1
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Xia M, Varmazyad M, Pla-Palacín I, Gavlock DC, DeBiasio R, LaRocca G, Reese C, Florentino RM, Faccioli LAP, Brown JA, Vernetti LA, Schurdak M, Stern AM, Gough A, Behari J, Soto-Gutierrez A, Taylor DL, Miedel MT. Comparison of wild-type and high-risk PNPLA3 variants in a human biomimetic liver microphysiology system for metabolic dysfunction-associated steatotic liver disease precision therapy. Front Cell Dev Biol 2024; 12:1423936. [PMID: 39324073 PMCID: PMC11422722 DOI: 10.3389/fcell.2024.1423936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Accepted: 08/16/2024] [Indexed: 09/27/2024] Open
Abstract
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a worldwide health epidemic with a global occurrence of approximately 30%. The pathogenesis of MASLD is a complex, multisystem disorder driven by multiple factors, including genetics, lifestyle, and the environment. Patient heterogeneity presents challenges in developing MASLD therapeutics, creating patient cohorts for clinical trials, and optimizing therapeutic strategies for specific patient cohorts. Implementing pre-clinical experimental models for drug development creates a significant challenge as simple in vitro systems and animal models do not fully recapitulate critical steps in the pathogenesis and the complexity of MASLD progression. To address this, we implemented a precision medicine strategy that couples the use of our liver acinus microphysiology system (LAMPS) constructed with patient-derived primary cells. We investigated the MASLD-associated genetic variant patatin-like phospholipase domain-containing protein 3 (PNPLA3) rs738409 (I148M variant) in primary hepatocytes as it is associated with MASLD progression. We constructed the LAMPS with genotyped wild-type and variant PNPLA3 hepatocytes, together with key non-parenchymal cells, and quantified the reproducibility of the model. We altered media components to mimic blood chemistries, including insulin, glucose, free fatty acids, and immune-activating molecules to reflect normal fasting (NF), early metabolic syndrome (EMS), and late metabolic syndrome (LMS) conditions. Finally, we investigated the response to treatment with resmetirom, an approved drug for metabolic syndrome-associated steatohepatitis (MASH), the progressive form of MASLD. This study, using primary cells, serves as a benchmark for studies using "patient biomimetic twins" constructed with patient induced pluripotent stem cell (iPSC)-derived liver cells using a panel of reproducible metrics. We observed increased steatosis, immune activation, stellate cell activation, and secretion of pro-fibrotic markers in the PNPLA3 GG variant compared to the wild-type CC LAMPS, consistent with the clinical characterization of this variant. We also observed greater resmetirom efficacy in the PNPLA3 wild-type CC LAMPS compared to the GG variant in multiple MASLD metrics, including steatosis, stellate cell activation, and the secretion of pro-fibrotic markers. In conclusion, our study demonstrates the capability of the LAMPS platform for the development of MASLD precision therapeutics, enrichment of patient cohorts for clinical trials, and optimization of therapeutic strategies for patient subgroups with different clinical traits and disease stages.
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Affiliation(s)
- Mengying Xia
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA, United States
| | - Mahboubeh Varmazyad
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA, United States
| | - Iris Pla-Palacín
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA, United States
| | - Dillon C. Gavlock
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA, United States
| | - Richard DeBiasio
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA, United States
| | - Gregory LaRocca
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA, United States
| | - Celeste Reese
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA, United States
| | - Rodrigo M. Florentino
- Department of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- Center for Transcriptional Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA, United States
| | - Lanuza A. P. Faccioli
- Department of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- Center for Transcriptional Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA, United States
| | - Jacquelyn A. Brown
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Computational and System Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Lawrence A. Vernetti
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Computational and System Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Mark Schurdak
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA, United States
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Computational and System Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Andrew M. Stern
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Computational and System Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Albert Gough
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA, United States
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA, United States
| | - Jaideep Behari
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA, United States
- Division of Gastroenterology, Hepatology and Nutrition, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Alejandro Soto-Gutierrez
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- Center for Transcriptional Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA, United States
| | - D. Lansing Taylor
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA, United States
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Computational and System Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Mark T. Miedel
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA, United States
- Department of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA, United States
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2
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Cadavid JL, Li NT, McGuigan AP. Bridging systems biology and tissue engineering: Unleashing the full potential of complex 3D in vitro tissue models of disease. BIOPHYSICS REVIEWS 2024; 5:021301. [PMID: 38617201 PMCID: PMC11008916 DOI: 10.1063/5.0179125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 03/12/2024] [Indexed: 04/16/2024]
Abstract
Rapid advances in tissue engineering have resulted in more complex and physiologically relevant 3D in vitro tissue models with applications in fundamental biology and therapeutic development. However, the complexity provided by these models is often not leveraged fully due to the reductionist methods used to analyze them. Computational and mathematical models developed in the field of systems biology can address this issue. Yet, traditional systems biology has been mostly applied to simpler in vitro models with little physiological relevance and limited cellular complexity. Therefore, integrating these two inherently interdisciplinary fields can result in new insights and move both disciplines forward. In this review, we provide a systematic overview of how systems biology has been integrated with 3D in vitro tissue models and discuss key application areas where the synergies between both fields have led to important advances with potential translational impact. We then outline key directions for future research and discuss a framework for further integration between fields.
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Jeong S, Fuwad A, Yoon S, Jeon TJ, Kim SM. A Microphysiological Model to Mimic the Placental Remodeling during Early Stage of Pregnancy under Hypoxia-Induced Trophoblast Invasion. Biomimetics (Basel) 2024; 9:289. [PMID: 38786499 PMCID: PMC11118815 DOI: 10.3390/biomimetics9050289] [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: 03/18/2024] [Revised: 05/05/2024] [Accepted: 05/09/2024] [Indexed: 05/25/2024] Open
Abstract
Placental trophoblast invasion is critical for establishing the maternal-fetal interface, yet the mechanisms driving trophoblast-induced maternal arterial remodeling remain elusive. To address this gap, we developed a three-dimensional microfluidic placenta-on-chip model that mimics early pregnancy placentation in a hypoxic environment. By studying human umbilical vein endothelial cells (HUVECs) under oxygen-deprived conditions upon trophoblast invasion, we observed significant HUVEC artery remodeling, suggesting the critical role of hypoxia in placentation. In particular, we found that trophoblasts secrete matrix metalloproteinase (MMP) proteins under hypoxic conditions, which contribute to arterial remodeling by the degradation of extracellular matrix components. This MMP-mediated remodeling is critical for facilitating trophoblast invasion and proper establishment of the maternal-fetal interface. In addition, our platform allows real-time monitoring of HUVEC vessel contraction during trophoblast interaction, providing valuable insights into the dynamic interplay between trophoblasts and maternal vasculature. Collectively, our findings highlight the importance of MMP-mediated arterial remodeling in placental development and underscore the potential of our platform to study pregnancy-related complications and evaluate therapeutic interventions.
