1
|
Alidoost M, Wilson JL. Preclinical side effect prediction through pathway engineering of protein interaction network models. CPT Pharmacometrics Syst Pharmacol 2024; 13:1180-1200. [PMID: 38736280 PMCID: PMC11247120 DOI: 10.1002/psp4.13150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 03/01/2024] [Accepted: 04/08/2024] [Indexed: 05/14/2024] Open
Abstract
Modeling tools aim to predict potential drug side effects, although they suffer from imperfect performance. Specifically, protein-protein interaction models predict drug effects from proteins surrounding drug targets, but they tend to overpredict drug phenotypes and require well-defined pathway phenotypes. In this study, we used PathFX, a protein-protein interaction tool, to predict side effects for active ingredient-side effect pairs extracted from drug labels. We observed limited performance and defined new pathway phenotypes using pathway engineering strategies. We defined new pathway phenotypes using a network-based and gene expression-based approach. Overall, we discovered a trade-off between sensitivity and specificity values and demonstrated a way to limit overprediction for side effects with sufficient true positive examples. We compared our predictions to animal models and demonstrated similar performance metrics, suggesting that protein-protein interaction models do not need perfect evaluation metrics to be useful. Pathway engineering, through the inclusion of true positive examples and omics measurements, emerges as a promising approach to enhance the utility of protein interaction network models for drug effect prediction.
Collapse
Affiliation(s)
- Mohammadali Alidoost
- Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Jennifer L Wilson
- Department of Bioengineering, University of California, Los Angeles, California, USA
| |
Collapse
|
2
|
Ribba B. Quantitative systems pharmacology in the age of artificial intelligence. CPT Pharmacometrics Syst Pharmacol 2023; 12:1823-1826. [PMID: 37779349 PMCID: PMC10725257 DOI: 10.1002/psp4.13047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 08/30/2023] [Accepted: 08/31/2023] [Indexed: 10/03/2023] Open
Affiliation(s)
- Benjamin Ribba
- Roche Pharma Research and Early Development (pRED), Roche Innovation Center, F. Hoffmann‐La Roche Ltd.BaselSwitzerland
| |
Collapse
|
3
|
Effect of Yisui Multipurpose Soup's Amelioration on D-Galactose-Induced Neuronal Cells. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2022; 2022:3372350. [PMID: 35754679 PMCID: PMC9217601 DOI: 10.1155/2022/3372350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 05/20/2022] [Accepted: 05/23/2022] [Indexed: 11/17/2022]
Abstract
This study clarified the regulatory effect of Yisui multipurpose Soup towards D-galactose-induced cognitive impairment cell model on the molecular level. We first constructed and cultured the cell model of cognitive impairment induced by D-galactose in neurons in vitro and then cultured the cells in the medium supplemented with different doses of drug-containing serum of Yisui multipurpose soup. Expressions of inflammatory cytokine tumor necrosis factor-α (TNF-α), inducible nitric oxide synthase (iNOS), nitric oxide (NO), and interleukin-1β (IL-1β) were assessed by the ELISA and western blot, and cell apoptosis was determined by flow cytometry and TUNEL. The expression changes of apoptosis-related proteins Bcl-2 and Bax were estimated by immunofluorescence, qPCR, and western blot. Finally, we analyzed and made the network interaction diagram of Yisui multipurpose soup-components-targets through the network pharmacology method, from which we could learn that there were 1104 gene targets related to vascular cognitive impairment (VCI) and 1071 component targets of Yisui multipurpose soup. And there were 251 overlapping genes, mainly gathering in protein binding, protein modification, MAPK signaling pathway, and calcium signaling pathway. The expressions of TNF-α, iNOS, NO, and IL-1β were significantly decreased after the culture medium was replaced by medium containing drug serum. We also found that the effect of high-dose drug-containing serum on the expression of inflammatory factors was better than that of low dose. The Yisui multipurpose soup drug serum in the medium not only significantly increased Bcl-2 expression and effectively reduced Bax expression, but also inhibited the apoptosis of neurons induced by D-galactose. In conclusion, Yisui multipurpose soup could effectively protect D-galactose-induced neuronal cell cognitive impairment by orchestrating expressions of the inflammatory factors TNF-α, iNOS, NO, and IL-1β and the apoptosis-related proteins Bcl-2 and Bax.
Collapse
|
4
|
Combating Viral Diseases in the Era of Systems Medicine. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2022; 2486:87-104. [PMID: 35437720 DOI: 10.1007/978-1-0716-2265-0_6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Viruses can cause many diseases resulting in disabilities and death. Fortunately, advances in systems medicine enable the development of effective therapies for treating viral diseases, of vaccines to prevent viral infections, as well as of diagnostic tools to mitigate the risk and reduce the death toll. Characterizing the SARS-CoV-2 gene sequence and the role of its spike protein in infection informs development of small molecule drugs, antibodies, and vaccines to combat infection and complication, as well as to end the pandemic. Drug repurposing of small molecule drugs is a viable strategy to combat viral diseases; the key concepts include (1) linking a drug candidate's pharmacological network to its pharmacodynamic response in patients; (2) linking a drug candidate's physicochemical properties to its pharmacokinetic characteristics; and (3) optimizing the safe and effective dosing regimen within its therapeutic window. Computational integration of drug-induced signaling pathways with clinical outcomes is useful to inform selection of potential drug candidates with respect to safety and effectiveness. Key pharmacokinetic and pharmacodynamic principles for computational optimization of drug development include a drug candidate's Cminss/IC95 ratio, pharmacokinetic characteristics, and systemic exposure-response relationship, where Cminss is the trough concentration following multiple dosing. In summary, systems medicine approaches play a vital role in global success in combating viral diseases, including global real-time information sharing, development of test kits, drug repurposing, discovery and development of safe, effective therapies, detection of highly transmissible and deadly variants, and development of vaccines.
