Micropatterned Co‐Cultures of Human Hepatocytes and Stromal Cells for the Assessment of Drug Clearance and Drug‐Drug Interactions

Christine Lin1, Salman R Khetani1

1 Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois
Publication Name:  Current Protocols in Toxicology
Unit Number:  Unit 14.17
DOI:  10.1002/cptx.23
Online Posting Date:  May, 2017
GO TO THE FULL TEXT: PDF or HTML at Wiley Online Library

Abstract

Drug clearance rates from the body can determine drug exposure that can affect efficacy or toxicity. Thus, accurate prediction of drug clearance during preclinical development can help guide dose selection in humans, but animal testing is not always predictive of human outcomes. Because hepatic drug metabolism is a rate‐limiting step in the overall clearance of many drugs, primary human hepatocytes (PHHs) in suspension cultures or monolayers are used for drug clearance predictions. Yet, the precipitous decline in drug metabolism capacity can lead to significant underestimation of clearance rates, particularly for low turnover compounds that have desirable one‐pill‐a‐day dosing regimens. In contrast, micropatterned co‐cultures (MPCCs) of PHHs and fibroblasts display phenotypic stability for several weeks and can help mitigate the limitations of conventional cultures. Here, we describe protocols to create and use MPCCs for drug clearance predictions, and for modeling clinically‐relevant drug‐drug interactions that can affect drug clearance. © 2017 by John Wiley & Sons, Inc.

Keywords: primary human hepatocytes; cytochrome P450; 3T3‐J2 fibroblasts; low turnover drugs; drug metabolism

     
 
GO TO THE FULL PROTOCOL:
PDF or HTML at Wiley Online Library

Table of Contents

  • Introduction
  • Basic Protocol 1: Creation of Micropatterned Cocultures
  • Support Protocol 1: Constructing the PDMS Mask
  • Support Protocol 2: Culturing 3T3‐J2 Fibroblasts
  • Support Protocol 3: Assessing Hepatocyte Health/Functionality
  • Basic Protocol 2: Assessing Drug Clearance in MPCCs
  • Alternate Protocol 1: Assessing Drug‐Drug Interactions in MPCCs
  • Reagents and Solutions
  • Commentary
  • Literature Cited
  • Figures
  • Tables
     
 
GO TO THE FULL PROTOCOL:
PDF or HTML at Wiley Online Library

Materials

Basic Protocol 1: Creation of Micropatterned Cocultures

  Materials
  • Rat‐tail collagen type I (Corning, cat. no. 354236)
  • Sterile double‐distilled water (ddH 2O)
  • 70% (v/v) ethanol in ddH 2O
  • 0.05% (w/v) bovine serum albumin fraction V (Fisher Scientific, cat. no. BP1600‐100) in ddH 2O
  • Plateable cryopreserved PHHs (BioreclamationIVT, Triangle Research Laboratories, and Life Technologies)
  • Human hepatocyte seeding medium (see recipe)
  • Trypan blue
  • 1× Dulbecco's modified Eagle medium (DMEM), high‐glucose formulation
  • Human hepatocyte overnight medium (see recipe)
  • 3T3‐J2 fibroblasts (see protocol 3)
  • Human hepatocyte maintenance medium (see recipe)
  • Biosafety cabinet
  • 96‐well tissue‐culture plates, polystyrene
  • 37°C cell culture incubator
  • PDMS mask (see protocol 2)
  • Plate compression clamp (Star Prototype Manufacturing, Guangdong, China, or 3D Systems, Rockhill, SC)
  • Screwdriver
  • Oxygen tank (medical grade)
  • Oxygen plasma chamber (e.g., PlasmaEtch and SPI Supplies)
  • 37°C water bath
  • 50‐ml conical tubes
  • Hemocytometer
  • Serologic pipettes
  • Multichannel micropipettes with tips
  • Tissue culture microscope

Support Protocol 1: Constructing the PDMS Mask

  Materials
  • Hexamethyldisilazane
  • Sylgard 184 PDMS kit (Dow Corning)
  • Silicon master wafer with SU‐8 photoresist (150‐250 µm thickness) negatively patterned in circular micro‐domains/islands of 500‐µm diameter that are spaced 1200 µm apart center‐to‐center (Trianja Technologies, SimTech, or FlowJem)
  • Glass petri dish
  • Weighing dishes
  • Vacuum desiccator
  • Arch punch (5‐mm diameter for a 96‐well plate)
  • Teflon blocks (e.g., Star Prototype Manufacturing, Guangdong, China, or 3D Systems, Rockhill, SC)
  • Oven

