Archives of Toxicology

, Volume 92, Issue 12, pp 3505–3515 | Cite as

Relevance of the incubation period in cytotoxicity testing with primary human hepatocytes

  • Xiaolong Gu
  • Wiebke Albrecht
  • Karolina Edlund
  • Franziska Kappenberg
  • Jörg Rahnenführer
  • Marcel Leist
  • Wolfgang Moritz
  • Patricio Godoy
  • Cristina Cadenas
  • Rosemarie Marchan
  • Tim Brecklinghaus
  • Laia Tolosa Pardo
  • José V. Castell
  • Iain Gardner
  • Bo Han
  • Jan G. HengstlerEmail author
  • Regina Stoeber
In vitro systems


Primary human hepatocytes (PHHs) remain the gold standard for in vitro testing in the field of pharmacology and toxicology. One crucial parameter influencing the results of in vitro tests is the incubation period with test compounds. It has been suggested that longer incubation periods may be critical for the prediction of repeated dose toxicity. However, a study that systematically analyzes the relationship between incubation period and cytotoxicity in PHHs is not available. To close this gap, 30 compounds were tested in a concentration-dependent manner for cytotoxicity in cultivated cryopreserved PHHs (three donors per compound) for 1, 2 and 7 days. The median of the EC50 values of all compounds decreased 1.78-fold on day 2 compared to day 1, and 1.89-fold on day 7 compared to day 1. Median values of EC50 ratios of all compounds at day 2 and day 7 were close to one but for individual compounds the ratio increased up to almost six. Strong correlations were obtained for EC50 on day 1 and day 7 (R = 0.985; 95% CI 0.960–0.994), day 1 and day 2 (R = 0.964; 95% CI 0.910–0.986), as well as day 2 and day 7 (R = 0.981; 95% CI 0.955–0.992). However, compound specific differences also occurred. Whereas, for example, busulfan showed a relatively strong increase on day 7 compared to day 1, cytotoxicity of acetaminophen did not increase during longer incubation periods. To validate the observed correlations, a publicly available data set, containing data on the cytotoxicity of human hepatocytes cultivated as spheroids for incubation periods of 5 and 14 days, was analyzed. A high correlation coefficient of EC50 values at day 5 and day 14 was obtained (R = 0.894; 95% CI 0.798–0.945). In conclusion, the median cytotoxicity of the test compounds increased between 1 and 2 days of incubation, with no or only a minimal further increase until day 7. It remains to be studied whether the different results obtained for some individual compounds after longer exposure periods would correspond better to human-repeated dose toxicity.


Hepatotoxicity Primary human hepatocyte Incubation period Cell-titer-blue 





















Dimethyl sulfoxide


Drug-induced liver injury






































Valproic acid

Vit C

Vitamin C



The study was supported by the European Union’s Horizon 2020 research and innovation programme (EUToxRisk; no. 681002) with additional contributions of the projects StemCellNet (BMBF, 01EK1604A), Liver Simulator (BMBF, 031A355A), DILI (BMBF, 031L0074F), LiSyM (BMBF, 031Loo45), LivSysTransfer (BMBF, 0101-31Q0517), InnoSysTox (BMBF/EU, 031L0021A), SteatoTox (031L0114B) and DEEP (BMBF, 01KU1216).

Compliance with ethical standards

Conflict of interest

There is no conflict of interest.