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Affiliation(s)
- Seorin Jeong
- Department of Mechanical Engineering, Inha University, 100, Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea; (S.J.); (A.F.)
| | - Ahmed Fuwad
- Department of Mechanical Engineering, Inha University, 100, Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea; (S.J.); (A.F.)
- Department of Biomedical Engineering, School of Mechanical & Manufacturing Engineering (SMME), National University of Science and Technology (NUST), Islamabad 44000, Pakistan
| | - Sunhee Yoon
- Department of Biological Sciences and Bioengineering, Inha University, 100, Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea;
| | - Tae-Joon Jeon
- Department of Biological Sciences and Bioengineering, Inha University, 100, Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea;
- Biohybrid Systems Research Center, Inha University, 100, Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea
- Department of Biological Engineering, Inha University, 100, Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea
| | - Sun Min Kim
- Department of Mechanical Engineering, Inha University, 100, Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea; (S.J.); (A.F.)
- Department of Biological Sciences and Bioengineering, Inha University, 100, Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea;
- Biohybrid Systems Research Center, Inha University, 100, Inha-ro, Michuhol-gu, Incheon 22212, Republic of Korea
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4
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Xia M, Varmazyad M, Palacin IP, Gavlock DC, Debiasio R, LaRocca G, Reese C, Florentino R, Faccioli LAP, Brown JA, Vernetti LA, Schurdak ME, Stern AM, Gough A, Behari J, Soto-Gutierrez A, Taylor DL, Miedel M. Comparison of Wild-Type and High-risk PNPLA3 variants in a Human Biomimetic Liver Microphysiology System for Metabolic Dysfunction-associated Steatotic Liver Disease Precision Therapy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.22.590608. [PMID: 38712213 PMCID: PMC11071381 DOI: 10.1101/2024.04.22.590608] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a worldwide health epidemic with a global occurrence of approximately 30%. The pathogenesis of MASLD is a complex, multisystem disorder driven by multiple factors including genetics, lifestyle, and the environment. Patient heterogeneity presents challenges for developing MASLD therapeutics, creation of patient cohorts for clinical trials and optimization of therapeutic strategies for specific patient cohorts. Implementing pre-clinical experimental models for drug development creates a significant challenge as simple in vitro systems and animal models do not fully recapitulate critical steps in the pathogenesis and the complexity of MASLD progression. To address this, we implemented a precision medicine strategy that couples the use of our liver acinus microphysiology system (LAMPS) constructed with patient-derived primary cells. We investigated the MASLD-associated genetic variant PNPLA3 rs738409 (I148M variant) in primary hepatocytes, as it is associated with MASLD progression. We constructed LAMPS with genotyped wild type and variant PNPLA3 hepatocytes together with key non-parenchymal cells and quantified the reproducibility of the model. We altered media components to mimic blood chemistries, including insulin, glucose, free fatty acids, and immune activating molecules to reflect normal fasting (NF), early metabolic syndrome (EMS) and late metabolic syndrome (LMS) conditions. Finally, we investigated the response to treatment with resmetirom, an approved drug for metabolic syndrome-associated steatohepatitis (MASH), the progressive form of MASLD. This study using primary cells serves as a benchmark for studies using patient biomimetic twins constructed with patient iPSC-derived liver cells using a panel of reproducible metrics. We observed increased steatosis, immune activation, stellate cell activation and secretion of pro-fibrotic markers in the PNPLA3 GG variant compared to wild type CC LAMPS, consistent with the clinical characterization of this variant. We also observed greater resmetirom efficacy in PNPLA3 wild type CC LAMPS compared to the GG variant in multiple MASLD metrics including steatosis, stellate cell activation and the secretion of pro-fibrotic markers. In conclusion, our study demonstrates the capability of the LAMPS platform for the development of MASLD precision therapeutics, enrichment of patient cohorts for clinical trials, and optimization of therapeutic strategies for patient subgroups with different clinical traits and disease stages.
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5
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Lim AY, Kato Y, Sakolish C, Valdiviezo A, Han G, Bajaj P, Stanko J, Ferguson SS, Villenave R, Hewitt P, Hardwick RN, Rusyn I. Reproducibility and Robustness of a Liver Microphysiological System PhysioMimix LC12 under Varying Culture Conditions and Cell Type Combinations. Bioengineering (Basel) 2023; 10:1195. [PMID: 37892925 PMCID: PMC10603899 DOI: 10.3390/bioengineering10101195] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 10/04/2023] [Accepted: 10/12/2023] [Indexed: 10/29/2023] Open
Abstract
The liver is one of the key organs for exogenous and endogenous metabolism and is often a target for drug- and chemical-driven toxicity. A wide range of experimental approaches has been established to model and characterize the mechanisms of drug- and chemical-induced hepatotoxicity. A number of microfluidics-enabled in vitro models of the liver have been developed, but the unclear translatability of these platforms has hindered their adoption by the pharmaceutical industry; to achieve wide use for drug and chemical safety evaluation, demonstration of reproducibility and robustness under various contexts of use is required. One of these commercially available platforms is the PhysioMimix LC12, a microfluidic device where cells are seeded into a 3D scaffold that is continuously perfused with recirculating cell culture media to mimic liver sinusoids. Previous studies demonstrated this model's functionality and potential applicability to preclinical drug development. However, to gain confidence in PhysioMimix LC12's robustness and reproducibility, supplementary characterization steps are needed, including the assessment of various human hepatocyte sources, contribution of non-parenchymal cells (NPCs), and comparison to other models. In this study, we performed replicate studies averaging 14 days with either primary human hepatocytes (PHHs) or induced pluripotent stem cell (iPSC)-derived hepatocytes, with and without NPCs. Albumin and urea secretion, lactate dehydrogenase, CYP3A4 activity, and metabolism were evaluated to assess basal function and metabolic capacity. Model performance was characterized by different cell combinations under intra- and inter-experimental replication and compared to multi-well plates and other liver platforms. PhysioMimix LC12 demonstrated the highest metabolic function with PHHs, with or without THP-1 or Kupffer cells, for up to 10-14 days. iPSC-derived hepatocytes and PHHs co-cultured with additional NPCs demonstrated sub-optimal performance. Power analyses based on replicate experiments and different contexts of use will inform future study designs due to the limited throughput and high cell demand. Overall, this study describes a workflow for independent testing of a complex microphysiological system for specific contexts of use, which may increase end-user adoption in drug development.
