1
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Zhang Q, Taniguchi S, So K, Tsuda M, Higuchi Y, Hashida M, Yamashita F. CREB is a potential marker associated with drug-induced liver injury: Identification and validation through transcriptome database analysis. J Toxicol Sci 2022; 47:337-348. [PMID: 35922923 DOI: 10.2131/jts.47.337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Drug-induced liver injury (DILI) is the main cause of failure in drug development and postapproval withdrawal. Although toxicogenomic techniques provide an unprecedented opportunity for mechanistic assessment and biomarker discovery, they are not suitable for the screening of large numbers of exploratory compounds in early drug discovery. Using a comprehensive analysis of toxicogenomics (TGx) data, we aimed to find DILI-relevant transcription factors (TFs) that could be incorporated into a reporter gene assay system. Gene set enrichment analysis (GSEA) of the Open TG-GATEs dataset highlighted 4 DILI-relevant TFs, including CREB, NRF2, ELK-1, and E2F. Using ten drugs with already assigned idiosyncratic toxicity (IDT) risks, reporter gene assays were conducted in HepG2 cells in the presence of the S9 mix. There were weak correlations between NRF2 activity and IDT risk, whereas strong correlations were observed between CREB activity and IDT risk. In addition, CREB activation associated with 3 Withdrawn/Black box Warning drugs was reversed by pretreatment with a PKA inhibitor. Collectively, we suggest that CREB might be a sensitive biomarker for DILI prediction, and its response to stress induced by high-risk drugs might be primarily regulated by the PKA/CREB signaling pathway.
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Affiliation(s)
- Qiyue Zhang
- Department of Drug Delivery Research, Graduate School of Pharmaceutical Sciences, Kyoto University
| | - Shiori Taniguchi
- Department of Drug Delivery Research, Graduate School of Pharmaceutical Sciences, Kyoto University
| | - Kanako So
- Department of Applied Pharmaceutics and Pharmacokinetics, Graduate School of Pharmaceutical Sciences, Kyoto University
| | - Masahiro Tsuda
- Department of Applied Pharmaceutics and Pharmacokinetics, Graduate School of Pharmaceutical Sciences, Kyoto University
| | - Yuriko Higuchi
- Department of Drug Delivery Research, Graduate School of Pharmaceutical Sciences, Kyoto University
| | - Mitsuru Hashida
- Department of Drug Delivery Research, Graduate School of Pharmaceutical Sciences, Kyoto University
| | - Fumiyoshi Yamashita
- Department of Drug Delivery Research, Graduate School of Pharmaceutical Sciences, Kyoto University.,Department of Applied Pharmaceutics and Pharmacokinetics, Graduate School of Pharmaceutical Sciences, Kyoto University
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2
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Abstract
Assessing the drug safety at an early stage of a drug discovery program is a critical issue. With the recent advances in molecular biology and genomic, massive amounts of generated and accumulated data by advanced experimental technologies such as RNA sequencing or proteomics start to be at the disposal of the scientific community. Innovative and adequate bioinformatic methods, tools, and protocols are required to analyze properly these diverse and extensive data sources with the aim to identify key features that are related to toxicity observations. Furthermore, the assessment of drug safety can be performed across multiple scales of complexity from molecular, cellular to phenotypic levels; therefore, the application of network science contributes to a better interpretation of the drug's exposure effect on human health. Here, we review databases containing toxicogenomics and chemical-phenotype information, as well as appropriated bioinformatics approaches that are currently used to analyze such data. Extension to others methods such as dose-responses, time-dependent processes, and text mining is also presented giving an overview of suitable tools available for a best practice of drug safety analysis.
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3
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Liu Y, Jing R, Wen Z, Li M. Narrowing the Gap Between In Vitro and In Vivo Genetic Profiles by Deconvoluting Toxicogenomic Data In Silico. Front Pharmacol 2020; 10:1489. [PMID: 31992983 PMCID: PMC6964707 DOI: 10.3389/fphar.2019.01489] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2019] [Accepted: 11/18/2019] [Indexed: 01/09/2023] Open
Abstract
Toxicogenomics (TGx) is a powerful method to evaluate toxicity and is widely used in both in vivo and in vitro assays. For in vivo TGx, reduction, refinement, and replacement represent the unremitting pursuit of live-animal tests, but in vitro assays, as alternatives, usually demonstrate poor correlation with real in vivo assays. In living subjects, in addition to drug effects, inner-environmental reactions also affect genetic variation, and these two factors are further jointly reflected in gene abundance. Thus, finding a strategy to factorize inner-environmental factor from in vivo assays based on gene expression levels and to further utilize in vitro data to better simulate in vivo data is needed. We proposed a strategy based on post-modified non-negative matrix factorization, which can estimate the gene expression profiles and contents of major factors in samples. The applicability of the strategy was first verified, and the strategy was then utilized to simulate in vivo data by correcting in vitro data. The similarities between real in vivo data and simulated data (single-dose 0.72, repeat-doses 0.75) were higher than those observed when directly comparing real in vivo data with in vitro data (single-dose 0.56, repeat-doses 0.70). Moreover, by keeping environment-related factor, a simulation can always be generated by using in vitro data to provide potential substitutions for in vivo TGx and to reduce the launch of live-animal tests.
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Affiliation(s)
- Yuan Liu
- College of Chemistry, Sichuan University, Chengdu, China
| | - Runyu Jing
- College of Cybersecurity, Sichuan University, Chengdu, China
| | - Zhining Wen
- College of Chemistry, Sichuan University, Chengdu, China
| | - Menglong Li
- College of Chemistry, Sichuan University, Chengdu, China
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4
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Aguayo-Orozco A, Taboureau O, Brunak S. The use of systems biology in chemical risk assessment. CURRENT OPINION IN TOXICOLOGY 2019. [DOI: 10.1016/j.cotox.2019.03.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
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5
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Taškova K, Fontaine JF, Mrowka R, Andrade-Navarro MA. Literature optimized integration of gene expression for organ-specific evaluation of toxicogenomics datasets. PLoS One 2019; 14:e0210467. [PMID: 30640953 PMCID: PMC6331104 DOI: 10.1371/journal.pone.0210467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Accepted: 12/24/2018] [Indexed: 11/30/2022] Open
Abstract
The study of drug toxicity in human organs is complicated by their complex inter-relations and by the obvious difficulty to testing drug effects on biologically relevant material. Animal models and human cell cultures offer alternatives for systematic and large-scale profiling of drug effects on gene expression level, as typically found in the so-called toxicogenomics datasets. However, the complexity of these data, which includes variable drug doses, time points, and experimental setups, makes it difficult to choose and integrate the data, and to evaluate the appropriateness of one or another model system to study drug toxicity (of particular drugs) of particular human organs. Here, we define a protocol to integrate drug-wise rankings of gene expression changes in toxicogenomics data, which we apply to the TG-GATEs dataset, to prioritize genes for association to drug toxicity in liver or kidney. Contrast of the results with sets of known human genes associated to drug toxicity in the literature allows to compare different rank aggregation approaches for the task at hand. Collectively, ranks from multiple models point to genes not previously associated to toxicity, notably, the PCNA clamp associated factor (PCLAF), and genes regulated by the master regulator of the antioxidant response NFE2L2, such as NQO1 and SRXN1. In addition, comparing gene ranks from different models allowed us to evaluate striking differences in terms of toxicity-associated genes between human and rat hepatocytes or between rat liver and rat hepatocytes. We interpret these results to point to the different molecular functions associated to organ toxicity that are best described by each model. We conclude that the expected production of toxicogenomics panels with larger numbers of drugs and models, in combination with the ongoing increase of the experimental literature in organ toxicity, will lead to increasingly better associations of genes for organism toxicity.