Collapse
|
5
|
Bloomingdale P, Meregalli C, Pollard K, Canta A, Chiorazzi A, Fumagalli G, Monza L, Pozzi E, Alberti P, Ballarini E, Oggioni N, Carlson L, Liu W, Ghandili M, Ignatowski TA, Lee KP, Moore MJ, Cavaletti G, Mager DE. Systems Pharmacology Modeling Identifies a Novel Treatment Strategy for Bortezomib-Induced Neuropathic Pain. Front Pharmacol 2022; 12:817236. [PMID: 35126148 PMCID: PMC8809372 DOI: 10.3389/fphar.2021.817236] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 12/16/2021] [Indexed: 11/17/2022] Open
Abstract
Chemotherapy-induced peripheral neurotoxicity is a common dose-limiting side effect of several cancer chemotherapeutic agents, and no effective therapies exist. Here we constructed a systems pharmacology model of intracellular signaling in peripheral neurons to identify novel drug targets for preventing peripheral neuropathy associated with proteasome inhibitors. Model predictions suggested the combinatorial inhibition of TNFα, NMDA receptors, and reactive oxygen species should prevent proteasome inhibitor-induced neuronal apoptosis. Dexanabinol, an inhibitor of all three targets, partially restored bortezomib-induced reduction of proximal action potential amplitude and distal nerve conduction velocity in vitro and prevented bortezomib-induced mechanical allodynia and thermal hyperalgesia in rats, including a partial recovery of intraepidermal nerve fiber density. Dexanabinol failed to restore bortezomib-induced decreases in electrophysiological endpoints in rats, and it did not compromise bortezomib anti-cancer effects in U266 multiple myeloma cells and a murine xenograft model. Owing to its favorable safety profile in humans and preclinical efficacy, dexanabinol might represent a treatment option for bortezomib-induced neuropathic pain.
Collapse
Affiliation(s)
- Peter Bloomingdale
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, United States
| | - Cristina Meregalli
- Experimental Neurology Unit and Milan Center for Neuroscience, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
| | - Kevin Pollard
- Department of Biomedical Engineering, School of Science and Engineering, Tulane University, New Orleans, LA, United States
| | - Annalisa Canta
- Experimental Neurology Unit and Milan Center for Neuroscience, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
| | - Alessia Chiorazzi
- Experimental Neurology Unit and Milan Center for Neuroscience, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
| | - Giulia Fumagalli
- Experimental Neurology Unit and Milan Center for Neuroscience, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
| | - Laura Monza
- Experimental Neurology Unit and Milan Center for Neuroscience, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
| | - Eleonora Pozzi
- Experimental Neurology Unit and Milan Center for Neuroscience, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
| | - Paola Alberti
- Experimental Neurology Unit and Milan Center for Neuroscience, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
| | - Elisa Ballarini
- Experimental Neurology Unit and Milan Center for Neuroscience, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
| | - Norberto Oggioni
- Experimental Neurology Unit and Milan Center for Neuroscience, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
| | - Louise Carlson
- Department of Immunology, Roswell Park Comprehensive Cancer Center, University at Buffalo, The State University of New York, Buffalo, NY, United States
| | - Wensheng Liu
- Department of Immunology, Roswell Park Comprehensive Cancer Center, University at Buffalo, The State University of New York, Buffalo, NY, United States
| | - Mehrnoosh Ghandili
- Department of Pathology and Anatomical Sciences, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, United States
| | - Tracey A. Ignatowski
- Department of Pathology and Anatomical Sciences, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, United States
| | - Kelvin P. Lee
- Department of Immunology, Roswell Park Comprehensive Cancer Center, University at Buffalo, The State University of New York, Buffalo, NY, United States
| | - Michael J. Moore
- Department of Biomedical Engineering, School of Science and Engineering, Tulane University, New Orleans, LA, United States
- AxoSim, Inc., New Orleans, LA, United States
| | - Guido Cavaletti
- Experimental Neurology Unit and Milan Center for Neuroscience, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
- *Correspondence: Guido Cavaletti, ; Donald E. Mager,
| | - Donald E. Mager
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, United States
- Enhanced Pharmacodynamics, LLC, Buffalo, NY, United States
- *Correspondence: Guido Cavaletti, ; Donald E. Mager,
| |
Collapse
|
6
|
Jones MR, Urits I, Wolf J, Corrigan D, Colburn L, Peterson E, Williamson A, Viswanath O. Drug-Induced Peripheral Neuropathy: A Narrative Review. ACTA ACUST UNITED AC 2021; 15:38-48. [PMID: 30666914 PMCID: PMC7365998 DOI: 10.2174/1574884714666190121154813] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Revised: 12/03/2018] [Accepted: 01/11/2019] [Indexed: 11/22/2022]
Abstract
Background Peripheral neuropathy is a painful condition deriving from many and varied etiologies. Certain medications have been implicated in the iatrogenic development of Drug Induced Peripheral Neuropathy (DIPN) and include chemotherapeutic agents, antimicrobials, cardiovascular drugs, psychotropic, anticonvulsants, among others. This review synthesizes current clinical concepts regarding the mechanism, common inciting medications, and treatment options for drug-induced peripheral neuropathy. Methods The authors undertook a structured search of bibliographic databases for peer-reviewed research literature using a focused review question and inclusion/exclusion criteria. The most relevant and up to date research was included. Results Drug-induced peripheral neuropathy is a common and painful condition caused by many different and frequently prescribed medications. Most often, DIPN is seen in chemotherapeutic agents, antimicrobials, cardiovascular drugs, psychotropic, and anticonvulsant drugs. Certain drugs exhibit more consistent neuropathic side effects, such as the chemotherapeutic compounds, but others are more commonly prescribed by a larger proportion of providers, such as the statins. DIPN is more likely to occur in patients with concomitant risk factors such as preexisting neuropathy, diabetes, and associated genetically predisposing diseases. DIPN is often difficult to treat, however medications including duloxetine, and gabapentin are shown to reduce neuropathic pain. Advanced techniques of neuromodulation offer promise though further randomized and controlled studies are needed to confirm efficacy. Conclusion Awareness of the drugs covered in this review and their potential for adverse neuropathic effect is important for providers caring for patients who report new onset symptoms of pain, paresthesia, or weakness. Prevention of DIPN is especially important because treatment often proves challenging. While many pharmacologic therapies have demonstrated analgesic potential in the pain caused by DIPN, many patients remain refractive to treatment. More studies are needed to elucidate the effectiveness of interventional, neuromodulating therapies.
