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Gi M, Suzuki S, Kanki M, Yokohira M, Tsukamoto T, Fujioka M, Vachiraarunwong A, Qiu G, Guo R, Wanibuchi H. A novel support vector machine-based 1-day, single-dose prediction model of genotoxic hepatocarcinogenicity in rats. Arch Toxicol 2024:10.1007/s00204-024-03755-w. [PMID: 38762666 DOI: 10.1007/s00204-024-03755-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Accepted: 03/27/2024] [Indexed: 05/20/2024]
Abstract
The development of a rapid and accurate model for determining the genotoxicity and carcinogenicity of chemicals is crucial for effective cancer risk assessment. This study aims to develop a 1-day, single-dose model for identifying genotoxic hepatocarcinogens (GHCs) in rats. Microarray gene expression data from the livers of rats administered a single dose of 58 compounds, including 5 GHCs, was obtained from the Open TG-GATEs database and used for the identification of marker genes and the construction of a predictive classifier to identify GHCs in rats. We identified 10 gene markers commonly responsive to all 5 GHCs and used them to construct a support vector machine-based predictive classifier. In the silico validation using the expression data of the Open TG-GATEs database indicates that this classifier distinguishes GHCs from other compounds with high accuracy. To further assess the model's effectiveness and reliability, we conducted multi-institutional 1-day single oral administration studies on rats. These studies examined 64 compounds, including 23 GHCs, with gene expression data of the marker genes obtained via quantitative PCR 24 h after a single oral administration. Our results demonstrate that qPCR analysis is an effective alternative to microarray analysis. The GHC predictive model showed high accuracy and reliability, achieving a sensitivity of 91% (21/23) and a specificity of 93% (38/41) across multiple validation studies in three institutions. In conclusion, the present 1-day single oral administration model proves to be a reliable and highly sensitive tool for identifying GHCs and is anticipated to be a valuable tool in identifying and screening potential GHCs.
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Affiliation(s)
- Min Gi
- Department of Environmental Risk Assessment, Graduate School of Medicine, Osaka Metropolitan University, Osaka, 545-8585, Japan
- Department of Molecular Pathology, Graduate School of Medicine, Osaka Metropolitan University, Osaka, 545-8585, Japan
| | - Shugo Suzuki
- Department of Molecular Pathology, Graduate School of Medicine, Osaka Metropolitan University, Osaka, 545-8585, Japan
| | - Masayuki Kanki
- Department of Molecular Pathology, Graduate School of Medicine, Osaka Metropolitan University, Osaka, 545-8585, Japan
| | - Masanao Yokohira
- Department of Medical Education, Faculty of Medicine, Kagawa University, Miki-cho, Kita-gun, Kagawa, 761-0793, Japan
- Department of Pathology and Host-Defense, Faculty of Medicine, Kagawa University, Miki-cho, Kita-gun, Kagawa, 761-0793, Japan
| | - Tetsuya Tsukamoto
- Department of Diagnostic Pathology, Graduate School of Medicine, Fujita Health University, Toyoake, Aichi, 470-1192, Japan
| | - Masaki Fujioka
- Department of Molecular Pathology, Graduate School of Medicine, Osaka Metropolitan University, Osaka, 545-8585, Japan
| | - Arpamas Vachiraarunwong
- Department of Environmental Risk Assessment, Graduate School of Medicine, Osaka Metropolitan University, Osaka, 545-8585, Japan
| | - Guiyu Qiu
- Department of Molecular Pathology, Graduate School of Medicine, Osaka Metropolitan University, Osaka, 545-8585, Japan
| | - Runjie Guo
- Department of Environmental Risk Assessment, Graduate School of Medicine, Osaka Metropolitan University, Osaka, 545-8585, Japan
| | - Hideki Wanibuchi
- Department of Molecular Pathology, Graduate School of Medicine, Osaka Metropolitan University, Osaka, 545-8585, Japan.
