Refining Hepatocyte Models to Capture the Impact of CYP2D6*10 Utilizing a PITCh System

Ryosuke Negoro; Ayu Ouchi; Sayaka Deguchi; Kazuo Takayama; Takuya Fujita

doi:10.1248/bpb.b24-00202

Abstract

CYP2D6 variants contain various single nucleotide polymorphisms as well as differing levels of metabolic activity. Among these, one of the less active variants CYP2D6*10 (100C > T) is the most prevalent mutation in East Asians, including Japanese. This mutation leads to an amino acid substitution from proline to serine, which reduces the stability of CYP2D6 and consequently decreases its metabolic activity. In this study, we used a genome editing technology called the Precise Integration into Target Chromosome (PITCh) system to stably express six drug-metabolizing enzymes (CYP3A4, POR, uridine diphosphate glucuronosyltransferase 1A1 (UGT1A1), CYP1A2, CYP2C19, CYP2C9, and CYP2D6*10) in HepG2 (CYP2D6*10 KI-HepG2) cells to examine the effect of CYP2D6*10 on drug metabolism prediction. The protein expression levels of CYP2D6 in CYP2D6*10 KI-HepG2 cells were reduced relative to those in the CYP3A4-POR-UGT1A1-CYP1A2-CYP2C19-CYP2C9-CYP2D6 knock-in-HepG2 (CYPs-UGT1A1 KI-HepG2) cells. Consistent with the CYP2D6 protein expression results, CYP2D6 metabolic activity in CYP2D6*10 KI-HepG2 cells was reduced relative to CYPs-UGT1A1 KI-HepG2 cells. We successfully generated CYP2D6*10 KI-HepG2 cells with highly expressed, functional CYP2D6*10, as well as CYP1A2, 2C9, 2C19 and 3A4. CYP2D6*10 KI-HepG2 cells could be an invaluable model for hepatic metabolism and hepatotoxicity studies in East Asians, including Japanese.

INTRODUCTION

The liver, a pivotal organ in drug metabolism, relies on CYPs to fulfill its crucial role in this process.^1,2) CYPs exist in a variety of isoforms.³⁾ For example, CYP2D6 metabolizes antipsychotic drugs, adrenergic beta-receptor blockers, and anti-arrhythmic drugs.¹⁾ On the other hand, more than 100 genetic polymorphisms have been reported for CYP2D6; the large number of such single nucleotide polymorphisms (SNPs) in CYP2D6 has led to numerous reports on the drug effects and adverse drug reactions of drugs metabolized by CYP2D6.^4,5) CYP2D6.1 and CYP2D6.2, which show average metabolic capacities, predominate in non-East Asians, including Japanese.⁶⁾ However, the most prevalent SNP in CYP2D6 among East Asians, including Japanese, is CYP2D6*10 (exon 1, 100C > T). This particular SNP is associated with a reduced CYP2D6 metabolic capacity and accounts for approximately 59% of the observed cases, making it the most frequently reported genetic variation.^7,8) CYP2D6*10 is a genetic variant in which thymine replaces the cytosine at position 100 of exon1. This mutation results in a proline-to-serine substitution of an amino acid, which reduces the stability of CYP2D6 and is known to result in low metabolic activity.^6,9,10)

Although primary cultured human hepatocytes (PHHs) are currently the gold standard for human hepatocyte models, they have problems such as substantial lot differences, high cost, and a lack of passaging.¹¹⁾ On the other hand, the HepG2 cell line, which is derived from human hepatocellular carcinoma, is an inexpensive and reproducible hepatocyte model that can be tested reproducibly but cannot predict drug metabolism or toxicity due to metabolites because of deficient expression levels of most CYP molecular species.¹²⁾

Previously, our group successfully generated HepG2 cells stably expressing CYP1A2, 2C9, 2C19, 2D6, 3A4, and uridine diphosphate glucuronosyltransferase 1A1 (UGT1A1), each of which plays a critical role in drug metabolism in the liver, using the Precise Integration into Target Chromosomes (PITCh) system based on the clustered regularly interspaced short palindromic repeats-CRISPR associated 9 (CRISPR-Cas9) system.¹³⁾ Furthermore, CYP3A4-POR-UGT1A1-CYP1A2-CYP2C19-CYP2C9-CYP2D6 knock-in-HepG2 (CYPs-UGT1A1 KI-HepG2) cells have a high drug-metabolizing capacity, indicating that they could be a helpful model for drug discovery research.