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Affiliation(s)
| | | | - Ralf Mrowka
- Experimentelle Nephrologie, Universitätsklinikum Jena, KIM III, Jena, Germany
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6
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Auerbach SS, Paules RS. Genomic dose response: Successes, challenges, and next steps. CURRENT OPINION IN TOXICOLOGY 2018. [DOI: 10.1016/j.cotox.2019.04.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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7
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Liu Z, Delavan B, Roberts R, Tong W. Transcriptional Responses Reveal Similarities Between Preclinical Rat Liver Testing Systems. Front Genet 2018; 9:74. [PMID: 29616076 PMCID: PMC5870427 DOI: 10.3389/fgene.2018.00074] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2017] [Accepted: 02/19/2018] [Indexed: 01/03/2023] Open
Abstract
Toxicogenomics (TGx) is an important tool to gain an enhanced understanding of toxicity at the molecular level. Previously, we developed a pair ranking (PRank) method to assess in vitro to in vivo extrapolation (IVIVE) using toxicogenomic datasets from the Open Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System (TG-GATEs) database. With this method, we investiagted three important questions that were not addressed in our previous study: (1) is a 1-day in vivo short-term assay able to replace the 28-day standard and expensive toxicological assay? (2) are some biological processes more conservative across different preclinical testing systems than others? and (3) do these preclinical testing systems have the similar resolution in differentiating drugs by their therapeutic uses? For question 1, a high similarity was noted (PRank score = 0.90), indicating the potential utility of shorter term in vivo studies to predict outcome in longer term and more expensive in vivo model systems. There was a moderate similarity between rat primary hepatocytes and in vivo repeat-dose studies (PRank score = 0.71) but a low similarity (PRank score = 0.56) between rat primary hepatocytes and in vivo single dose studies. To address question 2, we limited the analysis to gene sets relevant to specific toxicogenomic pathways and we found that pathways such as lipid metabolism were consistently over-represented in all three assay systems. For question 3, all three preclinical assay systems could distinguish compounds from different therapeutic categories. This suggests that any noted differences in assay systems was biological process-dependent and furthermore that all three systems have utility in assessing drug responses within a certain drug class. In conclusion, this comparison of three commonly used rat TGx systems provides useful information in utility and application of TGx assays.
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Affiliation(s)
- Zhichao Liu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, United States
| | - Brian Delavan
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, United States.,Department of Biosciences, University of Arkansas at Little Rock, Little Rock, AR, United States
| | - Ruth Roberts
- ApconiX, Alderley Edge, United Kingdom.,Department of Biosciences, University of Birmingham, Birmingham, United Kingdom
| | - Weida Tong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, United States
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8
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Application of Multiplex Biomarker Approaches to Accelerate Drug Discovery and Development. Methods Mol Biol 2018; 1546:3-17. [PMID: 27896754 DOI: 10.1007/978-1-4939-6730-8_1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/26/2023]
Abstract
Multiplex biomarker tests are becoming an essential part of the drug development process. This chapter explores the role of biomarker-based tests as effective tools in improving preclinical research and clinical development, and the challenges that this presents. The potential of incorporating biomarkers in the clinical pipeline to improve decision making, accelerate drug development, improve translation, and reduce development costs is discussed. This chapter also discusses the latest biomarker technologies in use to make this possible and details the next steps that must undertaken to keep driving this process forwards.
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9
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Systems Microscopy Approaches in Unraveling and Predicting Drug-Induced Liver Injury (DILI). METHODS IN PHARMACOLOGY AND TOXICOLOGY 2018. [DOI: 10.1007/978-1-4939-7677-5_29] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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10
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Integration of the TGx-28.65 genomic biomarker with the flow cytometry micronucleus test to assess the genotoxicity of disperse orange and 1,2,4-benzenetriol in human TK6 cells. Mutat Res 2017; 806:51-62. [PMID: 29017062 DOI: 10.1016/j.mrfmmm.2017.09.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2017] [Revised: 07/21/2017] [Accepted: 09/10/2017] [Indexed: 12/13/2022]
Abstract
In vitro gene expression signatures to predict toxicological responses can provide mechanistic context for regulatory testing. We previously developed the TGx-28.65 genomic biomarker from a database of gene expression profiles derived from human TK6 cells exposed to 28 well-known compounds. The biomarker comprises 65 genes that can classify chemicals as DNA damaging or non-DNA damaging. In this study, we applied the TGx-28.65 genomic biomarker in parallel with the in vitro micronucleus (MN) assay to determine if two chemicals of regulatory interest at Health Canada, disperse orange (DO: the orange azo dye 3-[[4-[(4-Nitrophenyl)azo]phenyl] benzylamino]propanenitrile) and 1,2,4-benzenetriol (BT: a metabolite of benzene) are genotoxic or non-genotoxic. Both chemicals caused dose-dependent declines in relative survival and increases in apoptosis. A strong significant increase in MN induction was observed for all concentrations of BT; the top two concentrations of DO also caused a statistically significant increase in MN, but these increases were <2-fold above controls. TGx-28.65 analysis classified BT as genotoxic at all three concentrations and DO as genotoxic at the mid and high concentrations. Thus, although DO only caused a small increase in MN, this response was sufficient to induce a cellular DNA damage response. Benchmark dose modeling confirmed that BT is much more potent than DO. The results strongly suggest that follow-up work is required to assess whether DO and BT are also genotoxic in vivo. This is particularly important for DO, which may require metabolic activation by bacterial gut flora to fully induce its genotoxic potential. Our previously published data and this proof of concept study suggest that the TGx-28.65 genomic biomarker has the potential to add significant value to existing approaches used to assess genotoxicity.
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11
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Liu L, Tsompana M, Wang Y, Wu D, Zhu L, Zhu R. Connection Map for Compounds (CMC): A Server for Combinatorial Drug Toxicity and Efficacy Analysis. J Chem Inf Model 2016; 56:1615-21. [PMID: 27508329 DOI: 10.1021/acs.jcim.6b00397] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Drug discovery and development is a costly and time-consuming process with a high risk for failure resulting primarily from a drug's associated clinical safety and efficacy potential. Identifying and eliminating inapt candidate drugs as early as possible is an effective way for reducing unnecessary costs, but limited analytical tools are currently available for this purpose. Recent growth in the area of toxicogenomics and pharmacogenomics has provided with a vast amount of drug expression microarray data. Web servers such as CMap and LTMap have used this information to evaluate drug toxicity and mechanisms of action independently; however, their wider applicability has been limited by the lack of a combinatorial drug-safety type of analysis. Using available genome-wide drug transcriptional expression profiles, we developed the first web server for combinatorial evaluation of toxicity and efficacy of candidate drugs named "Connection Map for Compounds" (CMC). Using CMC, researchers can initially compare their query drug gene signatures with prebuilt gene profiles generated from two large-scale toxicogenomics databases, and subsequently perform a drug efficacy analysis for identification of known mechanisms of drug action or generation of new predictions. CMC provides a novel approach for drug repositioning and early evaluation in drug discovery with its unique combination of toxicity and efficacy analyses, expansibility of data and algorithms, and customization of reference gene profiles. CMC can be freely accessed at http://cadd.tongji.edu.cn/webserver/CMCbp.jsp .
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Affiliation(s)
- Lei Liu
- Department of Bioinformatics, School of Life Sciences and Technology, Tongji University , Shanghai 200092, People's Repubic of China
| | - Maria Tsompana
- Center of Excellence in Bioinformatics and Life Sciences, the State University of New York at Buffalo , Buffalo, New York 14203, United States
| | - Yong Wang
- Basic Medical College, Beijing University of Chinese Medicine , Beijing 100029, People's Republic of China
| | - Dingfeng Wu
- Department of Bioinformatics, School of Life Sciences and Technology, Tongji University , Shanghai 200092, People's Repubic of China
| | - Lixin Zhu
- Digestive Diseases and Nutrition Center, Department of Pediatrics, The State University of New York at Buffalo , Buffalo, New York 14260, United States.,Genome, Environment, and Microbiome Community of Excellence, The State University of New York at Buffalo , Buffalo, New York 14214, United States.,Institute of Digestive Diseases, Longhua Hospital, Shanghai University of Traditional Chinese Medicine , Shanghai 200032, People's Republic of China
| | - Ruixin Zhu
- Department of Bioinformatics, School of Life Sciences and Technology, Tongji University , Shanghai 200092, People's Repubic of China
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12
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El-Hachem N, Grossmann P, Blanchet-Cohen A, Bateman AR, Bouchard N, Archambault J, Aerts HJ, Haibe-Kains B. Characterization of Conserved Toxicogenomic Responses in Chemically Exposed Hepatocytes across Species and Platforms. ENVIRONMENTAL HEALTH PERSPECTIVES 2016; 124:313-20. [PMID: 26173225 PMCID: PMC4786983 DOI: 10.1289/ehp.1409157] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2014] [Accepted: 07/09/2015] [Indexed: 05/03/2023]
Abstract
BACKGROUND Genome-wide expression profiling is increasingly being used to identify transcriptional changes induced by drugs and environmental stressors. In this context, the Toxicogenomics Project-Genomics Assisted Toxicity Evaluation system (TG-GATEs) project generated transcriptional profiles from rat liver samples and human/rat cultured primary hepatocytes exposed to more than 100 different chemicals. OBJECTIVES To assess the capacity of the cell culture models to recapitulate pathways induced by chemicals in vivo, we leveraged the TG-GATEs data set to compare the early transcriptional responses observed in the liver of rats treated with a large set of chemicals with those of cultured rat and human primary hepatocytes challenged with the same compounds in vitro. METHODS We developed a new pathway-based computational pipeline that efficiently combines gene set enrichment analysis (GSEA) using pathways from the Reactome database with biclustering to identify common modules of pathways that are modulated by several chemicals in vivo and in vitro across species. RESULTS We found that some chemicals induced conserved patterns of early transcriptional responses in in vitro and in vivo settings, and across human and rat genomes. These responses involved pathways of cell survival, inflammation, xenobiotic metabolism, oxidative stress, and apoptosis. Moreover, our results support the transforming growth factor beta receptor (TGF-βR) signaling pathway as a candidate biomarker associated with exposure to environmental toxicants in primary human hepatocytes. CONCLUSIONS Our integrative analysis of toxicogenomics data provides a comprehensive overview of biochemical perturbations affected by a large panel of chemicals. Furthermore, we show that the early toxicological response occurring in animals is recapitulated in human and rat primary hepatocyte cultures at the molecular level, indicating that these models reproduce key pathways in response to chemical stress. These findings expand our understanding and interpretation of toxicogenomics data from human hepatocytes exposed to environmental toxicants.