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Chandy M, Hill T, Jimenez-Tellez N, Wu JC, Sarles SE, Hensel E, Wang Q, Rahman I, Conklin DJ. Addressing Cardiovascular Toxicity Risk of Electronic Nicotine Delivery Systems in the Twenty-First Century: "What Are the Tools Needed for the Job?" and "Do We Have Them?". Cardiovasc Toxicol 2024; 24:435-471. [PMID: 38555547 DOI: 10.1007/s12012-024-09850-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 03/19/2024] [Indexed: 04/02/2024]
Abstract
Cigarette smoking is positively and robustly associated with cardiovascular disease (CVD), including hypertension, atherosclerosis, cardiac arrhythmias, stroke, thromboembolism, myocardial infarctions, and heart failure. However, after more than a decade of ENDS presence in the U.S. marketplace, uncertainty persists regarding the long-term health consequences of ENDS use for CVD. New approach methods (NAMs) in the field of toxicology are being developed to enhance rapid prediction of human health hazards. Recent technical advances can now consider impact of biological factors such as sex and race/ethnicity, permitting application of NAMs findings to health equity and environmental justice issues. This has been the case for hazard assessments of drugs and environmental chemicals in areas such as cardiovascular, respiratory, and developmental toxicity. Despite these advances, a shortage of widely accepted methodologies to predict the impact of ENDS use on human health slows the application of regulatory oversight and the protection of public health. Minimizing the time between the emergence of risk (e.g., ENDS use) and the administration of well-founded regulatory policy requires thoughtful consideration of the currently available sources of data, their applicability to the prediction of health outcomes, and whether these available data streams are enough to support an actionable decision. This challenge forms the basis of this white paper on how best to reveal potential toxicities of ENDS use in the human cardiovascular system-a primary target of conventional tobacco smoking. We identify current approaches used to evaluate the impacts of tobacco on cardiovascular health, in particular emerging techniques that replace, reduce, and refine slower and more costly animal models with NAMs platforms that can be applied to tobacco regulatory science. The limitations of these emerging platforms are addressed, and systems biology approaches to close the knowledge gap between traditional models and NAMs are proposed. It is hoped that these suggestions and their adoption within the greater scientific community will result in fresh data streams that will support and enhance the scientific evaluation and subsequent decision-making of tobacco regulatory agencies worldwide.
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Affiliation(s)
- Mark Chandy
- Robarts Research Institute, Western University, London, N6A 5K8, Canada
| | - Thomas Hill
- Division of Nonclinical Science, Center for Tobacco Products, US Food and Drug Administration, Silver Spring, MD, 20993, USA
| | - Nerea Jimenez-Tellez
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94304, USA
| | - Joseph C Wu
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94304, USA
| | - S Emma Sarles
- Biomedical and Chemical Engineering PhD Program, Rochester Institute of Technology, Rochester, NY, 14623, USA
| | - Edward Hensel
- Department of Mechanical Engineering, Rochester Institute of Technology, Rochester, NY, 14623, USA
| | - Qixin Wang
- Department of Environmental Medicine, University of Rochester Medical Center, Rochester, NY, 14642, USA
| | - Irfan Rahman
- Department of Environmental Medicine, University of Rochester Medical Center, Rochester, NY, 14642, USA
| | - Daniel J Conklin
- Division of Environmental Medicine, Department of Medicine, Center for Cardiometabolic Science, Christina Lee Brown Envirome Institute, University of Louisville, 580 S. Preston St., Delia Baxter, Rm. 404E, Louisville, KY, 40202, USA.