Supplementary material

204_2018_2302_MOESM1_ESM.pdf (131 kb)
Suppl. Fig. 1A: Cell-Titer-Blue cytotoxicity data for 30 compounds in primary human hepatocytes after incubation for one, two and seven days. The concentration-dependent curves represent data from three independent experiments corresponding to hepatocytes from three different donors with four technical replicates each. The cell viability for each concentration is presented as the percentage of untreated controls. Gray symbols indicate the viability of each technical replicate normalized to untreated controls; whereas, black symbols represent the mean values of all technical replicates for each concentration. The vertical line indicates the concentration which causes 20% (A–C) or 50% (D–F) loss of viability. The vertical dashed black lines show the 95% confidence interval of the EC50 or EC20s. The exact EC50 or EC20 (or EC80) values are given in the lower left corner of each panel. (A) EC20, one day incubation period; (B) EC20, two days incubation period; (C) EC20, seven days incubation period; (D) EC50, one day incubation period; (E) EC50, two days incubation period; and (F) EC50, seven days incubation period (PDF 130 KB)
204_2018_2302_MOESM2_ESM.pdf (133 kb)
Suppl. Fig. 1B (PDF 133 KB)
204_2018_2302_MOESM3_ESM.pdf (126 kb)
Suppl. Fig. 1C (PDF 126 KB)
204_2018_2302_MOESM4_ESM.pdf (130 kb)
Suppl. Fig. 1D (PDF 130 KB)
204_2018_2302_MOESM5_ESM.pdf (133 kb)
Suppl. Fig. 1E (PDF 132 KB)
204_2018_2302_MOESM6_ESM.pdf (126 kb)
Suppl. Fig. 1F (PDF 126 KB)
204_2018_2302_MOESM7_ESM.pptx (2.6 mb)
Suppl. Fig. 2: Bar plots of cytotoxicity EC50 and EC20 for 30 compounds in primary human hepatocytes after incubation for one, two and seven days. Note: For day one and day two or both, some of the less toxic compounds did not reduce viability compared to controls. In these cases, the highest tested concentrations were used and bars were labeled by an asterisk (PPTX 2685 KB)
204_2018_2302_MOESM8_ESM.pdf (331 kb)
Supplement 1: Detailed donor characteristics given by the supplier (PDF 331 KB)
204_2018_2302_MOESM9_ESM.docx (148 kb)
Supplement 2: Standard operation procedure (SOP) for cultivation of primary human hepatocytes (DOCX 148 KB)
204_2018_2302_MOESM10_ESM.docx (147 kb)
Supplement 3: Standard operation procedure (SOP) for cytotoxicity testing (DOCX 147 KB)
204_2018_2302_MOESM11_ESM.docx (22 kb)
Suppl. Table 1: (A) Stock solutions of the test compounds. For incubation periods of 24 and 48 h, the concentrations of stock solutions given in the light fields were used. For the 7 days incubation period, additional lower concentrations of stock solutions were used as indicated by the dark background. A final concentration of 0.1% DMSO in the culture medium was used with the exception of compounds with low solubility, where 0.5% DMSO was used, indicated by *. Culture medium-soluble compounds are indicated in blue, while compounds dissolved in DMSO are indicated in red. In the present study, concentrations have been selected to study cytotoxicity. To compare in vivo relevant concentrations, peak plasma concentrations of therapeutic doses (or documented human exposure for chemicals not used as drugs) are given. (B) Investigated concentrations of the test compounds. The applied stock solutions are given in Suppl. Table 1. For incubation periods of 24 and 48 h, the concentrations indicated in the white fields were tested. For the seven days incubation period, additional lower concentrations were tested as indicated in the fields with grey background. For water soluble test compounds, the required concentrations could be obtained in the culture medium (indicated by blue colour). For the further compounds (labeled red), stock solutions were prepared in dimethyl sulfoxide (DMSO). The final concentration of DMSO was 0.1%, with the exception of compounds with relatively low DMSO solubility which had a final concentration of 0.5% DMSO (indicated by * in Table 1 and Suppl. Table 1) (DOCX 22 KB)
204_2018_2302_MOESM12_ESM.xlsx (15 kb)
Suppl. Table 2: Cytotoxicity data (EC50 and EC20 values; mean and median values of three donors) from all test compounds, with ratios of EC50 as well as EC20 values of the different incubation periods (XLSX 15 KB)
204_2018_2302_MOESM13_ESM.xlsx (16 kb)
Suppl. Table 3: EC50 and EC20 values for each individual donor (XLSX 16 KB)
204_2018_2302_MOESM14_ESM.xlsx (116 kb)
Suppl. Table 4: Raw data from the CellTiter-Blue test of all individual compounds and donors (XLSX 115 KB)