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Affiliation(s)
- Alicia Y. Lim
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX 77843, USA
| | - Yuki Kato
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX 77843, USA
- Laboratory for Drug Discovery and Development, Shionogi Pharmaceutical Research Center, Shionogi & Co., Ltd., Osaka 561-0825, Japan
| | - Courtney Sakolish
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX 77843, USA
| | - Alan Valdiviezo
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX 77843, USA
| | - Gang Han
- Department of Epidemiology and Biostatistics, Texas A&M University, College Station, TX 77843, USA
| | - Piyush Bajaj
- Global Investigative Toxicology, Preclinical Safety, Sanofi, Cambridge, MA 02141, USA
| | - Jason Stanko
- Division of Translational Toxicology, National Institute of Environmental Health Sciences, Durham, NC 27709, USA
| | - Stephen S. Ferguson
- Division of Translational Toxicology, National Institute of Environmental Health Sciences, Durham, NC 27709, USA
| | - Remi Villenave
- Roche Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., 4070 Basel, Switzerland
| | - Philip Hewitt
- Chemical and Preclinical Safety, Merck Healthcare KGaA, 64293 Darmstadt, Germany
| | - Rhiannon N. Hardwick
- Discovery Toxicology, Pharmaceutical Candidate Optimization, Bristol Myers Squibb, San Diego, CA 92121, USA
| | - Ivan Rusyn
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX 77843, USA
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6
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Beaudoin JJ, Clemens L, Miedel MT, Gough A, Zaidi F, Ramamoorthy P, Wong KE, Sarangarajan R, Battista C, Shoda LKM, Siler SQ, Taylor DL, Howell BA, Vernetti LA, Yang K. The Combination of a Human Biomimetic Liver Microphysiology System with BIOLOGXsym, a Quantitative Systems Toxicology (QST) Modeling Platform for Macromolecules, Provides Mechanistic Understanding of Tocilizumab- and GGF2-Induced Liver Injury. Int J Mol Sci 2023; 24:9692. [PMID: 37298645 PMCID: PMC10253699 DOI: 10.3390/ijms24119692] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 05/25/2023] [Accepted: 05/30/2023] [Indexed: 06/12/2023] Open
Abstract
Biologics address a range of unmet clinical needs, but the occurrence of biologics-induced liver injury remains a major challenge. Development of cimaglermin alfa (GGF2) was terminated due to transient elevations in serum aminotransferases and total bilirubin. Tocilizumab has been reported to induce transient aminotransferase elevations, requiring frequent monitoring. To evaluate the clinical risk of biologics-induced liver injury, a novel quantitative systems toxicology modeling platform, BIOLOGXsym™, representing relevant liver biochemistry and the mechanistic effects of biologics on liver pathophysiology, was developed in conjunction with clinically relevant data from a human biomimetic liver microphysiology system. Phenotypic and mechanistic toxicity data and metabolomics analysis from the Liver Acinus Microphysiology System showed that tocilizumab and GGF2 increased high mobility group box 1, indicating hepatic injury and stress. Tocilizumab exposure was associated with increased oxidative stress and extracellular/tissue remodeling, and GGF2 decreased bile acid secretion. BIOLOGXsym simulations, leveraging the in vivo exposure predicted by physiologically-based pharmacokinetic modeling and mechanistic toxicity data from the Liver Acinus Microphysiology System, reproduced the clinically observed liver signals of tocilizumab and GGF2, demonstrating that mechanistic toxicity data from microphysiology systems can be successfully integrated into a quantitative systems toxicology model to identify liabilities of biologics-induced liver injury and provide mechanistic insights into observed liver safety signals.
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Affiliation(s)
- James J. Beaudoin
- DILIsym Services Division, Simulations Plus Inc., Research Triangle Park, Durham, NC 27709, USA (S.Q.S.)
| | - Lara Clemens
- DILIsym Services Division, Simulations Plus Inc., Research Triangle Park, Durham, NC 27709, USA (S.Q.S.)
| | - Mark T. Miedel
- Department of Computational and Systems Biology, Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15219, USA (A.G.); (D.L.T.)
| | - Albert Gough
- Department of Computational and Systems Biology, Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15219, USA (A.G.); (D.L.T.)
| | - Fatima Zaidi
- Metabolon Inc., Durham, NC 27713, USA (P.R.); (K.E.W.); (R.S.)
| | | | - Kari E. Wong
- Metabolon Inc., Durham, NC 27713, USA (P.R.); (K.E.W.); (R.S.)
| | | | - Christina Battista
- DILIsym Services Division, Simulations Plus Inc., Research Triangle Park, Durham, NC 27709, USA (S.Q.S.)
| | - Lisl K. M. Shoda
- DILIsym Services Division, Simulations Plus Inc., Research Triangle Park, Durham, NC 27709, USA (S.Q.S.)
| | - Scott Q. Siler
- DILIsym Services Division, Simulations Plus Inc., Research Triangle Park, Durham, NC 27709, USA (S.Q.S.)
| | - D. Lansing Taylor
- Department of Computational and Systems Biology, Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15219, USA (A.G.); (D.L.T.)
| | - Brett A. Howell
- DILIsym Services Division, Simulations Plus Inc., Research Triangle Park, Durham, NC 27709, USA (S.Q.S.)
| | - Lawrence A. Vernetti
- Department of Computational and Systems Biology, Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15219, USA (A.G.); (D.L.T.)
| | - Kyunghee Yang
- DILIsym Services Division, Simulations Plus Inc., Research Triangle Park, Durham, NC 27709, USA (S.Q.S.)