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Affiliation(s)
- Nehme El-Hachem
- Integrative systems biology, Institut de Recherches Cliniques de Montréal, Montreal, Quebec, Canada
- Department of Medicine, University of Montreal, Montréal, Quebec, Canada
| | - Patrick Grossmann
- Department of Biostatistics & Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | | | - Alain R. Bateman
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
| | - Nicolas Bouchard
- Department of Medicine, University of Montreal, Montréal, Quebec, Canada
- Molecular Biology of Neural Development, Institut de Recherches Cliniques de Montréal, Montreal, Canada
| | - Jacques Archambault
- Laboratory of Molecular Virology, Institut de Recherches Cliniques de Montréal, Montreal, Quebec, Canada
| | - Hugo J.W.L. Aerts
- Department of Biostatistics & Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
- Department of Radiation Oncology, Dana-Farber Cancer Institute, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Department of Radiology, Dana-Farber Cancer Institute, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Address correspondence to B. Haibe-Kains, Princess Margaret Cancer Centre, University Health Network, 101 College St., Toronto, ON, M5G 1L7, Canada. Telephone: 1 (416) 581-7628. E-mail: , or to H.J.W.L. Aerts, Department of Radiology, Dana-Farber Cancer Institute, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115 USA. E-mail:
| | - Benjamin Haibe-Kains
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
- Medical Biophysics Department, University of Toronto, Toronto, Ontario, Canada
- Address correspondence to B. Haibe-Kains, Princess Margaret Cancer Centre, University Health Network, 101 College St., Toronto, ON, M5G 1L7, Canada. Telephone: 1 (416) 581-7628. E-mail: , or to H.J.W.L. Aerts, Department of Radiology, Dana-Farber Cancer Institute, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115 USA. E-mail:
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13
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Ball N, Cronin MTD, Shen J, Blackburn K, Booth ED, Bouhifd M, Donley E, Egnash L, Hastings C, Juberg DR, Kleensang A, Kleinstreuer N, Kroese ED, Lee AC, Luechtefeld T, Maertens A, Marty S, Naciff JM, Palmer J, Pamies D, Penman M, Richarz AN, Russo DP, Stuard SB, Patlewicz G, van Ravenzwaay B, Wu S, Zhu H, Hartung T. Toward Good Read-Across Practice (GRAP) guidance. ALTEX-ALTERNATIVES TO ANIMAL EXPERIMENTATION 2016; 33:149-66. [PMID: 26863606 PMCID: PMC5581000 DOI: 10.14573/altex.1601251] [Citation(s) in RCA: 116] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/21/2016] [Accepted: 02/11/2016] [Indexed: 12/04/2022]
Abstract
Grouping of substances and utilizing read-across of data within those groups represents an important data gap filling technique for chemical safety assessments. Categories/analogue groups are typically developed based on structural similarity and, increasingly often, also on mechanistic (biological) similarity. While read-across can play a key role in complying with legislation such as the European REACH regulation, the lack of consensus regarding the extent and type of evidence necessary to support it often hampers its successful application and acceptance by regulatory authorities. Despite a potentially broad user community, expertise is still concentrated across a handful of organizations and individuals. In order to facilitate the effective use of read-across, this document presents the state of the art, summarizes insights learned from reviewing ECHA published decisions regarding the relative successes/pitfalls surrounding read-across under REACH, and compiles the relevant activities and guidance documents. Special emphasis is given to the available existing tools and approaches, an analysis of ECHA's published final decisions associated with all levels of compliance checks and testing proposals, the consideration and expression of uncertainty, the use of biological support data, and the impact of the ECHA Read-Across Assessment Framework (RAAF) published in 2015.
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Affiliation(s)
| | - Mark T D Cronin
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, UK
| | - Jie Shen
- Research Institute for Fragrance Materials, Inc. Woodcliff Lake, NJ, USA
| | | | - Ewan D Booth
- Syngenta Ltd, Jealott's Hill International Research Centre, Bracknell, Berkshire, UK
| | - Mounir Bouhifd
- Johns Hopkins Bloomberg School of Public Health, Center for Alternatives to Animal Testing (CAAT), Baltimore, MD, USA
| | | | - Laura Egnash
- Stemina Biomarker Discovery Inc., Madison, WI, USA
| | - Charles Hastings
- BASF SE, Ludwigshafen am Rhein, Germany, and Research Triangle Park, NC, USA
| | | | - Andre Kleensang
- Johns Hopkins Bloomberg School of Public Health, Center for Alternatives to Animal Testing (CAAT), Baltimore, MD, USA
| | - Nicole Kleinstreuer
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - E Dinant Kroese
- Risk Analysis for Products in Development, TNO Zeist, The Netherlands
| | - Adam C Lee
- DuPont Haskell Global Centers for Health and Environmental Sciences, Newark, DE, USA
| | - Thomas Luechtefeld
- Johns Hopkins Bloomberg School of Public Health, Center for Alternatives to Animal Testing (CAAT), Baltimore, MD, USA
| | - Alexandra Maertens
- Johns Hopkins Bloomberg School of Public Health, Center for Alternatives to Animal Testing (CAAT), Baltimore, MD, USA
| | - Sue Marty
- The Dow Chemical Company, Midland, MI, USA
| | | | | | - David Pamies
- Johns Hopkins Bloomberg School of Public Health, Center for Alternatives to Animal Testing (CAAT), Baltimore, MD, USA
| | | | - Andrea-Nicole Richarz
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, UK
| | - Daniel P Russo
- Department of Chemistry and Center for Computational and Integrative Biology, Rutgers University, Camden, NJ, USA
| | | | - Grace Patlewicz
- US EPA/ORD, National Center for Computational Toxicology, Research Triangle Park, NC, USA
| | | | - Shengde Wu
- The Procter and Gamble Co., Cincinatti, OH, USA
| | - Hao Zhu
- Department of Chemistry and Center for Computational and Integrative Biology, Rutgers University, Camden, NJ, USA
| | - Thomas Hartung
- Johns Hopkins Bloomberg School of Public Health, Center for Alternatives to Animal Testing (CAAT), Baltimore, MD, USA.,University of Konstanz, CAAT-Europe, Konstanz, Germany
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14
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Zhu H, Bouhifd M, Kleinstreuer N, Kroese ED, Liu Z, Luechtefeld T, Pamies D, Shen J, Strauss V, Wu S, Hartung T. Supporting read-across using biological data. ALTEX 2016; 33:167-82. [PMID: 26863516 PMCID: PMC4834201 DOI: 10.14573/altex.1601252] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/25/2016] [Accepted: 02/09/2016] [Indexed: 01/08/2023]
Abstract
Read-across, i.e. filling toxicological data gaps by relating to similar chemicals, for which test data are available, is usually done based on chemical similarity. Besides structure and physico-chemical properties, however, biological similarity based on biological data adds extra strength to this process. In the context of developing Good Read-Across Practice guidance, a number of case studies were evaluated to demonstrate the use of biological data to enrich read-across. In the simplest case, chemically similar substances also show similar test results in relevant in vitro assays. This is a well-established method for the read-across of e.g. genotoxicity assays. Larger datasets of biological and toxicological properties of hundreds and thousands of substances become increasingly available enabling big data approaches in read-across studies. Several case studies using various big data sources are described in this paper. An example is given for the US EPA's ToxCast dataset allowing read-across for high quality uterotrophic assays for estrogenic endocrine disruption. Similarly, an example for REACH registration data enhancing read-across for acute toxicity studies is given. A different approach is taken using omics data to establish biological similarity: Examples are given for stem cell models in vitro and short-term repeated dose studies in rats in vivo to support read-across and category formation. These preliminary biological data-driven read-across studies highlight the road to the new generation of read-across approaches that can be applied in chemical safety assessment.