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Christopher Corton J, Mitchell CA, Auerbach S, Bushel JP, Ellinger-Ziegelbauer H, Escobar PA, Froetschl R, Harrill AH, Johnson K, Klaunig JE, Pandiri AR, Podtelezhnikov AA, Rager JE, Tanis KQ, van der Laan JW, Vespa A, Yauk CL, Pettit SD, Sistare FD. A Collaborative Initiative to Establish Genomic Biomarkers for Assessing Tumorigenic Potential to Reduce Reliance on Conventional Rodent Carcinogenicity Studies. Toxicol Sci 2022; 188:4-16. [PMID: 35404422 PMCID: PMC9238304 DOI: 10.1093/toxsci/kfac041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
There is growing recognition across broad sectors of the scientific community that use of genomic biomarkers has the potential to reduce the need for conventional rodent carcinogenicity studies of industrial chemicals, agrochemicals, and pharmaceuticals through a weight-of-evidence approach. These biomarkers fall into 2 major categories: (1) sets of gene transcripts that can identify distinct tumorigenic mechanisms of action; and (2) cancer driver gene mutations indicative of rapidly expanding growth-advantaged clonal cell populations. This call-to-action article describes a collaborative approach launched to develop and qualify biomarker gene expression panels that measure widely accepted molecular pathways linked to tumorigenesis and their activation levels to predict tumorigenic doses of chemicals from short-term exposures. Growing evidence suggests that application of such biomarker panels in short-term exposure rodent studies can identify both tumorigenic hazard and tumorigenic activation levels for chemical-induced carcinogenicity. In the future, this approach will be expanded to include methodologies examining mutations in key cancer driver gene mutation hotspots as biomarkers of both genotoxic and nongenotoxic chemical tumor risk. Analytical, technical, and biological validation studies of these complementary genomic tools are being undertaken by multisector and multidisciplinary collaborative teams within the Health and Environmental Sciences Institute. Success from these efforts will facilitate the transition from current heavy reliance on conventional 2-year rodent carcinogenicity studies to more rapid animal- and resource-sparing approaches for mechanism-based carcinogenicity evaluation supporting internal and regulatory decision-making.
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Affiliation(s)
- J Christopher Corton
- Center for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, NC, USA
| | | | - Scott Auerbach
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - J Pierre Bushel
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, NC, USA
| | | | - Patricia A Escobar
- Safety Assessment and Laboratory Animal Resources, Merck Sharp & Dohme Corp, West Point, PA, USA
| | - Roland Froetschl
- BfArM-Bundesinstitut für Arzneimittel und Medizinprodukte, Federal Institute for Drugs and Medical Devices, Kurt-Georg-Kiesinger-Allee 3, Bonn, Germany
| | - Alison H Harrill
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | | | - James E Klaunig
- Laboratory of Investigative Toxicology and Pathology, Department of Environmental and Occupational Health, Indiana School of Public Health, Indiana University, Bloomington, IN, USA
| | - Arun R Pandiri
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | | | - Julia E Rager
- The Institute for Environmental Health Solutions, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Keith Q Tanis
- Safety Assessment and Laboratory Animal Resources, Merck Sharp & Dohme Corp, West Point, PA, USA
| | - Jan Willem van der Laan
- Section on Pharmacology, Toxicology and Kinetics, Medicines Evaluation Board, Utrecht, The Netherlands
| | - Alisa Vespa
- Therapeutic Products Directorate, Health Canada, Ottawa, Canada
| | - Carole L Yauk
- Department of Biology, University of Ottawa, Ottawa, ON, Canada
| | - Syril D Pettit
- Health and Environmental Sciences Institute, Washington, DC, USA
| | - Frank D Sistare
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA
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Corton JC, Korunes KL, Abedini J, El-Masri H, Brown J, Paul-Friedman K, Liu Y, Martini C, He S, Rooney J. Thresholds Derived From Common Measures in Rat Studies Are Predictive of Liver Tumorigenic Chemicals. Toxicol Pathol 2020; 48:857-874. [DOI: 10.1177/0192623320960412] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
We hypothesized that typical tissue and clinical chemistry (ClinChem) end points measured in rat toxicity studies exhibit chemical-independent biological thresholds beyond which cancer occurs. Using the rat in vivo TG-GATES study, 75 chemicals were examined across chemical-dose-time comparisons that could be linked to liver tumor outcomes. Thresholds for liver weight to body weight (LW/BW) and 21 serum ClinChem end points were defined as the maximum and minimum values for those exposures that did not lead to liver tumors in rats. Upper thresholds were identified for LW/BW (117%), aspartate aminotransferase (195%), alanine aminotransferase (141%), alkaline phosphatase (152%), and total bilirubin (115%), and lower thresholds were identified for phospholipids (82%), relative albumin (93%), total cholesterol (82%), and total protein (94%). Thresholds derived from the TG-GATES data set were consistent across other acute and subchronic rat studies. A training set of ClinChem and LW/BW thresholds derived from a 38 chemical training set from TG-GATES was predictive of liver tumor outcomes for a test set of 37 independent TG-GATES chemicals (91%). The thresholds were most predictive when applied to 7d treatments (98%). These findings provide support that biological thresholds for common end points in rodent studies can be used to predict chemical tumorigenic potential.