In this study, we used the PITCh system to generate HepG2 cells stably expressing CYP1A2, 2C9, 2C19, 2D6*10, 3A4, and UGT1A1 and tested whether they could be a hepatocyte model reflecting CYP2D6 metabolic capacity in East Asians, including Japanese.

MATERIALS AND METHODS

HepG2 Cells

Parental HepG2 cells (RGB1648) were provided by RIKEN BRC (Ibaraki, Japan). The HepG2 cells culture protocol was described previously.¹³⁾

PHHs

The primary human hepatocyte culture protocol was described previously.^13–15)

Vector Construction

The CRISPR-Cas9 vector (pX330A-hROSA26/PITCh) was described previously.¹³⁾ Parental CRISPR-Cas9 vector (pX330A-1 × 2¹⁶⁾; Addgene plasmid #58766, pX330S-2-PITCh¹⁷⁾; Addgene plasmid #63670) were provided by Addgene (Watertown, MA, U.S.A.). The oligonucleotides for the sgRNA template targeting hROSA26 locus were described previously.¹³⁾

Donor vectors were constructed using PCR and an In-Fusion^® HD Cloning Kit (TaKaRa Bio, Shiga, Japan) or by standard molecular-cloning methods. An In-Fusion^® HD Cloning Kit (TaKaRa Bio) introduced a point mutation in CYP2D6 (NM_000106.6) to create CYP2D6*10 (exon1, 100C > T). The donor plasmid sequences are described in Supplementary Materials.

Transfection of HepG2 Cells for Genome Editing Experiments

The genome editing experiments protocol was described previously.¹³⁾ Briefly, CRISPR-Cas9 vector and donor plasmid vector 2 d after transfection, the medium was replaced with 0.4 mg/mL Hygromycin B (FUJIFILM Wako Pure Chemical Corporation, Osaka, Japan)-containing medium to generate CYP3A4-POR-UGT1A1-CYP1A2-CYP2C19-CYP2C9-CYP2D6*10 knock-in-HepG2 (CYP2D6*10 KI-HepG2) cells.

Real-Time RT-PCR

The total RNA isolated, cDNA synthesized and real-time RT-PCR protocol was described previously.^13,18,19) The real-time RT-PCR primer sequences are summarized in Supplementary Table S1.

Western Blotting

The Western blotting (WB) protocol was described previously.^18–20) Primary antibodies used were CYP1A2 (Cat# sc-53241; Santa Cruz Biotechnology, Dallas, TX, U.S.A.), CYP2C8/9/18/19 (Cat# 16546-1-AP; Proteintech, Rosemont, IL, U.S.A.), CYP2D6/7 (Cat# 17868-1-AP; Proteintech), CYP3A4 (Cat#sc-53850; Santa Cruz Biotechnology), POR (Cat#ab180597; Abcam, Cambridge, U.K.), UGT1A1 (Cat# ab170858; Abcam) or glyceraldehyde 3-phosphate dehydrogenase (GAPDH) (Cat#015-25473; FUJIFILM Wako Pure Chemical Corporation) antibody. Secondary antibody used was HRP-conjugated Affinipure Rabbit Anti-Goat immunoglobulin G (IgG) (H + L) (Cat#SA00001-4; Proteintech) or HRP-conjugated Affinipure Goat Anti-Mouse IgG (H + L) (Cat# SA00001-1; Proteintech). The intensity of the WB bands was measured using Image J with the Band/Peak Quantification Tool.²¹⁾ The intensity of the WB bands was normalized by that of the housekeeping protein, GAPDH.