  1. Arbo MD, Melega S, Stober R et al (2016) Hepatotoxicity of piperazine designer drugs: up-regulation of key enzymes of cholesterol and lipid biosynthesis. Arch Toxicol 90(12):3045–3060CrossRefGoogle Scholar
  2. Bernal W, Auzinger G, Dhawan A, Wendon J (2010) Acute liver failure. Lancet 376(9736):190–201CrossRefGoogle Scholar
  3. Chaudhari U, Nemade H, Gaspar JA, Hescheler J, Hengstler JG, Sachinidis A (2016) MicroRNAs as early toxicity signatures of doxorubicin in human-induced pluripotent stem cell-derived cardiomyocytes. Arch Toxicol 90(12):3087–3098CrossRefGoogle Scholar
  4. Colaianna M, Ilmjarv S, Peterson H et al (2017) Fingerprinting of neurotoxic compounds using a mouse embryonic stem cell dual luminescence reporter assay. Arch Toxicol 91(1):365–391CrossRefGoogle Scholar
  5. Daneshian M, Kamp H, Hengstler J, Leist M, van de Water B (2016) Highlight report: launch of a large integrated European in vitro toxicology project: EU-ToxRisk. Arch Toxicol 90(5):1021–1024CrossRefGoogle Scholar
  6. Deharde D, Schneider C, Hiller T et al (2016) Bile canaliculi formation and biliary transport in 3D sandwich-cultured hepatocytes in dependence of the extracellular matrix composition. Arch Toxicol 90(10):2497–2511CrossRefGoogle Scholar
  7. Frey O, Misun PM, Fluri DA, Hengstler JG, Hierlemann A (2014) Reconfigurable microfluidic hanging drop network for multi-tissue interaction and analysis. Nat Commun 5:4250CrossRefGoogle Scholar
  8. Gaspar JA, Doss MX, Hengstler JG, Cadenas C, Hescheler J, Sachinidis A (2014) Unique metabolic features of stem cells, cardiomyocytes, and their progenitors. Circ Res 114(8):1346–1360CrossRefGoogle Scholar
  9. Ghallab A (2015) Interspecies extrapolation by physiologically based pharmacokinetic modeling. EXCLI J 14:1261–1263PubMedPubMedCentralGoogle Scholar
  10. Ghallab A, Celliere G, Henkel SG et al (2016) Model-guided identification of a therapeutic strategy to reduce hyperammonemia in liver diseases. J Hepatol 64(4):860–871CrossRefGoogle Scholar
  11. Godoy P, Hewitt NJ, Albrecht U et al (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. Arch Toxicol 87(8):1315–1530CrossRefGoogle Scholar
  12. Godoy P, Schmidt-Heck W, Natarajan K et al (2015) Gene networks and transcription factor motifs defining the differentiation of stem cells into hepatocyte-like cells. J Hepatol 63(4):934–942CrossRefGoogle Scholar
  13. Godoy P, Widera A, Schmidt-Heck W et al (2016) Gene network activity in cultivated primary hepatocytes is highly similar to diseased mammalian liver tissue. Arch Toxicol 90(10):2513–2529CrossRefGoogle Scholar
  14. Gong X, Ivanov VN, Hei TK (2016) 2,3,5,6-Tetramethylpyrazine (TMP) down-regulated arsenic-induced heme oxygenase-1 and ARS2 expression by inhibiting Nrf2, NF-kappaB, AP-1 and MAPK pathways in human proximal tubular cells. Arch Toxicol 90(9):2187–2200CrossRefGoogle Scholar
  15. Grinberg M (2017) Statistical analysis of concentration-dependent, high-dimensional gene expression data. PhD thesis, University of Dortmund, 2017Google Scholar
  16. Grinberg M, Stober RM, Edlund K et al (2014) Toxicogenomics directory of chemically exposed human hepatocytes. Arch Toxicol 88(12):2261–2287CrossRefGoogle Scholar
  17. Hammad S, Braeuning A, Meyer C, Mohamed F, Hengstler JG, Dooley S (2017) A frequent misinterpretation in current research on liver fibrosis: the vessel in the center of CCl4-induced pseudolobules is a portal vein. Arch Toxicol 91(11):3689–3692CrossRefGoogle Scholar
  18. Hengstler JG, Utesch D, Steinberg P et al (2000) Cryopreserved primary hepatocytes as a constantly available in vitro model for the evaluation of human and animal drug metabolism and enzyme induction. Drug Metab Rev 32(1):81–118CrossRefGoogle Scholar
  19. Hewitt NJ, Lechon MJ, Houston JB et al (2007) Primary hepatocytes: current understanding of the regulation of metabolic enzymes and transporter proteins, and pharmaceutical practice for the use of hepatocytes in metabolism, enzyme induction, transporter, clearance, and hepatotoxicity studies. Drug Metab Rev 39(1):159–234CrossRefGoogle Scholar
  20. Hoehme S, Brulport M, Bauer A et al (2010) Prediction and validation of cell alignment along microvessels as order principle to restore tissue architecture in liver regeneration. Proc Natl Acad Sci USA 107(23):10371–10376CrossRefGoogle Scholar
  21. Hoehme S, Friebel A, Hammad S, Drasdo D, Hengstler JG (2017) Creation of three-dimensional liver tissue models from experimental images for systems medicine. Methods Mol Biol 1506:319–362CrossRefGoogle Scholar