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Affiliation(s)
- Hao Zhu
- Department of Chemistry, Rutgers University, Camden, NJ, USA; Center for Computational and Integrative Biology, Rutgers University, Camden, NJ, USA
| | - Mounir Bouhifd
- Johns Hopkins Bloomberg School of Public Health, Center for Alternatives to Animal Testing (CAAT), Baltimore, MD, USA
| | - Nicole Kleinstreuer
- National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - E. Dinant Kroese
- Risk Analysis for Products in Development, TNO Zeist, The Netherlands
| | | | - Thomas Luechtefeld
- Johns Hopkins Bloomberg School of Public Health, Center for Alternatives to Animal Testing (CAAT), Baltimore, MD, USA
| | - David Pamies
- Johns Hopkins Bloomberg School of Public Health, Center for Alternatives to Animal Testing (CAAT), Baltimore, MD, USA
| | - Jie Shen
- Research Institute for Fragrance Materials, Inc. Woodcliff Lake, New Jersey, USA
| | - Volker Strauss
- BASF Aktiengesellschaft, Experimental Toxicology and Ecology, Ludwigshafen, Germany
| | | | - Thomas Hartung
- Johns Hopkins Bloomberg School of Public Health, Center for Alternatives to Animal Testing (CAAT), Baltimore, MD, USA
- University of Konstanz, CAAT-Europe, Konstanz, Germany
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15
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Zaitsu K, Hayashi Y, Kusano M, Tsuchihashi H, Ishii A. Application of metabolomics to toxicology of drugs of abuse: A mini review of metabolomics approach to acute and chronic toxicity studies. Drug Metab Pharmacokinet 2015; 31:21-26. [PMID: 26613805 DOI: 10.1016/j.dmpk.2015.10.002] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2015] [Revised: 10/20/2015] [Accepted: 10/23/2015] [Indexed: 12/24/2022]
Abstract
Metabolomics has been widely applied to toxicological fields, especially to elucidate the mechanism of action of toxicity. In this review, metabolomics application with focus on the studies of chronic and acute toxicities of drugs of abuse like stimulants, opioids and the recently-distributed designer drugs will be presented in addition to an outline of basic analytical techniques used in metabolomics. Limitation of metabolomics studies and future perspectives will be also provided.
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Affiliation(s)
- Kei Zaitsu
- Department of Legal Medicine & Bioethics, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan; Institute for Advanced Research, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan.
| | - Yumi Hayashi
- Institute for Advanced Research, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan; Department of Radiological and Medical Laboratory Sciences, Nagoya University Graduate School of Medicine, 1-1-20 Daiko-Minami, Higashi-ku, Nagoya 461-8673, Japan.
| | - Maiko Kusano
- Department of Legal Medicine & Bioethics, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan.
| | - Hitoshi Tsuchihashi
- Department of Legal Medicine & Bioethics, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan.
| | - Akira Ishii
- Department of Legal Medicine & Bioethics, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan.
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16
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Otava M, Shkedy Z, Talloen W, Verheyen GR, Kasim A. Identification of in vitro and in vivo disconnects using transcriptomic data. BMC Genomics 2015; 16:615. [PMID: 26282683 PMCID: PMC4539666 DOI: 10.1186/s12864-015-1726-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2015] [Accepted: 06/26/2015] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Integrating transcriptomic experiments within drug development is increasingly advocated for the early detection of toxicity. This is partly to reduce costs related to drug failures in the late, and expensive phases of clinical trials. Such an approach has proven useful both in the study of toxicology and carcinogenicity. However, general lack of translation of in vitro findings to in vivo systems remains one of the bottle necks in drug development. This paper proposes a method for identifying disconnected genes between in vitro and in vivo toxicogenomic rat experiments. The analytical framework is based on the joint modeling of dose-dependent in vitro and in vivo data using a fractional polynomial framework and biclustering algorithm. RESULTS Most disconnected genes identified belonged to known pathways, such as drug metabolism and oxidative stress due to reactive metabolites, bilirubin increase, glutathion depletion and phospholipidosis. We also identified compounds that were likely to induce disconnect in gene expression between in vitro and in vivo toxicogenomic rat experiments. These compounds include: sulindac and diclofenac (both linked to liver damage), naphtyl isothiocyanate (linked to hepatoxocity), indomethacin and naproxen (linked to gastrointestinal problem and damage of intestines). CONCLUSION The results confirmed that there are important discrepancies between in vitro and in vivo toxicogenomic experiments. However, the contribution of this paper is to provide a tool to identify genes that are disconnected between the two systems. Pathway analysis of disconnected genes may improve our understanding of uncertainties in the mechanism of actions of drug candidates in humans, especially concerning the early detection of toxicity.
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Affiliation(s)
- Martin Otava
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Martelarenlaan 32, Hasselt, 3500, Belgium.
| | - Ziv Shkedy
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Martelarenlaan 32, Hasselt, 3500, Belgium.
| | - Willem Talloen
- Janssen, Pharmaceutical companies of Johnson & Johnson, Turnhoutseweg 30, Beerse, 2340, Belgium.
| | | | - Adetayo Kasim
- Wolfson Research Institute for Health and Wellbeing, Durham University, University Boulevard, TS17 6BH Thornaby, Stockton-on-Tees, UK.
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17
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Jiang J, Wolters JEJ, van Breda SG, Kleinjans JC, de Kok TM. Development of novel tools for the in vitro investigation of drug-induced liver injury. Expert Opin Drug Metab Toxicol 2015; 11:1523-37. [PMID: 26155718 DOI: 10.1517/17425255.2015.1065814] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
INTRODUCTION Due to its complex mechanisms and unpredictable occurrence, drug-induced liver injury (DILI) complicates drug identification and classification. Since species-specific differences in metabolism and pharmacokinetics exist, data obtained from animal studies may not be sufficient to predict DILI in humans. AREAS COVERED Over the last few decades, numerous in vitro models have been developed to replace animal testing. The advantages and disadvantages of commonly used liver-derived in vitro models (e.g., cell lines, hepatocyte models, liver slices, three-dimensional (3D) hepatospheres, etc.) are discussed. Toxicogenomics-based methodologies (genomics, epigenomics, transcriptomics, proteomics and metabolomics) and next-generation sequencing have also been used to enhance the reliability of DILI prediction. This review presents an overview of the currently used alternative toxicological models and of the most advanced approaches in the field of DILI research. EXPERT OPINION It seems unlikely that a single in vitro system will be able to mimic the complex interactions in the human liver. Three-dimensional multicellular systems may bridge the gap between conventional 2D models and in vivo clinical studies in humans and provide a reliable basis for hepatic toxicity assay development. Next-generation sequencing technologies, in comparison to microarray-based technologies, may overcome the current limitations and are promising for the development of predictive models in the near future.