Collapse
Affiliation(s)
- Mark R Jones
- Harvard Medical School, Beth Israel Deaconess Medical Center, Department of Anesthesia, Critical Care, and Pain Medicine, Boston, MA, 02118, United States
| | - Ivan Urits
- Harvard Medical School, Beth Israel Deaconess Medical Center, Department of Anesthesia, Critical Care, and Pain Medicine, Boston, MA, 02118, United States
| | - John Wolf
- Creighton University School of Medicine-Phoenix Regional Campus, St. Joseph's Hospital and Medical Center, Phoenix, AZ 85013, United States
| | - Devin Corrigan
- Creighton University School of Medicine-Phoenix Regional Campus, St. Joseph's Hospital and Medical Center, Phoenix, AZ 85013, United States
| | - Luc Colburn
- Creighton University School of Medicine-Phoenix Regional Campus, St. Joseph's Hospital and Medical Center, Phoenix, AZ 85013, United States
| | - Emily Peterson
- Creighton University School of Medicine-Phoenix Regional Campus, St. Joseph's Hospital and Medical Center, Phoenix, AZ 85013, United States
| | - Amber Williamson
- Creighton University School of Medicine-Phoenix Regional Campus, St. Joseph's Hospital and Medical Center, Phoenix, AZ 85013, United States
| | - Omar Viswanath
- Valley Anesthesiology and Pain Consultants, Phoenix, AZ, University of Arizona College of Medicine-Phoenix, Phoenix, AZ, Creighton University School of Medicine, Omaha, NE, United States
| |
Collapse
|
7
|
Kober KM, Lee MC, Olshen A, Conley YP, Sirota M, Keiser M, Hammer MJ, Abrams G, Schumacher M, Levine JD, Miaskowski C. Differential methylation and expression of genes in the hypoxia-inducible factor 1 signaling pathway are associated with paclitaxel-induced peripheral neuropathy in breast cancer survivors and with preclinical models of chemotherapy-induced neuropathic pain. Mol Pain 2020; 16:1744806920936502. [PMID: 32586194 PMCID: PMC7322824 DOI: 10.1177/1744806920936502] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 05/26/2020] [Accepted: 06/01/2020] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Paclitaxel is an important chemotherapeutic agent for the treatment of breast cancer. Paclitaxel-induced peripheral neuropathy (PIPN) is a major dose-limiting toxicity that can persist into survivorship. While not all survivors develop PIPN, for those who do, it has a substantial negative impact on their functional status and quality of life. No interventions are available to treat PIPN. In our previous studies, we identified that the HIF-1 signaling pathway (H1SP) was perturbed between breast cancer survivors with and without PIPN. Preclinical studies suggest that the H1SP is involved in the development of bortezomib-induced and diabetic peripheral neuropathy, and sciatic nerve injury. The purpose of this study was to identify H1SP genes that have both differential methylation and differential gene expression between breast cancer survivors with and without PIPN. METHODS A multi-staged integrated analysis was performed. In peripheral blood, methylation was assayed using microarray and gene expression was assayed using RNA-seq. Candidate genes in the H1SP having both differentially methylation and differential expression were identified between survivors who received paclitaxel and did (n = 25) and did not (n = 25) develop PIPN. Then, candidate genes were evaluated for differential methylation and differential expression in public data sets of preclinical models of PIPN and sciatic nerve injury. RESULTS Eight candidate genes were identified as both differential methylation and differential expression in survivors. Of the eight homologs identified, one was found to be differential expression in both PIPN and "normal" mice dorsal root ganglia; three were differential methylation in sciatic nerve injury versus sham rats in both pre-frontal cortex and T-cells; and two were differential methylation in sciatic nerve injury versus sham rats in the pre-frontal cortex. CONCLUSIONS This study is the first to evaluate for methylation in cancer survivors with chronic PIPN. The findings provide evidence that the expression of H1SP genes associated with chronic PIPN in cancer survivors may be regulated by epigenetic mechanisms and suggests genes for validation as potential therapeutic targets.