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7
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Kato Y, Lim AY, Sakolish C, Valdiviezo A, Moyer HL, Hewitt P, Bajaj P, Han G, Rusyn I. Analysis of reproducibility and robustness of OrganoPlate® 2-lane 96, a liver microphysiological system for studies of pharmacokinetics and toxicological assessment of drugs. Toxicol In Vitro 2022; 85:105464. [PMID: 36057418 PMCID: PMC10015056 DOI: 10.1016/j.tiv.2022.105464] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Revised: 07/26/2022] [Accepted: 08/26/2022] [Indexed: 02/06/2023]
Abstract
Establishing the functionality, reproducibility, robustness, and reliability of microphysiological systems is a critical need for adoption of these technologies. A high throughput microphysiological system for liver studies was recently proposed in which induced pluripotent stem cell-derived hepatocytes (iHeps) and non-parenchymal cells (endothelial cells and THP-1 cells differentiated with phorbol 12-myristate 13-acetate into macrophage-like cells) were co-cultured in OrganoPlate® 2-lane 96 devices. The goal of this study was to evaluate this platform using additional cell types and conditions and characterize its utility and reproducibility. Primary human hepatocytes or iHeps, with and without non-parenchymal cells, were cultured for up to 17 days. Image-based cell viability, albumin and urea secretion into culture media, CYP3A4 activity and drug metabolism were assessed. The iHeps co-cultured with non-parenchymal cells demonstrated stable cell viability and function up to 17 days; however, variability was appreciable both within and among studies. The iHeps in monoculture did not form clusters and lost viability and function over time. The primary human hepatocytes in monoculture also exhibited low cell viability and hepatic function. Metabolism of various drugs was most efficient when iHeps were co-cultured with non-parenchymal cells. Overall, we found that the OrganoPlate® 2-lane 96 device, when used with iHeps and non-parenchymal cells, is a functional liver microphysiological model; however, the high-throughput nature of this model is somewhat dampened by the need for replicates to compensate for high variability.
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Affiliation(s)
- Yuki Kato
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX 77843, USA; Laboratory for Drug Discovery and Development, Shionogi Pharmaceutical Research Center, Shionogi & Co., Ltd., Osaka 561-0825, Japan
| | - Alicia Y Lim
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX 77843, USA
| | - Courtney Sakolish
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX 77843, USA
| | - Alan Valdiviezo
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX 77843, USA
| | - Haley L Moyer
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX 77843, USA
| | - Philip Hewitt
- Chemical and Preclinical Safety, Merck Healthcare KGaA, 64293 Darmstadt, Germany
| | - Piyush Bajaj
- Global Investigative Toxicology, Preclinical Safety, Sanofi USA, MA 01701, USA
| | - Gang Han
- Department of Epidemiology and Biostatistics, Texas A&M University, College Station, TX 77843, USA
| | - Ivan Rusyn
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, TX 77843, USA.
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8
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Lefever DE, Miedel MT, Pei F, DiStefano JK, Debiasio R, Shun TY, Saydmohammed M, Chikina M, Vernetti LA, Soto-Gutierrez A, Monga SP, Bataller R, Behari J, Yechoor VK, Bahar I, Gough A, Stern AM, Taylor DL. A Quantitative Systems Pharmacology Platform Reveals NAFLD Pathophysiological States and Targeting Strategies. Metabolites 2022; 12:528. [PMID: 35736460 PMCID: PMC9227696 DOI: 10.3390/metabo12060528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 05/28/2022] [Accepted: 06/03/2022] [Indexed: 11/17/2022] Open
Abstract
Non-alcoholic fatty liver disease (NAFLD) has a high global prevalence with a heterogeneous and complex pathophysiology that presents barriers to traditional targeted therapeutic approaches. We describe an integrated quantitative systems pharmacology (QSP) platform that comprehensively and unbiasedly defines disease states, in contrast to just individual genes or pathways, that promote NAFLD progression. The QSP platform can be used to predict drugs that normalize these disease states and experimentally test predictions in a human liver acinus microphysiology system (LAMPS) that recapitulates key aspects of NAFLD. Analysis of a 182 patient-derived hepatic RNA-sequencing dataset generated 12 gene signatures mirroring these states. Screening against the LINCS L1000 database led to the identification of drugs predicted to revert these signatures and corresponding disease states. A proof-of-concept study in LAMPS demonstrated mitigation of steatosis, inflammation, and fibrosis, especially with drug combinations. Mechanistically, several structurally diverse drugs were predicted to interact with a subnetwork of nuclear receptors, including pregnane X receptor (PXR; NR1I2), that has evolved to respond to both xenobiotic and endogenous ligands and is intrinsic to NAFLD-associated transcription dysregulation. In conjunction with iPSC-derived cells, this platform has the potential for developing personalized NAFLD therapeutic strategies, informing disease mechanisms, and defining optimal cohorts of patients for clinical trials.
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Affiliation(s)
- Daniel E. Lefever
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA; (D.E.L.); (M.T.M.); (R.D.); (T.Y.S.); (M.S.); (L.A.V.); (A.S.-G.); (S.P.M.); (V.K.Y.); (I.B.); (A.G.)
| | - Mark T. Miedel
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA; (D.E.L.); (M.T.M.); (R.D.); (T.Y.S.); (M.S.); (L.A.V.); (A.S.-G.); (S.P.M.); (V.K.Y.); (I.B.); (A.G.)