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Affiliation(s)
- Jian Jiang
- a 1 Maastricht University, GROW School for Oncology and Developmental Biology, Department of Toxicogenomics , Maastricht, The Netherlands +31 43 3881090 ; +31 43 3884146 ;
| | - Jarno E J Wolters
- b 2 Maastricht University, GROW School for Oncology and Developmental Biology, Department of Toxicogenomics , Maastricht, The Netherlands
| | - Simone G van Breda
- b 2 Maastricht University, GROW School for Oncology and Developmental Biology, Department of Toxicogenomics , Maastricht, The Netherlands
| | - Jos C Kleinjans
- b 2 Maastricht University, GROW School for Oncology and Developmental Biology, Department of Toxicogenomics , Maastricht, The Netherlands
| | - Theo M de Kok
- b 2 Maastricht University, GROW School for Oncology and Developmental Biology, Department of Toxicogenomics , Maastricht, The Netherlands
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18
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Lin C, Ballinger KR, Khetani SR. The application of engineered liver tissues for novel drug discovery. Expert Opin Drug Discov 2015; 10:519-40. [PMID: 25840592 DOI: 10.1517/17460441.2015.1032241] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
INTRODUCTION Drug-induced liver injury remains a major cause of drug attrition. Furthermore, novel drugs are being developed for treating liver diseases. However, differences between animals and humans in liver pathways necessitate the use of human-relevant liver models to complement live animal testing during preclinical drug development. Microfabrication tools and synthetic biomaterials now allow for the creation of tissue subunits that display more physiologically relevant and long-term liver functions than possible with declining monolayers. AREAS COVERED The authors discuss acellular enzyme platforms, two-dimensional micropatterned co-cultures, three-dimensional spheroidal cultures, microfluidic perfusion, liver slices and humanized rodent models. They also present the use of cell lines, primary liver cells and induced pluripotent stem cell-derived human hepatocyte-like cells in the creation of cell-based models and discuss in silico approaches that allow integration and modeling of the datasets from these models. Finally, the authors describe the application of liver models for the discovery of novel therapeutics for liver diseases. EXPERT OPINION Engineered liver models with varying levels of in vivo-like complexities provide investigators with the opportunity to develop assays with sufficient complexity and required throughput. Control over cell-cell interactions and co-culture with stromal cells in both two dimension and three dimension are critical for enabling stable liver models. The validation of liver models with diverse sets of compounds for different applications, coupled with an analysis of cost:benefit ratio, is important for model adoption for routine screening. Ultimately, engineered liver models could significantly reduce drug development costs and enable the development of more efficacious and safer therapeutics for liver diseases.
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Affiliation(s)
- Christine Lin
- Colorado State University, School of Biomedical Engineering , 200 W. Lake St, 1301 Campus Delivery, Fort Collins, CO 80523-1374 , USA
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19
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Khetani SR, Berger DR, Ballinger KR, Davidson MD, Lin C, Ware BR. Microengineered liver tissues for drug testing. ACTA ACUST UNITED AC 2015; 20:216-50. [PMID: 25617027 DOI: 10.1177/2211068214566939] [Citation(s) in RCA: 86] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2014] [Indexed: 01/09/2023]
Abstract
Drug-induced liver injury (DILI) is a leading cause of drug attrition. Significant and well-documented differences between animals and humans in liver pathways now necessitate the use of human-relevant in vitro liver models for testing new chemical entities during preclinical drug development. Consequently, several human liver models with various levels of in vivo-like complexity have been developed for assessment of drug metabolism, toxicity, and efficacy on liver diseases. Recent trends leverage engineering tools, such as those adapted from the semiconductor industry, to enable precise control over the microenvironment of liver cells and to allow for miniaturization into formats amenable for higher throughput drug screening. Integration of liver models into organs-on-a-chip devices, permitting crosstalk between tissue types, is actively being pursued to obtain a systems-level understanding of drug effects. Here, we review the major trends, challenges, and opportunities associated with development and implementation of engineered liver models created from primary cells, cell lines, and stem cell-derived hepatocyte-like cells. We also present key applications where such models are currently making an impact and highlight areas for improvement. In the future, engineered liver models will prove useful for selecting drugs that are efficacious, safer, and, in some cases, personalized for specific patient populations.
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Affiliation(s)
- Salman R Khetani
- Department of Mechanical Engineering, Colorado State University, Fort Collins, CO, USA School of Biomedical Engineering, Colorado State University, Fort Collins, CO, USA
| | - Dustin R Berger
- School of Biomedical Engineering, Colorado State University, Fort Collins, CO, USA
| | - Kimberly R Ballinger
- Department of Mechanical Engineering, Colorado State University, Fort Collins, CO, USA
| | - Matthew D Davidson
- School of Biomedical Engineering, Colorado State University, Fort Collins, CO, USA
| | - Christine Lin
- School of Biomedical Engineering, Colorado State University, Fort Collins, CO, USA
| | - Brenton R Ware
- School of Biomedical Engineering, Colorado State University, Fort Collins, CO, USA
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20
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Adler M, Leich E, Ellinger-Ziegelbauer H, Hewitt P, Dekant W, Rosenwald A, Mally A. Application of RNA interference to improve mechanistic understanding of omics responses to a hepatotoxic drug in primary rat hepatocytes. Toxicology 2014; 326:86-95. [DOI: 10.1016/j.tox.2014.10.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2014] [Revised: 09/26/2014] [Accepted: 10/15/2014] [Indexed: 10/24/2022]
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21
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Titz B, Elamin A, Martin F, Schneider T, Dijon S, Ivanov NV, Hoeng J, Peitsch MC. Proteomics for systems toxicology. Comput Struct Biotechnol J 2014; 11:73-90. [PMID: 25379146 PMCID: PMC4212285 DOI: 10.1016/j.csbj.2014.08.004] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Current toxicology studies frequently lack measurements at molecular resolution to enable a more mechanism-based and predictive toxicological assessment. Recently, a systems toxicology assessment framework has been proposed, which combines conventional toxicological assessment strategies with system-wide measurement methods and computational analysis approaches from the field of systems biology. Proteomic measurements are an integral component of this integrative strategy because protein alterations closely mirror biological effects, such as biological stress responses or global tissue alterations. Here, we provide an overview of the technical foundations and highlight select applications of proteomics for systems toxicology studies. With a focus on mass spectrometry-based proteomics, we summarize the experimental methods for quantitative proteomics and describe the computational approaches used to derive biological/mechanistic insights from these datasets. To illustrate how proteomics has been successfully employed to address mechanistic questions in toxicology, we summarized several case studies. Overall, we provide the technical and conceptual foundation for the integration of proteomic measurements in a more comprehensive systems toxicology assessment framework. We conclude that, owing to the critical importance of protein-level measurements and recent technological advances, proteomics will be an integral part of integrative systems toxicology approaches in the future.
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22
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MS-based metabolomics facilitates the discovery of in vivo functional small molecules with a diversity of biological contexts. Future Med Chem 2014; 5:1953-65. [PMID: 24175746 DOI: 10.4155/fmc.13.148] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
In vivo small molecules as necessary intermediates are involved in numerous critical metabolic pathways and biological processes associated with many essential biological functions and events. There is growing evidence that MS-based metabolomics is emerging as a powerful tool to facilitate the discovery of functional small molecules that can better our understanding of development, infection, nutrition, disease, toxicity, drug therapeutics, gene modifications and host-pathogen interaction from metabolic perspectives. However, further progress must still be made in MS-based metabolomics because of the shortcomings in the current technologies and knowledge. This technique-driven review aims to explore the discovery of in vivo functional small molecules facilitated by MS-based metabolomics and to highlight the analytic capabilities and promising applications of this discovery strategy. Moreover, the biological significance of the discovery of in vivo functional small molecules with different biological contexts is also interrogated at a metabolic perspective.
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23
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Bale SS, Vernetti L, Senutovitch N, Jindal R, Hegde M, Gough A, McCarty WJ, Bakan A, Bhushan A, Shun TY, Golberg I, DeBiasio R, Usta BO, Taylor DL, Yarmush ML. In vitro platforms for evaluating liver toxicity. Exp Biol Med (Maywood) 2014; 239:1180-1191. [PMID: 24764241 DOI: 10.1177/1535370214531872] [Citation(s) in RCA: 125] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
The liver is a heterogeneous organ with many vital functions, including metabolism of pharmaceutical drugs and is highly susceptible to injury from these substances. The etiology of drug-induced liver disease is still debated although generally regarded as a continuum between an activated immune response and hepatocyte metabolic dysfunction, most often resulting from an intermediate reactive metabolite. This debate stems from the fact that current animal and in vitro models provide limited physiologically relevant information, and their shortcomings have resulted in "silent" hepatotoxic drugs being introduced into clinical trials, garnering huge financial losses for drug companies through withdrawals and late stage clinical failures. As we advance our understanding into the molecular processes leading to liver injury, it is increasingly clear that (a) the pathologic lesion is not only due to liver parenchyma but is also due to the interactions between the hepatocytes and the resident liver immune cells, stellate cells, and endothelial cells; and (b) animal models do not reflect the human cell interactions. Therefore, a predictive human, in vitro model must address the interactions between the major human liver cell types and measure key determinants of injury such as the dosage and metabolism of the drug, the stress response, cholestatic effect, and the immune and fibrotic response. In this mini-review, we first discuss the current state of macro-scale in vitro liver culture systems with examples that have been commercialized. We then introduce the paradigm of microfluidic culture systems that aim to mimic the liver with physiologically relevant dimensions, cellular structure, perfusion, and mass transport by taking advantage of micro and nanofabrication technologies. We review the most prominent liver-on-a-chip platforms in terms of their physiological relevance and drug response. We conclude with a commentary on other critical advances such as the deployment of fluorescence-based biosensors to identify relevant toxicity pathways, as well as computational models to create a predictive tool.