Collapse
Affiliation(s)
- Kord M Kober
- School of Nursing, University of
California, San Francisco, CA, USA
- Helen Diller Family Comprehensive
Cancer Center, University of California, San Francisco, CA, USA
- Bakar Computational Health Sciences
Institute, University of California, San Francisco, CA, USA
| | - Man-Cheung Lee
- School of Medicine, University of
California, San Francisco, CA, USA
| | - Adam Olshen
- Helen Diller Family Comprehensive
Cancer Center, University of California, San Francisco, CA, USA
- Department of Epidemiology and
Biostatistics, University of California, San Francisco, CA, USA
| | - Yvette P Conley
- School of Nursing,
University
of Pittsburgh, Pittsburgh, PA, USA
| | - Marina Sirota
- Bakar Computational Health Sciences
Institute, University of California, San Francisco, CA, USA
- School of Medicine, University of
California, San Francisco, CA, USA
| | - Michael Keiser
- Bakar Computational Health Sciences
Institute, University of California, San Francisco, CA, USA
- School of Medicine, University of
California, San Francisco, CA, USA
- Institute for Neurodegenerative
Diseases, University of California, San Francisco, CA, USA
| | - Marilyn J Hammer
- Phyllis F. Cantor Center,
Dana-Farber Cancer Institute, Boston, MA, USA
| | - Gary Abrams
- School of Medicine, University of
California, San Francisco, CA, USA
| | - Mark Schumacher
- School of Medicine, University of
California, San Francisco, CA, USA
| | - Jon D Levine
- School of Medicine, University of
California, San Francisco, CA, USA
| | - Christine Miaskowski
- School of Nursing, University of
California, San Francisco, CA, USA
- Helen Diller Family Comprehensive
Cancer Center, University of California, San Francisco, CA, USA
| |
Collapse
|
8
|
Geerts H, Wikswo J, van der Graaf PH, Bai JPF, Gaiteri C, Bennett D, Swalley SE, Schuck E, Kaddurah-Daouk R, Tsaioun K, Pelleymounter M. Quantitative Systems Pharmacology for Neuroscience Drug Discovery and Development: Current Status, Opportunities, and Challenges. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2019; 9:5-20. [PMID: 31674729 PMCID: PMC6966183 DOI: 10.1002/psp4.12478] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/11/2019] [Accepted: 10/09/2019] [Indexed: 12/18/2022]
Abstract
The substantial progress made in the basic sciences of the brain has yet to be adequately translated to successful clinical therapeutics to treat central nervous system (CNS) diseases. Possible explanations include the lack of quantitative and validated biomarkers, the subjective nature of many clinical endpoints, and complex pharmacokinetic/pharmacodynamic relationships, but also the possibility that highly selective drugs in the CNS do not reflect the complex interactions of different brain circuits. Although computational systems pharmacology modeling designed to capture essential components of complex biological systems has been increasingly accepted in pharmaceutical research and development for oncology, inflammation, and metabolic disorders, the uptake in the CNS field has been very modest. In this article, a cross-disciplinary group with representatives from academia, pharma, regulatory, and funding agencies make the case that the identification and exploitation of CNS therapeutic targets for drug discovery and development can benefit greatly from a system and network approach that can span the gap between molecular pathways and the neuronal circuits that ultimately regulate brain activity and behavior. The National Institute of Neurological Disorders and Stroke (NINDS), in collaboration with the National Institute on Aging (NIA), National Institute of Mental Health (NIMH), National Institute on Drug Abuse (NIDA), and National Center for Advancing Translational Sciences (NCATS), convened a workshop to explore and evaluate the potential of a quantitative systems pharmacology (QSP) approach to CNS drug discovery and development. The objective of the workshop was to identify the challenges and opportunities of QSP as an approach to accelerate drug discovery and development in the field of CNS disorders. In particular, the workshop examined the potential for computational neuroscience to perform QSP-based interrogation of the mechanism of action for CNS diseases, along with a more accurate and comprehensive method for evaluating drug effects and optimizing the design of clinical trials. Following up on an earlier white paper on the use of QSP in general disease mechanism of action and drug discovery, this report focuses on new applications, opportunities, and the accompanying limitations of QSP as an approach to drug development in the CNS therapeutic area based on the discussions in the workshop with various stakeholders.
Collapse
Affiliation(s)
- Hugo Geerts
- In Silico Biosciences, Berwyn, Pennsylvania, USA
| | - John Wikswo
- Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt University, Nashville, Tennessee, USA
| | | | - Jane P F Bai
- Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Chris Gaiteri
- Rush Alzheimer's Disease Center, Rush University, Chicago, Illinois, USA
| | - David Bennett
- Rush Alzheimer's Disease Center, Rush University, Chicago, Illinois, USA
| | | | | | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, North Carolina, USA
| | - Katya Tsaioun
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Mary Pelleymounter
- Division of Translational Research, National Institute of Neurological Disorders and Stroke, Bethesda, Maryland, USA
| |
Collapse
|
9
|
de Anda‐Jáuregui G, McGregor BA, Guo K, Hur J. A Network Pharmacology Approach for the Identification of Common Mechanisms of Drug-Induced Peripheral Neuropathy. CPT Pharmacometrics Syst Pharmacol 2019; 8:211-219. [PMID: 30762308 PMCID: PMC6482281 DOI: 10.1002/psp4.12383] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2018] [Accepted: 12/27/2018] [Indexed: 01/06/2023] Open
Abstract
Drug-induced peripheral neuropathy is a side effect of a variety of therapeutic agents that can affect therapeutic adherence and lead to regimen modifications, impacting patient quality of life. The molecular mechanisms involved in the development of this condition have yet to be completely described in the literature. We used a computational network pharmacology approach to explore the Connectivity Map, a large collection of transcriptional profiles from drug perturbation experiments to identify common genes affected by peripheral neuropathy-inducing drugs. Consensus profiles for 98 of these drugs were used to construct a drug-gene perturbation network. We identified 27 genes significantly associated with neuropathy-inducing drugs. These genes may have a potential role in the action of neuropathy-inducing drugs. Our results suggest that molecular mechanisms, including alterations in mitochondrial function, microtubule and cytoskeleton function, ion channels, transcriptional regulation including epigenetic mechanisms, signal transduction, and wound healing, may play a critical role in drug-induced peripheral neuropathy.