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Affiliation(s)
- J. Christopher Corton
- Center for Computational Toxicology and Exposure, U.S. EPA, Research Triangle Park, NC, USA
| | - Katharine L. Korunes
- Center for Computational Toxicology and Exposure, U.S. EPA, Research Triangle Park, NC, USA
- Department of Evolutionary Anthropology, Duke University, Durham, NC, USA
| | - Jaleh Abedini
- Center for Computational Toxicology and Exposure, U.S. EPA, Research Triangle Park, NC, USA
| | - Hisham El-Masri
- Center for Computational Toxicology and Exposure, U.S. EPA, Research Triangle Park, NC, USA
| | - Jason Brown
- Center for Computational Toxicology and Exposure, U.S. EPA, Research Triangle Park, NC, USA
| | - Katie Paul-Friedman
- Center for Computational Toxicology and Exposure, U.S. EPA, Research Triangle Park, NC, USA
| | - Ying Liu
- ASRC Federal, Research Triangle Park, NC, USA
| | | | - Shihan He
- ASRC Federal, Research Triangle Park, NC, USA
| | - John Rooney
- Center for Computational Toxicology and Exposure, U.S. EPA, Research Triangle Park, NC, USA
- Oak Ridge Institute for Science and Education (ORISE), National Health and Environmental Effects Research Laboratory (NHEERL), Office of Research and Development, U.S. Environmental Protection Agency (EPA), Research Triangle Park, NC, USA
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Lewis RW, Hill T, Corton JC. A set of six Gene expression biomarkers and their thresholds identify rat liver tumorigens in short-term assays. Toxicology 2020; 443:152547. [PMID: 32755643 PMCID: PMC10439517 DOI: 10.1016/j.tox.2020.152547] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 07/23/2020] [Accepted: 07/28/2020] [Indexed: 02/01/2023]
Abstract
Traditional methods for cancer risk assessment are retrospective, resource-intensive, and not feasible for the vast majority of environmental chemicals. In earlier studies, we used a set of six biomarkers to accurately identify liver tumorigens in transcript profiles derived from chemically-treated rats using either a Toxicological Priority Index (ToxPi) approach or using derived biomarker thresholds for cancer. The biomarkers consisting of 7-113 genes are used to predict the most common liver cancer molecular initiating events: genotoxicity, cytotoxicity and activation of the xenobiotic receptors AhR, CAR, ER, and PPARα. In the present study, we apply and evaluate the performance of these methods for cancer prediction in an independent rat liver study of 44 chemicals (6 h-7d exposures) examined by Affymetrix arrays. In the first approach, ToxPi ranking of biomarker scores consistently gave the highest scores to tumorigenic chemical-dose pairs; balanced accuracies for identification of liver tumorigenic chemicals were up to 89 %. The second approach used tumorigenic thresholds derived in the present study or from our earlier study that were set at the maximum value for chemical-dose exposures without detectable liver tumor outcomes. Using these thresholds, balanced accuracies were up to 90 %. Both approaches identified all tumorigenic chemicals. Almost all of the tumorigenic chemicals activated more than one MIE. We also compared biomarker responses between two types of profiling platforms (Affymetrix full-genome array, TempO-Seq 1500+ array containing ∼2600 genes) and found that the lack of the full set of biomarker genes on the 1500+ array resulted in decreased ability to identify chemicals that activate the MIEs. Overall, these results demonstrate that predictive approaches based on the 6 biomarkers could be used in short-term assays to identify chemicals and their doses that induce liver tumors, the most common endpoint in rodent bioassays.
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Affiliation(s)
- Robert W Lewis
- Center for Computational Toxicology and Exposure, U.S. EPA, Research Triangle Park, NC, United States.
| | - Thomas Hill
- Center for Computational Toxicology and Exposure, U.S. EPA, Research Triangle Park, NC, United States; Oak Ridge Institute for Science and Education (ORISE) fellow Office of Research and Development, U.S. Environmental Protection Agency (EPA), Research Triangle Park, NC, United States.
| | - J Christopher Corton
- Center for Computational Toxicology and Exposure, U.S. EPA, Research Triangle Park, NC, United States.
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