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Affiliation(s)
- Shyam Sundhar Bale
- Center for Engineering in Medicine (CEM) at Massachusetts General Hospital, Harvard Medical School, Shriners Hospital for Children, Boston MA 02114
| | - Lawrence Vernetti
- University of Pittsburgh Drug Discovery Institute, Pittsburgh PA 15260.,University of Pittsburgh Department of Computational and Systems Biology, Pittsburgh PA 15260
| | - Nina Senutovitch
- University of Pittsburgh Drug Discovery Institute, Pittsburgh PA 15260.,University of Pittsburgh Department of Computational and Systems Biology, Pittsburgh PA 15260
| | - Rohit Jindal
- Center for Engineering in Medicine (CEM) at Massachusetts General Hospital, Harvard Medical School, Shriners Hospital for Children, Boston MA 02114
| | - Manjunath Hegde
- Center for Engineering in Medicine (CEM) at Massachusetts General Hospital, Harvard Medical School, Shriners Hospital for Children, Boston MA 02114
| | - Albert Gough
- University of Pittsburgh Drug Discovery Institute, Pittsburgh PA 15260.,University of Pittsburgh Department of Computational and Systems Biology, Pittsburgh PA 15260
| | - William J McCarty
- Center for Engineering in Medicine (CEM) at Massachusetts General Hospital, Harvard Medical School, Shriners Hospital for Children, Boston MA 02114
| | - Ahmet Bakan
- University of Pittsburgh Department of Computational and Systems Biology, Pittsburgh PA 15260
| | - Abhinav Bhushan
- Center for Engineering in Medicine (CEM) at Massachusetts General Hospital, Harvard Medical School, Shriners Hospital for Children, Boston MA 02114
| | - Tong Ying Shun
- University of Pittsburgh Drug Discovery Institute, Pittsburgh PA 15260
| | - Inna Golberg
- Center for Engineering in Medicine (CEM) at Massachusetts General Hospital, Harvard Medical School, Shriners Hospital for Children, Boston MA 02114
| | - Richard DeBiasio
- University of Pittsburgh Drug Discovery Institute, Pittsburgh PA 15260
| | - Berk Osman Usta
- Center for Engineering in Medicine (CEM) at Massachusetts General Hospital, Harvard Medical School, Shriners Hospital for Children, Boston MA 02114
| | - D Lansing Taylor
- University of Pittsburgh Drug Discovery Institute, Pittsburgh PA 15260.,University of Pittsburgh Department of Computational and Systems Biology, Pittsburgh PA 15260
| | - Martin L Yarmush
- Center for Engineering in Medicine (CEM) at Massachusetts General Hospital, Harvard Medical School, Shriners Hospital for Children, Boston MA 02114
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24
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Hebels DGA, Jetten MJA, Aerts HJW, Herwig R, Theunissen DHJ, Gaj S, van Delft JH, Kleinjans JCS. Evaluation of database-derived pathway development for enabling biomarker discovery for hepatotoxicity. Biomark Med 2014; 8:185-200. [DOI: 10.2217/bmm.13.154] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
Current testing models for predicting drug-induced liver injury are inadequate, as they basically under-report human health risks. We present here an approach towards developing pathways based on hepatotoxicity-associated gene groups derived from two types of publicly accessible hepatotoxicity databases, in order to develop drug-induced liver injury biomarker profiles. One human liver ‘omics-based and four text-mining-based databases were explored for hepatotoxicity-associated gene lists. Over-representation analysis of these gene lists with a hepatotoxicant-exposed primary human hepatocytes data set showed that human liver ‘omics gene lists performed better than text-mining gene lists and the results of the latter differed strongly between databases. However, both types of databases contained gene lists demonstrating biomarker potential. Visualizing those in pathway format may aid in interpreting the biomolecular background. We conclude that exploiting existing and openly accessible databases in a dedicated manner seems promising in providing venues for translational research in toxicology and biomarker development.
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Affiliation(s)
- Dennie GA Hebels
- Department of Toxicogenomics, Maastricht University, Universiteitssingel 50, 6229 ER Maastricht, The Netherlands
| | - Marlon JA Jetten
- Department of Toxicogenomics, Maastricht University, Universiteitssingel 50, 6229 ER Maastricht, The Netherlands
| | - Hugo JW Aerts
- Department or Biostatistics & Computational Biology, Dana–Farber Cancer Institute, Harvard School of Public Health, 44 Binney Street, Boston, MA 02115, USA
| | - Ralf Herwig
- Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, 14195 Berlin, Germany
| | - Daniël HJ Theunissen
- Department of Toxicogenomics, Maastricht University, Universiteitssingel 50, 6229 ER Maastricht, The Netherlands
| | - Stan Gaj
- Department of Toxicogenomics, Maastricht University, Universiteitssingel 50, 6229 ER Maastricht, The Netherlands
| | - Joost H van Delft
- Department of Toxicogenomics, Maastricht University, Universiteitssingel 50, 6229 ER Maastricht, The Netherlands
| | - Jos CS Kleinjans
- Department of Toxicogenomics, Maastricht University, Universiteitssingel 50, 6229 ER Maastricht, The Netherlands
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25
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Ahuja V, Sharma S. Drug safety testing paradigm, current progress and future challenges: an overview. J Appl Toxicol 2013; 34:576-94. [PMID: 24777877 DOI: 10.1002/jat.2935] [Citation(s) in RCA: 51] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2013] [Revised: 08/08/2013] [Accepted: 08/22/2013] [Indexed: 12/29/2022]
Abstract
Early assessment of the toxicity potential of new molecules in pharmaceutical industry is a multi-dimensional task involving predictive systems and screening approaches to aid in the optimization of lead compounds prior to their entry into development phase. Due to the high attrition rate in the pharma industry in last few years, it has become imperative for the nonclinical toxicologist to focus on novel approaches which could be helpful for early screening of drug candidates. The need is that the toxicologists should change their classical approach to a more investigative approach. This review discusses the developments that allow toxicologists to anticipate safety problems and plan ways to address them earlier than ever before. This includes progress in the field of in vitro models, surrogate models, molecular toxicology, 'omics' technologies, translational safety biomarkers, stem-cell based assays and preclinical imaging. The traditional boundaries between teams focusing on efficacy/ safety and preclinical/ clinical aspects in the pharma industry are disappearing, and translational research-centric organizations with a focused vision of bringing drugs forward safely and rapidly are emerging. Today's toxicologist should collaborate with medicinal chemists, pharmacologists, and clinicians and these value-adding contributions will change traditional toxicologists from side-effect identifiers to drug development enablers.
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Affiliation(s)
- Varun Ahuja
- Drug Safety Assessment, Novel Drug Discovery and Development, Lupin Limited (Research Park), 46A/47A, Nande Village, MulshiTaluka, Pune, 412 115, India
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26
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Sasseville VG, Mansfield KG, Brees DJ. Safety biomarkers in preclinical development: translational potential. Vet Pathol 2013; 51:281-91. [PMID: 24091814 DOI: 10.1177/0300985813505117] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
The identification, application, and qualification of safety biomarkers are becoming increasingly critical to successful drug discovery and development as companies are striving to develop drugs for difficult targets and for novel disease indications in a risk-adverse environment. Translational safety biomarkers that are minimally invasive and monitor drug-induced toxicity during human clinical trials are urgently needed to assess whether toxicities observed in preclinical toxicology studies are relevant to humans at therapeutic doses. The interpretation of data during the biomarker qualification phase should include careful consideration of the analytic method used, the biology, pharmacokinetic and pharmacodynamic properties of the biomarker, and the pathophysiology of the process studied. The purpose of this review is to summarize commonly employed technologies in the development of fluid- and tissue-based safety biomarkers in drug discovery and development and to highlight areas of ongoing novel assay development.