Collapse
Affiliation(s)
- Guillermo de Anda‐Jáuregui
- Department of Biomedical SciencesSchool of Medicine & Health SciencesUniversity of North DakotaGrand ForksNorth DakotaUSA
- Present address:
Computational Genomics DivisionNational Institute of Genomic MedicineColonia Arenal TepepanDelegación TlalpanMéxico DFMexico
| | - Brett A. McGregor
- Department of Biomedical SciencesSchool of Medicine & Health SciencesUniversity of North DakotaGrand ForksNorth DakotaUSA
| | - Kai Guo
- Department of Biomedical SciencesSchool of Medicine & Health SciencesUniversity of North DakotaGrand ForksNorth DakotaUSA
| | - Junguk Hur
- Department of Biomedical SciencesSchool of Medicine & Health SciencesUniversity of North DakotaGrand ForksNorth DakotaUSA
| |
Collapse
|
10
|
Machine Learning Models for the Prediction of Chemotherapy-Induced Peripheral Neuropathy. Pharm Res 2019; 36:35. [DOI: 10.1007/s11095-018-2562-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2018] [Accepted: 12/17/2018] [Indexed: 01/01/2023]
|
11
|
Wilson JL, Racz R, Liu T, Adeniyi O, Sun J, Ramamoorthy A, Pacanowski M, Altman R. PathFX provides mechanistic insights into drug efficacy and safety for regulatory review and therapeutic development. PLoS Comput Biol 2018; 14:e1006614. [PMID: 30532240 PMCID: PMC6285459 DOI: 10.1371/journal.pcbi.1006614] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Accepted: 10/31/2018] [Indexed: 12/14/2022] Open
Abstract
Failure to demonstrate efficacy and safety issues are important reasons that drugs do not reach the market. An incomplete understanding of how drugs exert their effects hinders regulatory and pharmaceutical industry projections of a drug's benefits and risks. Signaling pathways mediate drug response and while many signaling molecules have been characterized for their contribution to disease or their role in drug side effects, our knowledge of these pathways is incomplete. To better understand all signaling molecules involved in drug response and the phenotype associations of these molecules, we created a novel method, PathFX, a non-commercial entity, to identify these pathways and drug-related phenotypes. We benchmarked PathFX by identifying drugs' marketed disease indications and reported a sensitivity of 41%, a 2.7-fold improvement over similar approaches. We then used PathFX to strengthen signals for drug-adverse event pairs occurring in the FDA Adverse Event Reporting System (FAERS) and also identified opportunities for drug repurposing for new diseases based on interaction paths that associated a marketed drug to that disease. By discovering molecular interaction pathways, PathFX improved our understanding of drug associations to safety and efficacy phenotypes. The algorithm may provide a new means to improve regulatory and therapeutic development decisions.
Collapse
Affiliation(s)
- Jennifer L. Wilson
- Department of Bioengineering, Stanford University, Palo Alto California, United States of America
| | - Rebecca Racz
- Division of Applied Regulatory Science, US Food and Drug Administration, Silver Spring Maryland, United States of America
| | - Tianyun Liu
- Department of Bioengineering, Stanford University, Palo Alto California, United States of America
| | - Oluseyi Adeniyi
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring Maryland, United States of America
| | - Jielin Sun
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring Maryland, United States of America
| | - Anuradha Ramamoorthy
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring Maryland, United States of America
| | - Michael Pacanowski
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring Maryland, United States of America
| | - Russ Altman
- Department of Bioengineering, Stanford University, Palo Alto California, United States of America
- Department of Genetics, Stanford University, Palo Alto California, United States of America
| |
Collapse
|
12
|
Wilson JL. A scientist engineer's contribution to therapeutic discovery and development. Exp Biol Med (Maywood) 2018; 243:1125-1132. [PMID: 30458646 PMCID: PMC6327370 DOI: 10.1177/1535370218813974] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
An engineering perspective views cells as complex circuits that process inputs – drugs, environmental cues – to create complex outcomes – disease, growth, death – and this perspective has immense potential for drug development. Logical rules can describe the features of cells and reductionist approaches have exploited these rules for drug development. In contrast, the reductionist approach serially characterizes cellular components and develops a deep understanding of each component’s specific role. This approach underutilizes the full system of biomolecules relevant to disease pathology and drug effects. An engineering perspective provides the tools to understand and leverage the full extent of biological systems; applying both reverse and forward engineering, a strength of the engineering approach has demonstrated progress in advancing understanding of disease and drug mechanisms. Drug development lacks sufficient engineering specifications, or empirical models, of drug pharmacodynamic effects and future efforts to derive empirical models of drug effects will streamline this development. At this stage of progress, the scientist engineer is uniquely poised to solve problems in therapeutics related to modulating multiple diseases with a single or multiple therapeutic agents and identifying pharmacodynamics biomarkers with knowledge of drug pathways. This article underscores the value of these principles in an age where drug development costs are soaring and finding efficacious therapies is challenging.