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA; (F.P.); (M.C.)
| | - Fen Pei
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA; (F.P.); (M.C.)
| | - Johanna K. DiStefano
- Diabetes and Fibrotic Disease Unit, Translational Genomics Research Institute TGen, Phoenix, AZ 85004, USA;
| | - Richard Debiasio
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA; (D.E.L.); (M.T.M.); (R.D.); (T.Y.S.); (M.S.); (L.A.V.); (A.S.-G.); (S.P.M.); (V.K.Y.); (I.B.); (A.G.)
| | - Tong Ying Shun
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA; (D.E.L.); (M.T.M.); (R.D.); (T.Y.S.); (M.S.); (L.A.V.); (A.S.-G.); (S.P.M.); (V.K.Y.); (I.B.); (A.G.)
| | - Manush Saydmohammed
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA; (D.E.L.); (M.T.M.); (R.D.); (T.Y.S.); (M.S.); (L.A.V.); (A.S.-G.); (S.P.M.); (V.K.Y.); (I.B.); (A.G.)
| | - Maria Chikina
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA; (F.P.); (M.C.)
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Lawrence A. Vernetti
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA; (D.E.L.); (M.T.M.); (R.D.); (T.Y.S.); (M.S.); (L.A.V.); (A.S.-G.); (S.P.M.); (V.K.Y.); (I.B.); (A.G.)
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA; (F.P.); (M.C.)
| | - Alejandro Soto-Gutierrez
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA; (D.E.L.); (M.T.M.); (R.D.); (T.Y.S.); (M.S.); (L.A.V.); (A.S.-G.); (S.P.M.); (V.K.Y.); (I.B.); (A.G.)
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA 15261, USA
- Department of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15261, USA
- McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15203, USA
| | - Satdarshan P. Monga
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA; (D.E.L.); (M.T.M.); (R.D.); (T.Y.S.); (M.S.); (L.A.V.); (A.S.-G.); (S.P.M.); (V.K.Y.); (I.B.); (A.G.)
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA 15261, USA
- Department of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Ramon Bataller
- Division of Gastroenterology Hepatology and Nutrition, Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15261, USA; (R.B.); (J.B.)
| | - Jaideep Behari
- Division of Gastroenterology Hepatology and Nutrition, Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15261, USA; (R.B.); (J.B.)
- UPMC Liver Clinic, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | - Vijay K. Yechoor
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA; (D.E.L.); (M.T.M.); (R.D.); (T.Y.S.); (M.S.); (L.A.V.); (A.S.-G.); (S.P.M.); (V.K.Y.); (I.B.); (A.G.)
- Division of Endocrinology and Metabolism, Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15203, USA
| | - Ivet Bahar
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA; (D.E.L.); (M.T.M.); (R.D.); (T.Y.S.); (M.S.); (L.A.V.); (A.S.-G.); (S.P.M.); (V.K.Y.); (I.B.); (A.G.)
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA; (F.P.); (M.C.)
| | - Albert Gough
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA; (D.E.L.); (M.T.M.); (R.D.); (T.Y.S.); (M.S.); (L.A.V.); (A.S.-G.); (S.P.M.); (V.K.Y.); (I.B.); (A.G.)
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA; (F.P.); (M.C.)
| | - Andrew M. Stern
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA; (D.E.L.); (M.T.M.); (R.D.); (T.Y.S.); (M.S.); (L.A.V.); (A.S.-G.); (S.P.M.); (V.K.Y.); (I.B.); (A.G.)
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA; (F.P.); (M.C.)
| | - D. Lansing Taylor
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA; (D.E.L.); (M.T.M.); (R.D.); (T.Y.S.); (M.S.); (L.A.V.); (A.S.-G.); (S.P.M.); (V.K.Y.); (I.B.); (A.G.)
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA; (F.P.); (M.C.)
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA 15261, USA
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9
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Saydmohammed M, Jha A, Mahajan V, Gavlock D, Shun TY, DeBiasio R, Lefever D, Li X, Reese C, Kershaw EE, Yechoor V, Behari J, Soto-Gutierrez A, Vernetti L, Stern A, Gough A, Miedel MT, Lansing Taylor D. Quantifying the progression of non-alcoholic fatty liver disease in human biomimetic liver microphysiology systems with fluorescent protein biosensors. Exp Biol Med (Maywood) 2021; 246:2420-2441. [PMID: 33957803 PMCID: PMC8606957 DOI: 10.1177/15353702211009228] [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: 12/30/2020] [Accepted: 03/23/2021] [Indexed: 12/12/2022] Open
Abstract
Metabolic syndrome is a complex disease that involves multiple organ systems including a critical role for the liver. Non-alcoholic fatty liver disease (NAFLD) is a key component of the metabolic syndrome and fatty liver is linked to a range of metabolic dysfunctions that occur in approximately 25% of the population. A panel of experts recently agreed that the acronym, NAFLD, did not properly characterize this heterogeneous disease given the associated metabolic abnormalities such as type 2 diabetes mellitus (T2D), obesity, and hypertension. Therefore, metabolic dysfunction-associated fatty liver disease (MAFLD) has been proposed as the new term to cover the heterogeneity identified in the NAFLD patient population. Although many rodent models of NAFLD/NASH have been developed, they do not recapitulate the full disease spectrum in patients. Therefore, a platform has evolved initially focused on human biomimetic liver microphysiology systems that integrates fluorescent protein biosensors along with other key metrics, the microphysiology systems database, and quantitative systems pharmacology. Quantitative systems pharmacology is being applied to investigate the mechanisms of NAFLD/MAFLD progression to select molecular targets for fluorescent protein biosensors, to integrate computational and experimental methods to predict drugs for repurposing, and to facilitate novel drug development. Fluorescent protein biosensors are critical components of the platform since they enable monitoring of the pathophysiology of disease progression by defining and quantifying the temporal and spatial dynamics of protein functions in the biosensor cells, and serve as minimally invasive biomarkers of the physiological state of the microphysiology system experimental disease models. Here, we summarize the progress in developing human microphysiology system disease models of NAFLD/MAFLD from several laboratories, developing fluorescent protein biosensors to monitor and to measure NAFLD/MAFLD disease progression and implementation of quantitative systems pharmacology with the goal of repurposing drugs and guiding the creation of novel therapeutics.