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Affiliation(s)
- V G Sasseville
- Discovery and Investigative Safety, Preclinical Safety, Novartis Institutes for Biomedical Research, Cambridge, MA 02139, USA.
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27
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Xing L, Wu L, Liu Y, Ai N, Lu X, Fan X. LTMap: a web server for assessing the potential liver toxicity by genome-wide transcriptional expression data. J Appl Toxicol 2013; 34:805-9. [PMID: 24022982 DOI: 10.1002/jat.2923] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2013] [Revised: 07/30/2013] [Accepted: 07/31/2013] [Indexed: 02/02/2023]
Abstract
Toxicogenomics (TGx) has played a significant role in mechanistic research related with hepatotoxicity as well as liver toxicity prediction. Currently, several large-scale preclinical TGx data sets were made freely accessible to the public, such as Open TG-GATEs. With the availability of a sufficient amount of microarray data, it is important to integrate this information to provide new insights into the risk assessment of potential drug-induced liver toxicity. Here we developed a web server for evaluating the potential liver toxicity based on genome-wide transcriptomics data, namely LTMap. In LTMap, researchers could compare signatures of query compounds against a pregenerated signature database of 20 123 Affymetrix arrays associated with about 170 compounds retrieved from the largest public toxicogenomics data set Open TG-GATEs. Results from this comparison may lead to the unexpected discovery of similar toxicological responses between chemicals. We validated our computational approach for similarity comparison using three example drugs. Our successful applications of LTMap in these case studies demonstrated its utility in revealing the connection of chemicals according to similar toxicological behaviors. Furthermore, a user-friendly web interface is provided by LTMap to browse and search toxicogenomics data (http://tcm.zju.edu.cn/ltmap).
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Affiliation(s)
- Li Xing
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
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28
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Abstract
Recent work has demonstrated the importance of post-transcriptional gene regulation in toxic responses. In the present study, we used two rat models to investigate mRNA translation in the liver following xenobiotic-induced toxicity. By combining polysome profiling with genomic methodologies, we were able to assess global changes in hepatic mRNA translation. Dio3 (iodothyronine deiodinase type III) was identified as a gene that exhibited specific translational repression and had a functional role in a number of relevant canonical pathways. Western blot analysis indicated that this repression led to reduced D3 (the protein expressed by Dio3) levels, enhanced over time and with increased dose. Using Northern blotting techniques and qRT-PCR (quantitative reverse transcription–PCR), we confirmed further that there was no reduction in Dio3 mRNA, suggesting that translational repression of Dio3 is an important determinant of the reduced D3 protein expression following liver damage. Finally, we show that drug-induced hepatotoxicity appears to cause localized disruptions in thyroid hormone levels in the liver and plasma. We suggest that this leads to reduced translation of Dio3 mRNA, which results in decreased D3 production. It may therefore be possible that this is an important mechanism by which the liver can, upon early signs of damage, act rapidly to maintain its own energy equilibrium, thereby avoiding global disruption of the hypothalamic–pituitary–thyroid axis.
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29
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Bai JP, Abernethy DR. Systems Pharmacology to Predict Drug Toxicity: Integration Across Levels of Biological Organization. Annu Rev Pharmacol Toxicol 2013; 53:451-73. [DOI: 10.1146/annurev-pharmtox-011112-140248] [Citation(s) in RCA: 102] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Jane P.F. Bai
- Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland 20993;
| | - Darrell R. Abernethy
- Office of Clinical Pharmacology, Office of Translational Science, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland 20993;
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30
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Sistare FD, DeGeorge JJ. Promise of new translational safety biomarkers in drug development and challenges to regulatory qualification. Biomark Med 2012; 5:497-514. [PMID: 21861671 DOI: 10.2217/bmm.11.52] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
One promise of new translational safety biomarkers (TSBs) is their ability to demonstrate that toxicities in animal studies are monitorable at an early stage, such that human relevance of potential adverse effects of drugs can be safely and definitively evaluated in clinical trials. Another is that they would provide an earlier, more definitive and deeper insight to patient prognosis compared with conventional biomarkers. Recent experience with regulatory authorities indicates that resource demands for new TSB qualifications under the current framework are daunting and the rate of their expansion will be slow, particularly in light of mounting financial pressures on the pharmaceutical industry. Sponsors face a dilemma over engaging in safety biomarker qualification consortia. While it is clear new TSBs could be considered catalysts to drug development and that patient health, business and scientific benefits, described here using examples, should outweigh qualification costs, concerns exist that early ambiguities in biomarker interpretations at the introduction of such new TSBs might hinder drug development.
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Affiliation(s)
- Frank D Sistare
- Safety Assessment & Laboratory Animal Resources, Merck and Co., Inc., West Point, PA 19486-0004, USA.
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Wiesinger M, Mayer B, Jennings P, Lukas A. Comparative analysis of perturbed molecular pathways identified in in vitro and in vivo toxicology studies. Toxicol In Vitro 2012; 26:956-62. [DOI: 10.1016/j.tiv.2012.03.018] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2011] [Revised: 03/26/2012] [Accepted: 03/29/2012] [Indexed: 10/28/2022]
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Schrattenholz A, Šoškić V, Schöpf R, Poznanović S, Klemm-Manns M, Groebe K. Protein biomarkers for in vitro testing of toxicology. MUTATION RESEARCH-GENETIC TOXICOLOGY AND ENVIRONMENTAL MUTAGENESIS 2012; 746:113-23. [DOI: 10.1016/j.mrgentox.2012.02.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2012] [Accepted: 02/21/2012] [Indexed: 12/14/2022]
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Chen M, Zhang M, Borlak J, Tong W. A Decade of Toxicogenomic Research and Its Contribution to Toxicological Science. Toxicol Sci 2012; 130:217-28. [DOI: 10.1093/toxsci/kfs223] [Citation(s) in RCA: 118] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
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Collins BC, Miller CA, Sposny A, Hewitt P, Wells M, Gallagher WM, Pennington SR. Development of a pharmaceutical hepatotoxicity biomarker panel using a discovery to targeted proteomics approach. Mol Cell Proteomics 2012; 11:394-410. [PMID: 22527513 DOI: 10.1074/mcp.m111.016493] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
There is a pressing and continued need for improved predictive power in preclinical pharmaceutical toxicology assessment as substantial numbers of drugs are still removed from the market, or from late-stage development, because of unanticipated issues of toxicity. In recent years a number of consortia have been formed with a view to integrating -omics molecular profiling strategies to increase the sensitivity and predictive power of preclinical toxicology evaluation. In this study we report on the LC-MS based proteomic analysis of the effects of the hepatotoxic compound EMD 335823 on liver from rats using an integrated discovery to targeted proteomics approach. This compound was one of a larger panel studied by a variety of molecular profiling techniques as part of the InnoMed PredTox Consortium. Label-free LC-MS analysis of hepatotoxicant EMD 335823 treated animals revealed only moderate correlation of individual protein expression with changes in mRNA expression observed by transcriptomic analysis of the same liver samples. Significantly however, analysis of the protein and transcript changes at the pathway level revealed they were in good agreement. This higher level analysis was also consistent with the previously suspected PPARα activity of the compound. Subsequently, a panel of potential biomarkers of liver toxicity was assembled from the label-free LC-MS proteomics discovery data, the previously acquired transcriptomics data and selected candidates identified from the literature. We developed and then deployed optimized selected reaction monitoring assays to undertake multiplexed measurement of 48 putative toxicity biomarkers in liver tissue. The development of the selected reaction monitoring assays was facilitated by the construction of a peptide MS/MS spectral library from pooled control and treated rat liver lysate using peptide fractionation by strong cation exchange and off-gel electrophoresis coupled to LC-MS/MS. After iterative optimization and quality control of the selected reaction monitoring assay panel, quantitative measurements of 48 putative biomarkers in the liver of EMD 335823 treated rats were carried out and this revealed that the panel is highly enriched for proteins modulated significantly on drug treatment/hepatotoxic insult. This proof-of-principle study provides a roadmap for future large scale pre-clinical toxicology biomarker verification studies whereby putative toxicity biomarkers assembled from multiple disparate sources can be evaluated at medium-high throughput by targeted MS.