Collapse
Affiliation(s)
- Jennifer L Wilson
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| |
Collapse
|
13
|
Hur J, Özgür A, He Y. Ontology-based literature mining and class effect analysis of adverse drug reactions associated with neuropathy-inducing drugs. J Biomed Semantics 2018; 9:17. [PMID: 29880031 PMCID: PMC5991464 DOI: 10.1186/s13326-018-0185-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2018] [Accepted: 05/18/2018] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Adverse drug reactions (ADRs), also called as drug adverse events (AEs), are reported in the FDA drug labels; however, it is a big challenge to properly retrieve and analyze the ADRs and their potential relationships from textual data. Previously, we identified and ontologically modeled over 240 drugs that can induce peripheral neuropathy through mining public drug-related databases and drug labels. However, the ADR mechanisms of these drugs are still unclear. In this study, we aimed to develop an ontology-based literature mining system to identify ADRs from drug labels and to elucidate potential mechanisms of the neuropathy-inducing drugs (NIDs). RESULTS We developed and applied an ontology-based SciMiner literature mining strategy to mine ADRs from the drug labels provided in the Text Analysis Conference (TAC) 2017, which included drug labels for 53 neuropathy-inducing drugs (NIDs). We identified an average of 243 ADRs per NID and constructed an ADR-ADR network, which consists of 29 ADR nodes and 149 edges, including only those ADR-ADR pairs found in at least 50% of NIDs. Comparison to the ADR-ADR network of non-NIDs revealed that the ADRs such as pruritus, pyrexia, thrombocytopenia, nervousness, asthenia, acute lymphocytic leukaemia were highly enriched in the NID network. Our ChEBI-based ontology analysis identified three benzimidazole NIDs (i.e., lansoprazole, omeprazole, and pantoprazole), which were associated with 43 ADRs. Based on ontology-based drug class effect definition, the benzimidazole drug group has a drug class effect on all of these 43 ADRs. Many of these 43 ADRs also exist in the enriched NID ADR network. Our Ontology of Adverse Events (OAE) classification further found that these 43 benzimidazole-related ADRs were distributed in many systems, primarily in behavioral and neurological, digestive, skin, and immune systems. CONCLUSIONS Our study demonstrates that ontology-based literature mining and network analysis can efficiently identify and study specific group of drugs and their associated ADRs. Furthermore, our analysis of drug class effects identified 3 benzimidazole drugs sharing 43 ADRs, leading to new hypothesis generation and possible mechanism understanding of drug-induced peripheral neuropathy.
Collapse
Affiliation(s)
- Junguk Hur
- Department of Department of Biomedical Sciences, University of North Dakota School of Medicine and Health Sciences, Grand Forks, ND, 58202, USA.
| | - Arzucan Özgür
- Department of Computer Engineering, Bogazici University, 34342, Istanbul, Turkey
| | - Yongqun He
- Unit for Laboratory Animal Medicine, Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA. .,Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA. .,Center for Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, 48109, USA. .,Comprehensive Cancer Center, University of Michigan Medical School, Ann Arbor, MI, 48109, USA.
| |
Collapse
|
14
|
de Anda-Jáuregui G, Guo K, McGregor BA, Hur J. Exploration of the Anti-Inflammatory Drug Space Through Network Pharmacology: Applications for Drug Repurposing. Front Physiol 2018; 9:151. [PMID: 29545755 PMCID: PMC5838628 DOI: 10.3389/fphys.2018.00151] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2017] [Accepted: 02/13/2018] [Indexed: 12/16/2022] Open
Abstract
The quintessential biological response to disease is inflammation. It is a driver and an important element in a wide range of pathological states. Pharmacological management of inflammation is therefore central in the clinical setting. Anti-inflammatory drugs modulate specific molecules involved in the inflammatory response; these drugs are traditionally classified as steroidal and non-steroidal drugs. However, the effects of these drugs are rarely limited to their canonical targets, affecting other molecules and altering biological functions with system-wide effects that can lead to the emergence of secondary therapeutic applications or adverse drug reactions (ADRs). In this study, relationships among anti-inflammatory drugs, functional pathways, and ADRs were explored through network models. We integrated structural drug information, experimental anti-inflammatory drug perturbation gene expression profiles obtained from the Connectivity Map and Library of Integrated Network-Based Cellular Signatures, functional pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome databases, as well as adverse reaction information from the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). The network models comprise nodes representing anti-inflammatory drugs, functional pathways, and adverse effects. We identified structural and gene perturbation similarities linking anti-inflammatory drugs. Functional pathways were connected to drugs by implementing Gene Set Enrichment Analysis (GSEA). Drugs and adverse effects were connected based on the proportional reporting ratio (PRR) of an adverse effect in response to a given drug. Through these network models, relationships among anti-inflammatory drugs, their functional effects at the pathway level, and their adverse effects were explored. These networks comprise 70 different anti-inflammatory drugs, 462 functional pathways, and 1,175 ADRs. Network-based properties, such as degree, clustering coefficient, and node strength, were used to identify new therapeutic applications within and beyond the anti-inflammatory context, as well as ADR risk for these drugs, helping to select better repurposing candidates. Based on these parameters, we identified naproxen, meloxicam, etodolac, tenoxicam, flufenamic acid, fenoprofen, and nabumetone as candidates for drug repurposing with lower ADR risk. This network-based analysis pipeline provides a novel way to explore the effects of drugs in a therapeutic space.
Collapse
Affiliation(s)
- Guillermo de Anda-Jáuregui
- Department of Biomedical Sciences, School of Medicine & Health Sciences, University of North Dakota, Grand Forks, ND, United States
| | - Kai Guo
- Department of Biomedical Sciences, School of Medicine & Health Sciences, University of North Dakota, Grand Forks, ND, United States
| | - Brett A McGregor
- Department of Biomedical Sciences, School of Medicine & Health Sciences, University of North Dakota, Grand Forks, ND, United States
| | - Junguk Hur
- Department of Biomedical Sciences, School of Medicine & Health Sciences, University of North Dakota, Grand Forks, ND, United States
| |
Collapse
|
15
|
Wilson JL, Altman RB. Biomarkers: Delivering on the expectation of molecularly driven, quantitative health. Exp Biol Med (Maywood) 2018; 243:313-322. [PMID: 29199461 PMCID: PMC5813871 DOI: 10.1177/1535370217744775] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Biomarkers are the pillars of precision medicine and are delivering on expectations of molecular, quantitative health. These features have made clinical decisions more precise and personalized, but require a high bar for validation. Biomarkers have improved health outcomes in a few areas such as cancer, pharmacogenetics, and safety. Burgeoning big data research infrastructure, the internet of things, and increased patient participation will accelerate discovery in the many areas that have not yet realized the full potential of biomarkers for precision health. Here we review themes of biomarker discovery, current implementations of biomarkers for precision health, and future opportunities and challenges for biomarker discovery. Impact statement Precision medicine evolved because of the understanding that human disease is molecularly driven and is highly variable across patients. This understanding has made biomarkers, a diverse class of biological measurements, more relevant for disease diagnosis, monitoring, and selection of treatment strategy. Biomarkers' impact on precision medicine can be seen in cancer, pharmacogenomics, and safety. The successes in these cases suggest many more applications for biomarkers and a greater impact for precision medicine across the spectrum of human disease. The authors assess the status of biomarker-guided medical practice by analyzing themes for biomarker discovery, reviewing the impact of these markers in the clinic, and highlight future and ongoing challenges for biomarker discovery. This work is timely and relevant, as the molecular, quantitative approach of precision medicine is spreading to many disease indications.
