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Chen YW, Diamante G, Ding J, Nghiem TX, Yang J, Ha SM, Cohn P, Arneson D, Blencowe M, Garcia J, Zaghari N, Patel P, Yang X. PharmOmics: A species- and tissue-specific drug signature database and gene-network-based drug repositioning tool. iScience 2022; 25:104052. [PMID: 35345455 PMCID: PMC8957031 DOI: 10.1016/j.isci.2022.104052] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 01/29/2022] [Accepted: 03/08/2022] [Indexed: 12/29/2022] Open
Abstract
Drug development has been hampered by a high failure rate in clinical trials due to our incomplete understanding of drug functions across organs and species. Therefore, elucidating species- and tissue-specific drug functions can provide insights into therapeutic efficacy, potential adverse effects, and interspecies differences necessary for effective translational medicine. Here, we present PharmOmics, a drug knowledgebase and analytical tool that is hosted on an interactive web server. Using tissue- and species-specific transcriptome data from human, mouse, and rat curated from different databases, we implemented a gene-network-based approach for drug repositioning. We demonstrate the potential of PharmOmics to retrieve known therapeutic drugs and identify drugs with tissue toxicity using in silico performance assessment. We further validated predicted drugs for nonalcoholic fatty liver disease in mice. By combining tissue- and species-specific in vivo drug signatures with gene networks, PharmOmics serves as a complementary tool to support drug characterization and network-based medicine. Development of PharmOmics, a platform for drug repositioning and toxicity prediction Contains >18000 species/tissue-specific gene signatures for 941 drugs and chemicals Benchmarked and validated network-based drug repositioning and toxicity prediction PharmOmics is freely accessible via an online web server to facilitate user access
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Affiliation(s)
- Yen-Wei Chen
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Interdepartmental Program of Molecular Toxicology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Graciel Diamante
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Interdepartmental Program of Molecular Toxicology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Jessica Ding
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Interdepartmental Program of Molecular, Cellular, & Integrative Physiology, Los Angeles, Los Angeles, CA 90095, USA
| | - Thien Xuan Nghiem
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Jessica Yang
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Sung-Min Ha
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Peter Cohn
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Douglas Arneson
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Interdepartmental Program of Bioinformatics, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Montgomery Blencowe
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Interdepartmental Program of Molecular, Cellular, & Integrative Physiology, Los Angeles, Los Angeles, CA 90095, USA
| | - Jennifer Garcia
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Nima Zaghari
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Paul Patel
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Xia Yang
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Interdepartmental Program of Molecular Toxicology, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Interdepartmental Program of Molecular, Cellular, & Integrative Physiology, Los Angeles, Los Angeles, CA 90095, USA
- Interdepartmental Program of Bioinformatics, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Corresponding author
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Advances in Engineered Liver Models for Investigating Drug-Induced Liver Injury. BIOMED RESEARCH INTERNATIONAL 2016; 2016:1829148. [PMID: 27725933 PMCID: PMC5048025 DOI: 10.1155/2016/1829148] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/23/2016] [Accepted: 07/19/2016] [Indexed: 12/17/2022]
Abstract
Drug-induced liver injury (DILI) is a major cause of drug attrition. Testing drugs on human liver models is essential to mitigate the risk of clinical DILI since animal studies do not always suffice due to species-specific differences in liver pathways. While primary human hepatocytes (PHHs) can be cultured on extracellular matrix proteins, a rapid decline in functions leads to low sensitivity (<50%) in DILI prediction. Semiconductor-driven engineering tools now allow precise control over the hepatocyte microenvironment to enhance and stabilize phenotypic functions. The latest platforms coculture PHHs with stromal cells to achieve hepatic stability and enable crosstalk between the various liver cell types towards capturing complex cellular mechanisms in DILI. The recent introduction of induced pluripotent stem cell-derived human hepatocyte-like cells can potentially allow a better understanding of interindividual differences in idiosyncratic DILI. Liver models are also being coupled to other tissue models via microfluidic perfusion to study the intertissue crosstalk upon drug exposure as in a live organism. Here, we review the major advances being made in the engineering of liver models and readouts as they pertain to DILI investigations. We anticipate that engineered human liver models will reduce drug attrition, animal usage, and cases of DILI in humans.
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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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Hammad S, Ahmed H. Biomarker: the universe of chemically induced gene expression alterations in human hepatocyte. EXCLI JOURNAL 2014; 13:1275-7. [PMID: 26417340 PMCID: PMC4462829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Download PDF] [Subscribe] [Scholar Register] [Received: 12/08/2014] [Accepted: 12/09/2014] [Indexed: 11/10/2022]
Affiliation(s)
- Seddik Hammad
- Department of Forensic Medicine and Veterinary Toxicology, Faculty of Veterinary Medicine, South Valley University, Qena, Egypt,*To whom correspondence should be addressed: Seddik Hammad, Department of Forensic Medicine and Veterinary Toxicology, Faculty of Veterinary Medicine, South Valley University, Qena, Egypt, E-mail:
| | - Hassan Ahmed
- Division of Cerebral Circuitry, National Institute for Physiological Sciences, Okazaki, Japan
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