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Affiliation(s)
- Ben C Collins
- UCD School of Medicine and Medical Science, University College Dublin, Dublin, Ireland
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Van Summeren A, Renes J, van Delft JH, Kleinjans JC, Mariman EC. Proteomics in the search for mechanisms and biomarkers of drug-induced hepatotoxicity. Toxicol In Vitro 2012; 26:373-85. [DOI: 10.1016/j.tiv.2012.01.012] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2011] [Revised: 12/22/2011] [Accepted: 01/09/2012] [Indexed: 10/14/2022]
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Abstract
HIV-1-infected individuals exhibit remarkable variation in the onset of disease. Virus replication and disease progression depend on host cellular transcription and gene regulation in virus-specific target cells. Both viral and host factors are implicated in this differential regulation. Gene arrays and transcriptome analyses might shed light on why some infected individuals remain asymptomatic while others progress rapidly to AIDS. Here we review developments in HIV research using gene array technologies and the unifying concepts that have emerged from these studies. Gene set enrichment analysis has revealed gene signatures linked to disease progression involving pathways related to metabolism, apoptosis, cell-cycle dysregulation, and T-cell signaling. Macrophages contain anti-apoptotic signatures. Also, HIV-1 regulates previously under-emphasized cholesterol biosynthesis and energy production pathways. Notably, cellular pathways linked to a subset of HIV-infected individuals known as non-progressors contribute to survival and anti-viral responses.
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Affiliation(s)
- Rajeev Mehla
- Department of Infectious Diseases and Microbiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA.
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Keller DA, Juberg DR, Catlin N, Farland WH, Hess FG, Wolf DC, Doerrer NG. Identification and characterization of adverse effects in 21st century toxicology. Toxicol Sci 2012; 126:291-7. [PMID: 22262567 DOI: 10.1093/toxsci/kfr350] [Citation(s) in RCA: 57] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
The practice of toxicology is changing rapidly, as demonstrated by the response to the 2007 NRC report on "Toxicity Testing in the 21(st) Century." New assays are being developed to replace animal testing; yet the use of data from these assays in decision making is not clear. A Health and Environmental Sciences Institute committee held a May 2011 workshop to discuss approaches to identifying adverse effects in the context of the NRC report. Scientists from industry, government, academia, and NGOs discussed two case studies and explored how information from new, high data content assays developed for screening can be used to differentiate adverse effects from adaptive responses. The terms "adverse effect" and "adaptive response" were defined, as well as two new terms, the relevant pathways of toxicological concern (RPTCs) and relevant responses for regulation (RRRs). RPTCs are biochemical pathways associated with adverse events and need to be elucidated before they are used in regulatory decision making. RRRs are endpoints that are the basis for risk assessment and may or may not be at the level of pathways. Workshop participants discussed the criteria for determining whether, at the RPTC level, an effect is potentially adverse or potentially indicative of adaptability, and how the use of prototypical, data-rich compounds could lead to a greater understanding of RPTCs and their use as RRRs. Also discussed was the use of RPTCs in a weight-of-evidence approach to risk assessment. Inclusion of data at this level could decrease uncertainty in risk assessments but will require the use of detailed dosimetry and consideration of exposure context and the time and dose continuum to yield scientifically based decisions. The results of this project point to the need for an extensive effort to characterize RPTCs and their use in risk assessment to make the vision of the 2007 NRC report a reality.
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Integrated transcriptomic and proteomic evaluation of gentamicin nephrotoxicity in rats. Toxicol Appl Pharmacol 2012; 258:124-33. [DOI: 10.1016/j.taap.2011.10.015] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2011] [Revised: 10/04/2011] [Accepted: 10/21/2011] [Indexed: 02/06/2023]
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Turteltaub KW, Davis MA, Burns-Naas LA, Lawton MP, Clark AM, Reynolds JA. Identification and Elucidation of the Biology of Adverse Events: The Challenges of Safety Assessment and Translational Medicine. Clin Cancer Res 2011; 17:6641-5. [DOI: 10.1158/1078-0432.ccr-11-1106] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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40
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A comparative integrated transcript analysis and functional characterization of differential mechanisms for induction of liver hypertrophy in the rat. Toxicol Appl Pharmacol 2011; 252:85-96. [DOI: 10.1016/j.taap.2011.01.021] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2010] [Revised: 01/14/2011] [Accepted: 01/28/2011] [Indexed: 11/18/2022]
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Matheis KA, Com E, Gautier JC, Guerreiro N, Brandenburg A, Gmuender H, Sposny A, Hewitt P, Amberg A, Boernsen O, Riefke B, Hoffmann D, Mally A, Kalkuhl A, Suter L, Dieterle F, Staedtler F. Cross-study and cross-omics comparisons of three nephrotoxic compounds reveal mechanistic insights and new candidate biomarkers. Toxicol Appl Pharmacol 2010; 252:112-22. [PMID: 21081137 DOI: 10.1016/j.taap.2010.11.006] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2010] [Revised: 10/15/2010] [Accepted: 11/09/2010] [Indexed: 11/18/2022]
Abstract
The European InnoMed-PredTox project was a collaborative effort between 15 pharmaceutical companies, 2 small and mid-sized enterprises, and 3 universities with the goal of delivering deeper insights into the molecular mechanisms of kidney and liver toxicity and to identify mechanism-linked diagnostic or prognostic safety biomarker candidates by combining conventional toxicological parameters with "omics" data. Mechanistic toxicity studies with 16 different compounds, 2 dose levels, and 3 time points were performed in male Crl: WI(Han) rats. Three of the 16 investigated compounds, BI-3 (FP007SE), Gentamicin (FP009SF), and IMM125 (FP013NO), induced kidney proximal tubule damage (PTD). In addition to histopathology and clinical chemistry, transcriptomics microarray and proteomics 2D-DIGE analysis were performed. Data from the three PTD studies were combined for a cross-study and cross-omics meta-analysis of the target organ. The mechanistic interpretation of kidney PTD-associated deregulated transcripts revealed, in addition to previously described kidney damage transcript biomarkers such as KIM-1, CLU and TIMP-1, a number of additional deregulated pathways congruent with histopathology observations on a single animal basis, including a specific effect on the complement system. The identification of new, more specific biomarker candidates for PTD was most successful when transcriptomics data were used. Combining transcriptomics data with proteomics data added extra value.
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Affiliation(s)
- Katja A Matheis
- Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany.
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Ellinger-Ziegelbauer H, Adler M, Amberg A, Brandenburg A, Callanan JJ, Connor S, Fountoulakis M, Gmuender H, Gruhler A, Hewitt P, Hodson M, Matheis KA, McCarthy D, Raschke M, Riefke B, Schmitt CS, Sieber M, Sposny A, Suter L, Sweatman B, Mally A. The enhanced value of combining conventional and "omics" analyses in early assessment of drug-induced hepatobiliary injury. Toxicol Appl Pharmacol 2010; 252:97-111. [PMID: 20888850 DOI: 10.1016/j.taap.2010.09.022] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2010] [Revised: 09/17/2010] [Accepted: 09/23/2010] [Indexed: 10/19/2022]
Abstract
The InnoMed PredTox consortium was formed to evaluate whether conventional preclinical safety assessment can be significantly enhanced by incorporation of molecular profiling ("omics") technologies. In short-term toxicological studies in rats, transcriptomics, proteomics and metabolomics data were collected and analyzed in relation to routine clinical chemistry and histopathology. Four of the sixteen hepato- and/or nephrotoxicants given to rats for 1, 3, or 14days at two dose levels induced similar histopathological effects. These were characterized by bile duct necrosis and hyperplasia and/or increased bilirubin and cholestasis, in addition to hepatocyte necrosis and regeneration, hepatocyte hypertrophy, and hepatic inflammation. Combined analysis of liver transcriptomics data from these studies revealed common gene expression changes which allowed the development of a potential sequence of events on a mechanistic level in accordance with classical endpoint observations. This included genes implicated in early stress responses, regenerative processes, inflammation with inflammatory cell immigration, fibrotic processes, and cholestasis encompassing deregulation of certain membrane transporters. Furthermore, a preliminary classification analysis using transcriptomics data suggested that prediction of cholestasis may be possible based on gene expression changes seen at earlier time-points. Targeted bile acid analysis, based on LC-MS metabonomics data demonstrating increased levels of conjugated or unconjugated bile acids in response to individual compounds, did not provide earlier detection of toxicity as compared to conventional parameters, but may allow distinction of different types of hepatobiliary toxicity. Overall, liver transcriptomics data delivered mechanistic and molecular details in addition to the classical endpoint observations which were further enhanced by targeted bile acid analysis using LC/MS metabonomics.
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