Collapse
Affiliation(s)
- Jennifer L Wilson
- Bioengineering Department, Stanford University, Stanford, CA 94305, USA
| | - Russ B Altman
- Bioengineering Department, Stanford University, Stanford, CA 94305, USA
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| |
Collapse
|
16
|
Messinis DE, Melas IN, Hur J, Varshney N, Alexopoulos LG, Bai JPF. Translational systems pharmacology-based predictive assessment of drug-induced cardiomyopathy. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2018; 7:166-174. [PMID: 29341478 PMCID: PMC5869547 DOI: 10.1002/psp4.12272] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/05/2017] [Revised: 11/14/2017] [Accepted: 11/17/2017] [Indexed: 12/21/2022]
Abstract
Drug‐induced cardiomyopathy contributes to drug attrition. We compared two pipelines of predictive modeling: (1) applying elastic net (EN) to differentially expressed genes (DEGs) of drugs; (2) applying integer linear programming (ILP) to construct each drug's signaling pathway starting from its targets to downstream proteins, to transcription factors, and to its DEGs in human cardiomyocytes, and then subjecting the genes/proteins in the drugs' signaling networks to EN regression. We classified 31 drugs with availability of DEGs into 13 toxic and 18 nontoxic drugs based on a clinical cardiomyopathy incidence cutoff of 0.1%. The ILP‐augmented modeling increased prediction accuracy from 79% to 88% (sensitivity: 88%; specificity: 89%) under leave‐one‐out cross validation. The ILP‐constructed signaling networks of drugs were better predictors than DEGs. Per literature, the microRNAs that reportedly regulate expression of our six top predictors are of diagnostic value for natural heart failure or doxorubicin‐induced cardiomyopathy. This translational predictive modeling might uncover potential biomarkers.
Collapse
Affiliation(s)
- Dimitris E Messinis
- Office of Clinical Pharmacology, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Ioannis N Melas
- Office of Clinical Pharmacology, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Junguk Hur
- Department of Biomedical Sciences, University of North Dakota, School of Medicine & Health Sciences, Grand Forks, North Dakota, USA
| | - Navya Varshney
- College of Pharmacy, University of Michigan, Ann Arbor, Michigan, USA
| | - Leonidas G Alexopoulos
- School of Mechanical Engineering, National Technical University of Athens, Zografou, Greece
| | - Jane P F Bai
- Office of Clinical Pharmacology, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| |
Collapse
|
17
|
Bai JPF, Melas IN, Hur J, Guo E. Advances in omics for informed pharmaceutical research and development in the era of systems medicine. Expert Opin Drug Discov 2017; 13:1-4. [PMID: 29073782 DOI: 10.1080/17460441.2018.1394839] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Affiliation(s)
- Jane P F Bai
- a Office of Clinical Pharmacology , Center for Drug Evaluation and Research, U.S. Food and Drug Administration , Silver Spring , Maryland , USA
| | | | - Junguk Hur
- c Department of Biomedical Sciences , University of North Dakota, School of Medicine & Health Sciences , Grand Forks , North Dakota , USA
| | - Ellen Guo
- d College of Pharmacy , University of Illinois at Chicago , Chicago , Illinois , USA
| |
Collapse
|
18
|
Bai JPF. Pharmacodynamics and Systems Pharmacology Approaches to Repurposing Drugs in the Wake of Global Health Burden. J Pharm Sci 2016; 105:3007-3012. [PMID: 27522921 PMCID: PMC7127093 DOI: 10.1016/j.xphs.2016.07.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2016] [Revised: 06/29/2016] [Accepted: 07/05/2016] [Indexed: 01/19/2023]
Abstract
There are emergent needs for cost-effective treatment worldwide, for which repurposing to develop a drug with existing marketing approval of disease(s) for new disease(s) is a valid option. Although strategic mining of electronic health records has produced real-world evidences to inform drug repurposing, using omics data (drug and disease), knowledge base of protein interactions, and database of transcription factors have been explored. Structured integration of all the existing data under the framework of drug repurposing will facilitate decision making. The ability to foresee the need to integrate new data types produced by emergent technologies and to enable data connectivity in the context of human biology and targeted diseases, as well as to use the existing crucial quality data of all approved drugs will catapult the number of drugs being successfully repurposed. However, translational pharmacodynamics databases for modeling information across human biology in the context of host factors are lacking and are critically needed for drug repurposing to improve global public health, especially for the efforts to combat neglected tropic diseases as well as emergent infectious diseases such as Zika or Ebola virus.