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Affiliation(s)
- Manush Saydmohammed
- University of Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Anupma Jha
- University of Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Vineet Mahajan
- University of Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Dillon Gavlock
- University of Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Tong Ying Shun
- University of Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Richard DeBiasio
- University of Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Daniel Lefever
- University of Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Xiang Li
- University of Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Celeste Reese
- University of Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Erin E Kershaw
- Department of Medicine, Division of Endocrinology and Metabolism, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Vijay Yechoor
- Department of Medicine, Division of Endocrinology and Metabolism, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Jaideep Behari
- Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, Pittsburgh, PA 15261, USA
- UPMC Liver Clinic, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Alejandro Soto-Gutierrez
- Department of Pathology, University of Pittsburgh, Pittsburgh, PA 15261, USA
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Larry Vernetti
- University of Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Andrew Stern
- University of Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Albert Gough
- University of Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Mark T Miedel
- University of Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - D Lansing Taylor
- University of Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15261, USA
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA 15261, USA
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15261, USA
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10
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Sakolish C, Luo YS, Valdiviezo A, Vernetti LA, Rusyn I, Chiu WA. Prediction of hepatic drug clearance with a human microfluidic four-cell liver acinus microphysiology system. Toxicology 2021; 463:152954. [PMID: 34543702 PMCID: PMC8585690 DOI: 10.1016/j.tox.2021.152954] [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: 08/06/2021] [Revised: 09/08/2021] [Accepted: 09/14/2021] [Indexed: 12/13/2022]
Abstract
Predicting human hepatic clearance remains a fundamental challenge in both pharmaceutical drug development and toxicological assessments of environmental chemicals, with concerns about both accuracy and precision of in vitro-derived estimates. Suggested sources of these issues have included differences in experimental protocols, differences in cell sourcing, and use of a single cell type, liver parenchymal cells (hepatocytes). Here we investigate the ability of human microfluidic four-cell liver acinus microphysiology system (LAMPS) to make predictions as to hepatic clearance for seven representative compounds: Caffeine, Pioglitazone, Rosiglitazone, Terfenadine, Tolcapone, Troglitazone, and Trovafloxacin. The model, whose reproducibility was recently confirmed in an inter-lab comparison, was constructed using primary human hepatocytes or human induced pluripotent stem cell (iPSC)-derived hepatocytes and 3 human cell lines for the endothelial, Kupffer and stellate cells. We calculated hepatic clearance estimates derived from experiments using LAMPS or traditional 2D cultures and compared the outcomes with both in vivo human clinical study-derived and in vitro human hepatocyte suspension culture-derived values reported in the literature. We found that, compared to in vivo clinically-derived values, the LAMPS model with iPSC-derived hepatocytes had higher precision as compared to primary cells in suspension or 2D culture, but, consistent with previous studies in other microphysiological systems, tended to underestimate in vivo clearance. Overall, these results suggest that use of LAMPS and iPSC-derived hepatocytes together with an empirical scaling factor warrants additional study with a larger set of compounds, as it has the potential to provide more accurate and precise estimates of hepatic clearance.
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Affiliation(s)
- Courtney Sakolish
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843, USA
| | - Yu-Syuan Luo
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843, USA; Institute of Food Safety and Health, National Taiwan University, Taipei 10617, Taiwan(1)
| | - Alan Valdiviezo
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843, USA
| | - Lawrence A Vernetti
- Drug Discovery Institute and Department of Computational & Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Ivan Rusyn
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843, USA
| | - Weihsueh A Chiu
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843, USA.
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11
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Grubb ML, Caliari SR. Fabrication approaches for high-throughput and biomimetic disease modeling. Acta Biomater 2021; 132:52-82. [PMID: 33716174 PMCID: PMC8433272 DOI: 10.1016/j.actbio.2021.03.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Revised: 02/15/2021] [Accepted: 03/02/2021] [Indexed: 12/24/2022]
Abstract
There is often a tradeoff between in vitro disease modeling platforms that capture pathophysiologic complexity and those that are amenable to high-throughput fabrication and analysis. However, this divide is closing through the application of a handful of fabrication approaches-parallel fabrication, automation, and flow-driven assembly-to design sophisticated cellular and biomaterial systems. The purpose of this review is to highlight methods for the fabrication of high-throughput biomaterial-based platforms and showcase examples that demonstrate their utility over a range of throughput and complexity. We conclude with a discussion of future considerations for the continued development of higher-throughput in vitro platforms that capture the appropriate level of biological complexity for the desired application. STATEMENT OF SIGNIFICANCE: There is a pressing need for new biomedical tools to study and understand disease. These platforms should mimic the complex properties of the body while also permitting investigation of many combinations of cells, extracellular cues, and/or therapeutics in high-throughput. This review summarizes emerging strategies to fabricate biomimetic disease models that bridge the gap between complex tissue-mimicking microenvironments and high-throughput screens for personalized medicine.
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Affiliation(s)
- Mackenzie L Grubb
- Department of Biomedical Engineering, University of Virginia, Unites States
| | - Steven R Caliari
- Department of Biomedical Engineering, University of Virginia, Unites States; Department of Chemical Engineering, University of Virginia, Unites States.
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12
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Clark AM, Allbritton NL, Wells A. Integrative microphysiological tissue systems of cancer metastasis to the liver. Semin Cancer Biol 2021; 71:157-169. [PMID: 32580025 PMCID: PMC7750290 DOI: 10.1016/j.semcancer.2020.06.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 06/10/2020] [Accepted: 06/10/2020] [Indexed: 02/07/2023]
Abstract
The liver is the most commonly involved organ in metastases from a wide variety of solid tumors. The use of biologically and cellularly complex liver tissue systems have shown that tumor cell behavior and therapeutic responses are modulated within the liver microenvironment and in ways distinct from the behaviors in the primary locations. These microphysiological systems have provided unexpected and powerful insights into the tumor cell biology of metastasis. However, neither the tumor nor the liver exist in an isolated tissue situation, having to function within a complete body and respond to systemic events as well as those in other organs. To examine the influence of one organ on the function of other tissues, microphysiological systems are being linked. Herein, we discuss extending this concept to tumor metastases by integrating complex models of the primary tumor with the liver metastatic environment. In addition, inflammatory organs and the immune system can be incorporated into these multi-organ systems to probe the effects on tumor behavior and cancer treatments.