Drug-Metabolizing Enzyme Activity

The protocol for measuring the activity of drug-metabolizing enzymes was described previously.^13,19) These compounds used as CYP2D6 inhibitors [10 µM Terbinafine (Tokyo Chemical Industry, Tokyo, Japan), 10 µM quinidine (Tokyo Chemical Industry) or 10 µM paroxetine (Tokyo Chemical Industry)]. HPLC analysis was performed using a Prominence HPLC system (Shimadzu, Kyoto, Japan). The HPLC methods was described previously.²²⁾

Cell Viability Tests

HepG2 cells were seeded in 96 well plates at 2.0 × 10⁴ cells/well. The next day, HepG2 cells were treated with various concentration of primaquine (Cayman Chemical, Ann Arbor, MI, U.S.A.) with or without quinidine (Tokyo Kasei, Tokyo, Japan). After 48 h, to examine the cell viability, we performed a WST-8 [2-(2-methoxy-4-nitrophenyl)-3-(4-nitrophenyl)-5-(2,4-disulfophenyl)-2H-tetrazolium, monosodium salt] assay by using Cell Count Reagent SF (Nacalai Tesque, Kyoto, Japan). The cell viability was calculated as a percentage of that in the cells treated with vehicle only.

Statistical Analysis

Statistical analyses were done as indicated in figure legends using Easy R (EZR) software. A value of p < 0.05 was considered statistically significant.

RESULTS

Generation of CYP2D6*10 KI-HepG2 Cells

Previously, our group generated CYP3A4-POR-UGT1A1-CYP1A2-CYP2C19 knock-in (KI)-HepG2 cells using the PITCh system. To generate CYP3A4-POR-UGT1A1-CYP1A2-CYP2C19-CYP2C9-CYP2D6*10 (CYP2D6*10) KI-HepG2 cells, the CAG-CYP2C9-CYP2D6*10-HygR-pA cassette was inserted into the hROSA26 locus of CYP3A4-POR-UGT1A1-CYP1A2-CYP2C19 KI-HepG2 cells using the PITCh system (Fig. 1). After hygromycin B selection, CYP2D6*10 KI-HepG2 cell clones were obtained.

Fig. 1. Generation of CYP2D6*10 KI-HepG2 Cells

This schematic overview shows the targeting strategy for hROSA26 locus. Donor and CRISPR-Cas9 plasmids: CAG, cytomegalovirus (CMV) early enhancer/chicken β actin promoter; U6, U6 promoter; PITCh, Precise Integration into Target Chromosome; MMEJ, microhomology-mediated end-joining; hROSA26, human ROSA26; P2A, self-cleaving P2A peptide sequence; T2A, self-cleaving T2A peptide sequence; CYP2C9, CYP family 2 subfamily C member 9; CYP2D6, CYP family 2 subfamily D member 6; HygR, hygromycin B resistance protein; pA, polyadenylation sequence.