Collapse
Affiliation(s)
- Jane P F Bai
- Office of Clinical Pharmacology, Center for Drug Research and Evaluation, U.S. Food and Drug Administration, Silver Spring, Maryland 20993.
| |
Collapse
|
19
|
Guo A, Racz R, Hur J, Lin Y, Xiang Z, Zhao L, Rinder J, Jiang G, Zhu Q, He Y. Ontology-based collection, representation and analysis of drug-associated neuropathy adverse events. J Biomed Semantics 2016; 7:29. [PMID: 27213033 PMCID: PMC4875649 DOI: 10.1186/s13326-016-0069-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2016] [Accepted: 04/28/2016] [Indexed: 01/22/2023] Open
Abstract
Background Neuropathy often occurs following drug treatment such as chemotherapy. Severe instances of neuropathy can result in cessation of life-saving chemotherapy treatment. Results To support data representation and analysis of drug-associated neuropathy adverse events (AEs), we developed the Ontology of Drug Neuropathy Adverse Events (ODNAE). ODNAE extends the Ontology of Adverse Events (OAE). Our combinatorial approach identified 215 US FDA-licensed small molecule drugs that induce signs and symptoms of various types of neuropathy. ODNAE imports related drugs from the Drug Ontology (DrON) with their chemical ingredients defined in ChEBI. ODNAE includes 139 drug mechanisms of action from NDF-RT and 186 biological processes represented in the Gene Ontology (GO). In total ODNAE contains 1579 terms. Our analysis of the ODNAE knowledge base shows neuropathy-inducing drugs classified under specific molecular entity groups, especially carbon, pnictogen, chalcogen, and heterocyclic compounds. The carbon drug group includes 127 organic chemical drugs. Thirty nine receptor agonist and antagonist terms were identified, including 4 pairs (31 drugs) of agonists and antagonists that share targets (e.g., adrenergic receptor, dopamine, serotonin, and sex hormone receptor). Many drugs regulate neurological system processes (e.g., negative regulation of dopamine or serotonin uptake). SPARQL scripts were used to query the ODNAE ontology knowledge base. Conclusions ODNAE is an effective platform for building a drug-induced neuropathy knowledge base and for analyzing the underlying mechanisms of drug-induced neuropathy. The ODNAE-based methods used in this study can also be extended to the representation and study of other categories of adverse events. Electronic supplementary material The online version of this article (doi:10.1186/s13326-016-0069-x) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Abra Guo
- University of Michigan Medical School, Ann Arbor, MI 48109 USA
| | - Rebecca Racz
- University of Michigan Medical School, Ann Arbor, MI 48109 USA
| | - Junguk Hur
- School of Medicine and Health Sciences, University of North Dakota, Grand Forks, ND 58203 USA
| | - Yu Lin
- University of Michigan Medical School, Ann Arbor, MI 48109 USA
| | - Zuoshuang Xiang
- University of Michigan Medical School, Ann Arbor, MI 48109 USA
| | - Lili Zhao
- University of Michigan Medical School, Ann Arbor, MI 48109 USA
| | - Jordan Rinder
- University of Michigan Medical School, Ann Arbor, MI 48109 USA
| | | | - Qian Zhu
- University of Maryland, Baltimore County, Baltimore, MD 21250 USA
| | - Yongqun He
- University of Michigan Medical School, Ann Arbor, MI 48109 USA ; Unit for Laboratory Animal Medicine, Department of Microbiology and Immunology, Center for Computational Medicine and Bioinformatics, and Comprehensive Cancer Center, University of Michigan Medical School, 1301 MSRB III, 1150 W. Medical Dr., Ann Arbor, MI 48109 USA
| |
Collapse
|
20
|
Sakellaropoulos T, Herod TJ, Alexopoulos LG, Bai JPF. Computed Biological Relations among Five Select Treatment-Related Organ/Tissue Toxicities. Chem Res Toxicol 2016; 29:914-23. [PMID: 27063352 DOI: 10.1021/acs.chemrestox.6b00060] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Drug toxicity presents a major challenge in drug development and patient care. We set to build upon previous works regarding select drug-induced toxicities to find common patterns in the mode of action of the drugs associated with these toxicities. In particular, we focused on five disparate organ toxicities, peripheral neuropathy (PN), rhabdomyolysis (RM), Stevens-Johnson syndrome/toxic epidermal necrosis (SJS/TEN), lung injury (LI), and heart contraction-related cardiotoxicity (CT), and identified biological commonalities between and among the toxicities in terms of pharmacological targets and nearest neighbors (indirect effects) using the hyper-geometric test and a distance metric of Spearman correlation. There were 20 significant protein targets associated with two toxicities and 0 protein targets associated with three or more toxicities. Per Spearman distance, PN was closest to SJS/TEN compared to other pairs, whereas the pairs involving RM were more different than others excluding RM. The significant targets associated with RM outnumbered those associated with every one of the other four toxicities. Enrichment analysis of drug targets that are expressed in corresponding organ/tissues determined proteins that should be avoided in drug discovery. The identified biological patterns emerging from the mode of action of these drugs are statistically associated with these serious toxicities and could potentially be used as predictors for new drug candidates. The predictive power and usefulness of these biological patterns will increase with the database of these five toxicities. Furthermore, extension of our approach to all severe adverse reactions will produce useful biological commonalities for reference in drug discovery and development.
Collapse
Affiliation(s)
- Theodore Sakellaropoulos
- Office of Clinical Pharmacology, Center for Drug Evaluation and Research, U.S. Food and Drug Administration , Silver Spring, Maryland 20993, United States
| | - Timothy J Herod
- Office of Clinical Pharmacology, Center for Drug Evaluation and Research, U.S. Food and Drug Administration , Silver Spring, Maryland 20993, United States
| | - Leonidas G Alexopoulos
- School of Mechanical Engineering, National Technical University of Athens , Athens, Greece
| | - Jane P F Bai
- Office of Clinical Pharmacology, Center for Drug Evaluation and Research, U.S. Food and Drug Administration , Silver Spring, Maryland 20993, United States
| |
Collapse
|
21
|
|