inc. Cambridge Massachusetts
                Author notes
                [*] [* ] Correspondence to: Carole L. Yauk, Health Canada, Environmental Health Centre, 50 Colombine Driveway, PL 0803A, Ottawa, ON K1A 0K9, Canada. E‐mail: carole.yauk@ 123456canada.ca
                Author information
                https://orcid.org/0000-0002-6197-2036
                Article
                EM22257
                10.1002/em.22257
                6588084
                30488505
                aae2ba14-b27b-4027-8fb0-1a667c26efc7
                © 2018 Her Majesty the Queen in Right of Canada Environmental and Molecular Mutagenesis.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 24 July 2018
                : 03 October 2018
                : 04 October 2018
                Page count
                Figures: 3, Tables: 4, Pages: 12, Words: 7971
                Funding
                Funded by: Health Canada Genomics Research and Development Initiative
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                em22257
                March 2019
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.6.4 mode:remove_FC converted:21.06.2019

                Molecular biology
                toxicogenomics,genotoxicity,transcriptomic biomarker,gene expression signature

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