Support Protocol 2: Culturing 3T3‐J2 Fibroblasts

  Materials
  • 3T3‐J2 murine embryonic fibroblasts (courtesy of Howard Green from Harvard Medical School)
  • Fibroblast medium (see recipe)
  • 1× phosphate buffered saline (PBS) solution
  • 0.25% (w/v) trypsin in 0.21 mm ethylenediaminetetraacetic acid (trypsin‐EDTA)
  • Tissue culture flasks (T‐150)

Support Protocol 3: Assessing Hepatocyte Health/Functionality

  Materials
  • CYP450 luminescent kit (Promega)
  • CYP450 substrates reconstituted in dimethyl sulfoxide (DMSO)
  • Human hepatocyte dosing medium (see recipe)
  • Human hepatocyte maintenance medium (see recipe)
  • Human albumin ELISA kit (Bethyl Laboratories)
  • Urea nitrogen test kit (Stanbio Laboratory)
  • 96‐well collection plates
  • 96‐well assay plates
  • Multichannel micropipettes with tips
  • Spectrophotometer (ideally compatible with 96‐well plate for higher throughput)
  • Luminometer (ideally compatible with 96‐well plates for higher throughput)
  • Data analysis software (e.g., Microsoft Excel and GraphPad Prism)

Basic Protocol 2: Assessing Drug Clearance in MPCCs

  Materials
  • Drugs of interest
  • DMSO
  • Human hepatocyte dosing medium (see recipe)
  • MPCCs seeded in 96‐well tissue culture plates (from protocol 1)
  • 1.5‐ml microcentrifuge tubes
  • 37°C water bath
  • 37°C incubator

Alternate Protocol 1: Assessing Drug‐Drug Interactions in MPCCs

  Additional Materials
  • Drugs of interest (perpetrator and victim drugs)
GO TO THE FULL PROTOCOL:
PDF or HTML at Wiley Online Library