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Affiliation(s)
- Amanda M Clark
- Department of Pathology, University of Pittsburgh, Pittsburgh, PA 15261, USA; VA Pittsburgh Healthcare System, Pittsburgh, PA 15213, USA; UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA 15213, USA.
| | - Nancy L Allbritton
- Department of Bioengineering, University of Washington, Seattle, WA 98195, USA
| | - Alan Wells
- Department of Pathology, University of Pittsburgh, Pittsburgh, PA 15261, USA; VA Pittsburgh Healthcare System, Pittsburgh, PA 15213, USA; UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15260, USA; Department of Computational & Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA
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13
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Gough A, Soto-Gutierrez A, Vernetti L, Ebrahimkhani MR, Stern AM, Taylor DL. Human biomimetic liver microphysiology systems in drug development and precision medicine. Nat Rev Gastroenterol Hepatol 2021; 18:252-268. [PMID: 33335282 PMCID: PMC9106093 DOI: 10.1038/s41575-020-00386-1] [Citation(s) in RCA: 61] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/02/2020] [Indexed: 02/07/2023]
Abstract
Microphysiology systems (MPS), also called organs-on-chips and tissue chips, are miniaturized functional units of organs constructed with multiple cell types under a variety of physical and biochemical environmental cues that complement animal models as part of a new paradigm of drug discovery and development. Biomimetic human liver MPS have evolved from simpler 2D cell models, spheroids and organoids to address the increasing need to understand patient-specific mechanisms of complex and rare diseases, the response to therapeutic treatments, and the absorption, distribution, metabolism, excretion and toxicity of potential therapeutics. The parallel development and application of transdisciplinary technologies, including microfluidic devices, bioprinting, engineered matrix materials, defined physiological and pathophysiological media, patient-derived primary cells, and pluripotent stem cells as well as synthetic biology to engineer cell genes and functions, have created the potential to produce patient-specific, biomimetic MPS for detailed mechanistic studies. It is projected that success in the development and maturation of patient-derived MPS with known genotypes and fully matured adult phenotypes will lead to advanced applications in precision medicine. In this Review, we examine human biomimetic liver MPS that are designed to recapitulate the liver acinus structure and functions to enhance our knowledge of the mechanisms of disease progression and of the absorption, distribution, metabolism, excretion and toxicity of therapeutic candidates and drugs as well as to evaluate their mechanisms of action and their application in precision medicine and preclinical trials.
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Affiliation(s)
- Albert Gough
- University of Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Alejandro Soto-Gutierrez
- University of Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Pathology, University of Pittsburgh, Pittsburgh, PA, USA
- McGowan Institute of Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lawrence Vernetti
- University of Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mo R Ebrahimkhani
- Department of Pathology, University of Pittsburgh, Pittsburgh, PA, USA
- McGowan Institute of Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Andrew M Stern
- University of Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - D Lansing Taylor
- University of Pittsburgh Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA.
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, PA, USA.
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14
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Analysis of reproducibility and robustness of a human microfluidic four-cell liver acinus microphysiology system (LAMPS). Toxicology 2020; 448:152651. [PMID: 33307106 DOI: 10.1016/j.tox.2020.152651] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 10/06/2020] [Accepted: 11/27/2020] [Indexed: 02/07/2023]
Abstract
A human microfluidic four-cell liver acinus microphysiology system (LAMPS), was evaluated for reproducibility and robustness as a model for drug pharmacokinetics and toxicology. The model was constructed using primary human hepatocytes or human induced pluripotent stem cell (iPSC)-derived hepatocytes and 3 human cell lines for the endothelial, Kupffer and stellate cells. The model was tested in two laboratories and demonstrated to be reproducible in terms of basal function of hepatocytes, Terfenadine metabolism, and effects of Tolcapone (88 μM), Troglitazone (150 μM), and caffeine (600 μM) over 9 days in culture. Additional experiments compared basal outputs of albumin, urea, lactate dehydrogenase (LDH) and tumor necrosis factor (TNF)α, as well as drug metabolism and toxicity in the LAMPS model, and in 2D cultures seeded with either primary hepatocytes or iPSC-hepatocytes. Further experiments to study the effects of Terfenadine (10 μM), Tolcapone (88 μM), Trovafloxacin (150 μM with or without 1 μg/mL lipopolysaccharide), Troglitazone (28 μM), Rosiglitazone (0.8 μM), Pioglitazone (3 μM), and caffeine (600 μM) were carried out over 10 days. We found that both primary human hepatocytes and iPSC-derived hepatocytes in 3D culture maintained excellent basal liver function and Terfenadine metabolism over 10 days compared the same cells in 2D cultures. In 2D, non-overlay monolayer cultures, both cell types lost hepatocyte phenotypes after 48 h. With respect to drug effects, both cell types demonstrated comparable and more human-relevant effects in LAMPS, as compared to 2D cultures. Overall, these studies show that LAMPS is a robust and reproducible in vitro liver model, comparable in performance when seeded with either primary human hepatocytes or iPSC-derived hepatocytes, and more physiologically and clinically relevant than 2D monolayer cultures.
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15
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Richardson L, Kim S, Menon R, Han A. Organ-On-Chip Technology: The Future of Feto-Maternal Interface Research? Front Physiol 2020; 11:715. [PMID: 32695021 PMCID: PMC7338764 DOI: 10.3389/fphys.2020.00715] [Citation(s) in RCA: 56] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Accepted: 05/29/2020] [Indexed: 12/17/2022] Open
Abstract
The placenta and fetal membrane act as a protective barrier throughout pregnancy while maintaining communication and nutrient exchange between the baby and the mother. Disruption of this barrier leads to various pregnancy complications, including preterm birth, which can have lasting negative consequences. Thus, understanding the role of the feto-maternal interface during pregnancy and parturition is vital to advancing basic and clinical research in the field of obstetrics. However, human subject studies are inherently difficult, and appropriate animal models are lacking. Due to these challenges, in vitro cell culture-based studies are most commonly utilized. However, the structure and functions of conventionally used in vitro 2D and 3D models are vastly different from the in vivo environment, making it difficult to fully understand the various factors affecting pregnancy as well as pathways and mechanisms contributing to term and preterm births. This limitation also makes it difficult to develop new therapeutics. The emergence of in vivo-like in vitro models such as organ-on-chip (OOC) platforms can better recapitulate in vivo functions and responses and has the potential to move this field forward significantly. OOC technology brings together two distinct fields, microfluidic engineering and cell/tissue biology, through which diverse human organ structures and functionalities can be built into a laboratory model that better mimics functions and responses of in vivo tissues and organs. In this review, we first provide an overview of the OOC technology, highlight two major designs commonly used in achieving multi-layer co-cultivation of cells, and introduce recently developed OOC models of the feto-maternal interface. As a vital component of this review, we aim to outline progress on the practicality and effectiveness of feto-maternal interface OOC (FM-OOC) models currently used and the advances they have fostered in obstetrics research. Lastly, we provide a perspective on the future basic research and clinical applications of FM-OOC models, and even those that integrate multiple organ systems into a single OOC system that may recreate intrauterine architecture in its entirety, which will accelerate our understanding of feto-maternal communication, induction of preterm labor, drug or toxicant permeability at this vital interface, and development of new therapeutic strategies.