  22. Jansen PL, Ghallab A, Vartak N et al (2017) The ascending pathophysiology of cholestatic liver disease. Hepatology 65(2):722–738CrossRefGoogle Scholar
  23. Kampe T, Konig A, Schroeder H, Hengstler JG, Niemeyer CM (2014) Modular microfluidic system for emulation of human phase I/phase II metabolism. Anal Chem 86(6):3068–3074CrossRefGoogle Scholar
  24. Kim JY, Fluri DA, Marchan R et al (2015) 3D spherical microtissues and microfluidic technology for multi-tissue experiments and analysis. J Biotechnol 205:24–35CrossRefGoogle Scholar
  25. Krug AK, Kolde R, Gaspar JA et al (2013) Human embryonic stem cell-derived test systems for developmental neurotoxicity: a transcriptomics approach. Arch Toxicol 87(1):123–143CrossRefGoogle Scholar
  26. LeCluyse EL (2001) Human hepatocyte culture systems for the in vitro evaluation of cytochrome P450 expression and regulation. Eur J Pharm Sci 13(4):343–368CrossRefGoogle Scholar
  27. Leist M, Ghallab A, Graepel R et al (2017) Adverse outcome pathways: opportunities, limitations and open questions. Arch Toxicol 91(11):3477–3505CrossRefGoogle Scholar
  28. Liu G, Wang ZK, Wang ZY, Yang DB, Liu ZP, Wang L (2016) Mitochondrial permeability transition and its regulatory components are implicated in apoptosis of primary cultures of rat proximal tubular cells exposed to lead. Arch Toxicol 90(5):1193–1209CrossRefGoogle Scholar
  29. Luckert C, Schulz C, Lehmann N et al (2017) Comparative analysis of 3D culture methods on human HepG2 cells. Arch Toxicol 91(1):393–406CrossRefGoogle Scholar
  30. Ostapowicz G, Fontana RJ, Schiodt FV et al (2002) Results of a prospective study of acute liver failure at 17 tertiary care centers in the United States. Ann Intern Med 137(12):947–954CrossRefGoogle Scholar
  31. Pfeiffer E, Kegel V, Zeilinger K et al (2015) Featured article: Isolation, characterization, and cultivation of human hepatocytes and non-parenchymal liver cells. Exp Biol Med (Maywood NJ) 240(5):645–656CrossRefGoogle Scholar
  32. Proctor WR, Foster AJ, Vogt J et al (2017) Utility of spherical human liver microtissues for prediction of clinical drug-induced liver injury. Arch Toxicol 91(8):2849–2863CrossRefGoogle Scholar
  33. Reif R, Karlsson J, Gunther G et al (2015) Bile canalicular dynamics in hepatocyte sandwich cultures. Arch Toxicol 89(10):1861–1870CrossRefGoogle Scholar
  34. Rempel E, Hoelting L, Waldmann T et al (2015) A transcriptome-based classifier to identify developmental toxicants by stem cell testing: design, validation and optimization for histone deacetylase inhibitors. Arch Toxicol 89(9):1599–1618CrossRefGoogle Scholar
  35. Schliess F, Hoehme S, Henkel SG et al (2014) Integrated metabolic spatial-temporal model for the prediction of ammonia detoxification during liver damage and regeneration. Hepatology 60(6):2040–2051CrossRefGoogle Scholar
  36. Shinde V, Hoelting L, Srinivasan SP et al (2017) Definition of transcriptome-based indices for quantitative characterization of chemically disturbed stem cell development: introduction of the STOP-Toxukn and STOP-Toxukk tests. Arch Toxicol 91(2):839–864CrossRefGoogle Scholar
  37. Waldmann T, Rempel E, Balmer NV et al (2014) Design principles of concentration-dependent transcriptome deviations in drug-exposed differentiating stem cells. Chem Res Toxicol 27(3):408–420CrossRefGoogle Scholar
  38. Wilke RA, Lin DW, Roden DM et al (2007) Identifying genetic risk factors for serious adverse drug reactions: current progress and challenges. Nat Rev Drug Discov 6(11):904–916CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Xiaolong Gu
    • 1
    • 2
  • Wiebke Albrecht
    • 1
  • Karolina Edlund
    • 1
  • Franziska Kappenberg
    • 3
  • Jörg Rahnenführer
    • 3
  • Marcel Leist
    • 4
  • Wolfgang Moritz
    • 5
  • Patricio Godoy
    • 1
  • Cristina Cadenas
    • 1
  • Rosemarie Marchan
    • 1
  • Tim Brecklinghaus
    • 1
  • Laia Tolosa Pardo
    • 6
  • José V. Castell
    • 6
  • Iain Gardner
    • 7
  • Bo Han
    • 2
  • Jan G. Hengstler
    • 1
    Email author
  • Regina Stoeber
    • 1
  1. 1.Leibniz Research Centre for Working Environment and Human Factors at the Technical University of Dortmund (IfADo)DortmundGermany
  2. 2.College of Veterinary MedicineYunnan Agricultural UniversityKunmingPeople’s Republic of China
  3. 3.Department of StatisticsTU Dortmund UniversityDortmundGermany
  4. 4.In Vitro Toxicology and Biomedicine, Department of BiologyUniversity of KonstanzKonstanzGermany
  5. 5.InSphero AGZürichSwitzerland
  6. 6.Unit for Cell TherapyUniversity La Fe HospitalValenciaSpain
  7. 7.SimcypSheffieldUK

Personalised recommendations