Figures

Videos

Literature Cited

Literature Cited
  Akabane, T., Gerst, N., Naritomi, Y., Masters, J. N., & Tamura, K. (2012). A practical and direct comparison of intrinsic metabolic clearance of several non‐CYP enzyme substrates in freshly isolated and cryopreserved hepatocytes. Drug Metabolism and Pharmacokinetics, 27, 181–191. doi: 10.2133/dmpk.DMPK‐11‐RG‐097.
  Atkinson, A. J. & Kushner, W. (1979). Clinical pharmacokinetics. Annual Review of Pharmacology and Toxicology, 19, 105–127. doi: 10.1146/annurev.pa.19.040179.000541.
  Baudoin, R., Legendre, A., Jacques, S., Cotton, J., Bois, F., & Leclerc, E. (2014). Evaluation of a liver microfluidic biochip to predict in vivo clearances of seven drugs in rats. Journal of Pharmaceutical Sciences, 103, 706–718. doi: 10.1002/jps.23796.
  Bhatia, S. N., Yarmush, M. L., & Toner, M. (1997). Controlling cell interactions by micropatterning in co‐cultures: Hepatocytes and 3T3 fibroblasts. Journal of Biomedical Materials Research, 34, 189–199. doi: 10.1002/(SICI)1097‐4636(199702)34:2<189::AID‐JBM8>3.0.CO;2‐M.
  Bi, Y.‐A., Kazolias, D., & Duignan, D. B. (2006). Use of cryopreserved human hepatocytes in sandwich culture to measure hepatobiliary transport. Drug Metabolism and Disposition, 34, 1658–1665. doi: 10.1124/dmd.105.009118.
  Chan, T. S., Yu, H., Moore, A., Khetani, S. R., & Tweedie, D. (2013). Meeting the challenge of predicting hepatic clearance of compounds slowly metabolized by cytochrome P450 using a novel hepatocyte model, HepatoPacTM. Drug metabolism and Disposition, 41, 2024–2032. doi: 10.1124/dmd.113.053397.
  Chao, P., Barminko, J., Novik, E., Han, Y., Maguire, T., & Cheng, K. C. (2009). Prediction of human hepatic clearance using an in vitro plated hepatocyte clearance model. Drug Metabolism Letters, 3, 296–307. doi: 10.2174/187231209790218073.fc4all.
  Davidson, M. D., Ballinger, K. R., & Khetani, S. R. (2016). Long‐term exposure to abnormal glucose levels alters drug metabolism pathways and insulin sensitivity in primary human hepatocytes. Scientific Reports, 6, 28178. doi: 10.1038/srep28178.
  Davidson, M. D., Lehrer, M., & Khetani, S. R. (2015). Hormone and drug‐mediated modulation of glucose metabolism in a microscale model of the human liver. Tissue Engineering Part C Methods, 21, 716–725. doi: 10.1089/ten.tec.2014.0512.
  Di, L., Hsu, I. C., Trapa, P., Tokiwa, T., Obach, R. S., Bennett, W., … Welsh, J. A. (2012). A novel relay method for determining low‐clearance values. Drug Metabolism and Disposition, 40, 1860–1865. doi: 10.1124/dmd.112.046425.
  Godoy, P., Hewitt, N. J., Albrecht, U., Andersen, M. E., Ansari, N., Bhattacharya, S., Bode, J. G., … Hengstler, J. G. (2013). Recent advances in 2D and 3D in vitro systems using primary hepatocytes, alternative hepatocyte sources and non‐parenchymal liver cells and their use in investigating mechanisms of hepatotoxicity, cell signaling and ADME. Archives of Toxicology, 87, 1315–1530. doi: 10.1007/s00204‐013‐1078‐5.
  Guguen‐Guillouzo, C., Clément, B., Baffet, G., Beaumont, C., Morel‐Chany, E., Glaise, D., & Guillouzo, A. (1983). Maintenance and reversibility of active albumin secretion by adult rat hepatocytes co‐cultured with another liver epithelial cell type. Experimental cell Research, 143, 47–54. doi: 10.1016/0014‐4827(83)90107‐6.
  Hallifax, D., Foster, J. A., & Houston, J. B. (2010). Prediction of human metabolic clearance from in vitro systems: Retrospective analysis and prospective view. Pharmaceutical Research, 27, 2150–2161. doi: 10.1007/s11095‐010‐0218‐3.
  Khetani, S. R., & Bhatia, S. N. (2008). Microscale culture of human liver cells for drug development. Nature Biotechnology, 26, 120–126. doi: 10.1038/nbt1361.
  Khetani, S. R., Chen, A. A., Ranscht, B., & Bhatia, S. N. (2008). T‐cadherin modulates hepatocyte functions in vitro. The FASEB Journal, 22, 3768–3775. doi: 10.1096/fj.07‐105155.
  Khetani, S. R., Szulgit, G., Del Rio, J. A., Barlow, C., & Bhatia, S. N. (2004). Exploring interactions between rat hepatocytes and nonparenchymal cells using gene expression profiling. Hepatology, 40, 545–554. doi: 10.1002/hep.20351.
  Khetani, S. R., Kanchagar, C., Ukairo, O., Krzyzewski, S., Moore, A., Shi, J., … Will, Y. (2013). Use of micropatterned cocultures to detect compounds that cause drug‐induced liver injury in humans. Toxicological Sciences, 132, 107–117. doi: 10.1093/toxsci/kfs326.