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Affiliation(s)
- Lauren Richardson
- Division of Maternal-Fetal Medicine and Perinatal Research, Department of Obstetrics and Gynecology, The University of Texas Medical Branch at Galveston, Galveston, TX, United States.,Department of Electrical and Computer Engineering, College of Engineering, Texas A&M University, College Station, TX, United States.,Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX, United States
| | - Sungjin Kim
- Department of Electrical and Computer Engineering, College of Engineering, Texas A&M University, College Station, TX, United States.,Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX, United States
| | - Ramkumar Menon
- Division of Maternal-Fetal Medicine and Perinatal Research, Department of Obstetrics and Gynecology, The University of Texas Medical Branch at Galveston, Galveston, TX, United States
| | - Arum Han
- Department of Electrical and Computer Engineering, College of Engineering, Texas A&M University, College Station, TX, United States.,Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX, United States
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16
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Hawkins KG, Casolaro C, Brown JA, Edwards DA, Wikswo JP. The Microbiome and the Gut-Liver-Brain Axis for Central Nervous System Clinical Pharmacology: Challenges in Specifying and Integrating In Vitro and In Silico Models. Clin Pharmacol Ther 2020; 108:929-948. [PMID: 32347548 PMCID: PMC7572575 DOI: 10.1002/cpt.1870] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Accepted: 04/22/2020] [Indexed: 12/18/2022]
Abstract
The complexity of integrating microbiota into clinical pharmacology, environmental toxicology, and opioid studies arises from bidirectional and multiscale interactions between humans and their many microbiota, notably those of the gut. Hosts and each microbiota are governed by distinct central dogmas, with genetics influencing transcriptomics, proteomics, and metabolomics. Each microbiota's metabolome differentially modulates its own and the host's multi‐omics. Exogenous compounds (e.g., drugs and toxins), often affect host multi‐omics differently than microbiota multi‐omics, shifting the balance between drug efficacy and toxicity. The complexity of the host‐microbiota connection has been informed by current methods of in vitro bacterial cultures and in vivo mouse models, but they fail to elucidate mechanistic details. Together, in vitro organ‐on‐chip microphysiological models, multi‐omics, and in silico computational models have the potential to supplement the established methods to help clinical pharmacologists and environmental toxicologists unravel the myriad of connections between the gut microbiota and host health and disease.
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Affiliation(s)
- Kyle G Hawkins
- Department of Physics and Astronomy, Vanderbilt University, Nashville, Tennessee, USA
| | - Caleb Casolaro
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Jacquelyn A Brown
- Department of Physics and Astronomy, Vanderbilt University, Nashville, Tennessee, USA.,Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt University, Nashville, Tennessee, USA
| | - David A Edwards
- Department of Anesthesiology and Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - John P Wikswo
- Department of Physics and Astronomy, Vanderbilt University, Nashville, Tennessee, USA.,Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA.,Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt University, Nashville, Tennessee, USA.,Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee, USA
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17
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Schurdak M, Vernetti L, Bergenthal L, Wolter QK, Shun TY, Karcher S, Taylor DL, Gough A. Applications of the microphysiology systems database for experimental ADME-Tox and disease models. LAB ON A CHIP 2020; 20:1472-1492. [PMID: 32211684 PMCID: PMC7497411 DOI: 10.1039/c9lc01047e] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 01/07/2020] [Indexed: 05/04/2023]
Abstract
To accelerate the development and application of Microphysiological Systems (MPS) in biomedical research and drug discovery/development, a centralized resource is required to provide the detailed design, application, and performance data that enables industry and research scientists to select, optimize, and/or develop new MPS solutions, as well as to harness data from MPS models. We have previously implemented an open source Microphysiology Systems Database (MPS-Db), with a simple icon driven interface, as a resource for MPS researchers and drug discovery/development scientists (https://mps.csb.pitt.edu). The MPS-Db captures and aggregates data from MPS, ranging from static microplate models to integrated, multi-organ microfluidic models, and associates those data with reference data from chemical, biochemical, pre-clinical, clinical and post-marketing sources to support the design, development, validation, application and interpretation of the models. The MPS-Db enables users to manage their multifactor, multichip studies, then upload, analyze, review, computationally model and share data. Here we discuss how the sharing of MPS study data in the MS-Db is under user control and can be kept private to the individual user, shared with a select group of collaborators, or be made accessible to the general scientific community. We also present a test case using our liver acinus MPS model (LAMPS) as an example and discuss the use of the MPS-Db in managing, designing, and analyzing MPS study data, assessing the reproducibility of MPS models, and evaluating the concordance of MPS model results with clinical findings. We introduce the Disease Portal module with links to resources for the design of MPS disease models and studies and discuss the integration of computational models for the prediction of PK/PD and disease pathways using data generated from MPS models.
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Affiliation(s)
- Mark Schurdak
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. and Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Lawrence Vernetti
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. and Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Luke Bergenthal
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
| | - Quinn K Wolter
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
| | - Tong Ying Shun
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
| | - Sandra Karcher
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
| | - D Lansing Taylor
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. and Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Albert Gough
- Drug Discovery Institute, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. and Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
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