  Lecluyse, E. L. (2001). Human hepatocyte culture systems for the in vitro evaluation of cytochrome P450 expression and regulation. European Journal of Pharmaceutical Sciences, 13, 343–368. doi: 10.1016/S0928‐0987(01)00135‐X.
  Lin, C., Shi, J., Moore, A., & Khetani, S. R. (2016). Prediction of drug clearance and drug‐drug interactions in microscale cultures of human hepatocytes. Drug Metabolism and Disposition, 44, 127–136. doi: 10.1124/dmd.115.066027.
  March, S., Ng, S., Velmurugan, S., Galstian, A., Shan, J., Logan, D. J., … Bhatia, S. N. (2013). A microscale human liver platform that supports the hepatic stages of Plasmodium falciparum and vivax. Cell Host & Microbe, 14, 104–115. doi: 10.1016/j.chom.2013.06.005.
  Nguyen, T. V., Ukairo, O., Khetani, S. R., McVay, M., Kanchagar, C., Seghezzi, W., … Evers, R. (2015). Establishment of a hepatocyte‐kupffer cell coculture model for assessment of proinflammatory cytokine effects on metabolizing enzymes and drug transporters. Drug Metabolism and Disposition, 43, 774–785. doi: 10.1124/dmd.114.061317.
  Nishimura, M., Ueda, N., & Naito, S. (2003). Effects of dimethyl sulfoxide on the gene induction of cytochrome P450 isoforms, UGT‐dependent glucuronosyl transferase isoforms, and ABCB1 in primary culture of human hepatocytes. Biological & Pharmaceutical Bulletin, 26, 1052–1056. doi: 10.1248/bpb.26.1052.
  Obach, R. S., Baxter, J. G., Liston, T. E., Silber, B. M., Jones, B. C., MacIntyre, F., … Wastall, P. (1997). The prediction of human pharmacokinetic parameters from preclinical and in vitro metabolism data. The Journal of Pharmacology and Experimental Therapeutics, 283, 46–58.
  Peng, C.‐C., Doshi, U., Prakash, C., & Li, A. P. (2016). A novel plated hepatocyte relay assay (PHRA) for in vitro evaluation of hepatic metabolic clearance of slowly metabolized compounds. Drug Metabolism Letters, 10, 3–15. doi: 10.2174/1872312809666150818111500.
  Ploss, A., Khetani, S. R., Jones, C. T., Syder, A. J., Trehan, K., Gaysinskaya, V. A., … Bhatia, S. N. (2010). Persistent hepatitis C virus infection in microscale primary human hepatocyte cultures. Proceedings of the National Academy of Sciences, 107, 3141–3145. doi: 10.1073/pnas.0915130107.
  Ramsden, D., Tweedie, D. J., Chan, T. S., Taub, M. E., & Li, Y. (2014). Bridging in vitro and in vivo metabolism and transport of faldaprevir in human using a novel cocultured human hepatocyte system, HepatoPac. Drug metabolism and Disposition, 42, 394–406. doi: 10.1124/dmd.113.055897.
  Ring, B. J., Chien, J. Y., Adkison, K. K., Jones, H. M., Rowland, M., Jones, R. D., … Poulin, P. (2011). PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 3: Comparative assessement of prediction methods of human clearance. Journal of Pharmaceutical Sciences, 100, 4090–4110. doi: 10.1002/jps.22552.
  Shih, H., Pickwell, G. V., Guenette, D. K., Bilir, B., & Quattrochi, L. C. (1999). Species differences in hepatocyte induction of CYP1A1 and CYP1A2 by omeprazole. Human & Experimental Toxicology, 18, 95–105. doi: 10.1191/096032799678839699.
  Shlomai, A., Schwartz, R. E., Ramanan, V., Bhatta, A., de Jong, Y. P., Bhatia, S. N., & Rice, C. M. (2014). Modeling host interactions with hepatitis B virus using primary and induced pluripotent stem cell‐derived hepatocellular systems. Proceedings of the National Academy of Sciences, 111, 12193–12198. doi: 10.1073/pnas.1412631111.
  Tweedie, D., Polli, J. W., Berglund, E. G., Huang, S.‐M., Zhang, L., Poirier, A., … Feng, B., and International Transporter Consortium. (2013). Transporter studies in drug development: Experience to date and follow‐up on decision trees from the International Transporter Consortium. Clinical Pharmacology and Therapeutics, 94, 113–125. doi: 10.1038/clpt.2013.77.
  Wang, W. W., Khetani, S. R., Krzyzewski, S., Duignan, D. B., & Obach, R. S. (2010). Assessment of a micropatterned hepatocyte coculture system to generate major human excretory and circulating drug metabolites. Drug Metabolism and Disposition, 38, 1900–1905. doi: 10.1124/dmd.110.034876.
  Ware, B. R., Berger, D. R., & Khetani, S. R. (2015). Prediction of drug‐induced liver injury in micropatterned co‐cultures containing iPSC‐derived human hepatocytes. Toxicological Sciences, 145, 252–262. doi: 10.1093/toxsci/kfv048.
  Wienkers, L. C. & Heath, T. G. (2005). Predicting in vivo drug interactions from in vitro drug discovery data. Nature Reviews Drug Discovery, 4, 825–833. doi: 10.1038/nrd1851.
GO TO THE FULL PROTOCOL:
PDF or HTML at Wiley Online Library