To check whether hepatocyte markers in CYP2D6*10 KI-HepG2 cells were adversely affected by genome editing experiments, hepatocyte markers [albumin (ALB), asialoglycoprotein receptor 1 (ASGR1), and hepatocyte nuclear factor 4 alpha (HNF4A)] were assessed by real-time PCR (Fig. 2A). We used 48-hour cultured primary human hepatocytes (PHHs 48 h) as positive controls. The expression levels of hepatic marker in CYP2D6*10 KI-HepG2 cells were similar to those in WT-HepG2 cells and CYPs-UGT1A1 KI-HepG2 cells. Next, the gene expression levels of drug-metabolizing enzymes (CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP3A4, POR, and UGT1A1) were analyzed to assess whether genome-editing experiments have resulted in high expression of drug-metabolizing enzymes in CYP2D6*10 KI-HepG2 cells. The expression levels of drug-metabolizing enzyme genes in CYP2D6*10 KI-HepG2 cells were comparable to those in the CYPs-UGT1A1 KI-HepG2 cells (Fig. 2A). On the other hand, the expression levels of drug-metabolizing enzyme genes in CYP2D6*10 KI-HepG2 cells were higher than those in the WT-HepG2 cells (Fig. 2A). CYP2D6 protein expression in CYP2D6*10 KI-HepG2 cells was assessed by Western blotting. We used PHHs 48 h and PHHs collected immediately after thawing (PHHs 0 h) as positive controls. Consistently, the CYP1A2, CYP2C9/19, CYP3A4, POR and UGT1A1 protein expression levels in CYPs-UGT1A1 KI-HepG2 cells and CYP2D6*10 KI-HepG2 cells were higher than those in WT-HepG2 cells (Fig. 2B, Supplementary Fig. S1). Two bands of the CYP2D6 protein were detected. The lower band could not be detected in WT-HepG2 cells or CYP2D6*10 KI-HepG2 cells, whereas it was detectable in CYPs-UGT1A1 KI-HepG2 cells and PHHs. Therefore, we consider the lower band to represent the CYP2D6 protein. The lower band was thus designated as the CYP2D6 protein. CYP2D6 protein expression was lower in CYP2D6*10 KI-HepG2 cells than in CYPs-UGT1A1 KI-HepG2 cells, contrary to the CYP2D6 gene expression levels (Fig. 2B, Supplementary Figs. S1, S2). These results suggest that genome editing experiments have generated CYP2D6*10 KI-HepG2 cells that reflect the effects of CYP2D6*10 and express high levels of seven drug-metabolizing enzymes.

Fig. 2. Expression Analysis of CYP2D6*10 KI-HepG2 Cells

(A) The gene expression levels of hepatic markers and drug-metabolizing enzymes in WT-HepG2 cells, CYPs-UGT1A1 KI-HepG2 cells and CYP2D6*10 KI-HepG2 cells. On the y axis, the gene expression levels in the PHHs 48 h were taken as 1.0. Data represent the means ± standard deviations (S.Ds.) of three independent experiments. Statistical significance was evaluated by one-way ANOVA followed by Tukey’s post hoc test (p < 0.05). Groups that do not share the same letter had significantly different results. (B) The CYP1A2, CYP2C9/19, CYP2D6, CYP3A4, POR and UGT1A1 protein expression levels were measured by Western blotting analysis. Lane 1: WT-HepG2 cells, Lane 2: CYPs-UGT1A1 KI-HepG2 cells, Lane 3: CYP2D6*10 KI-HepG2 cells, Lane 4: PHHs 48 h, Lane 5: PHHs collected immediately after thawing 0 h (PHHs 0 h).

Drug-Metabolizing Activity Evaluation of CYP2D6*10 KI-HepG2 Cells

We evaluated the drug-metabolizing activity to assess whether genome-edited drug-metabolizing enzymes in CYP2D6*10 KI-HepG2 cells are functional. We used PHHs 48 h as positive controls. We examined the CYP1A2, 2C9, 2C19, 2D6, 3A4 and UGT1A1 activities by quantifying acetaminophen, 4′-hydroxy diclofenac, 4′-hydroxy mephenytoin, 1′-hydroxy bufuralol, 1′-hydroxy midazolam, and 7′-hydroxy coumarin glucuronide, respectively. CYP1A2, 2C9, 2C19, 3A4 and UGT1A1 activity levels in CYP2D6*10 KI-HepG2 cells were comparable to CYPs-UGT1A1 KI-HepG2 cells (Fig. 3). Interestingly, the CYP2D6 activity levels in CYP2D6*10 KI-HepG2 cells were lower than those in CYPs-UGT1A1 KI-HepG2 cells (Fig. 3).

Fig. 3. Drug-Metabolizing Activity Evaluation of CYP2D6*10 KI-HepG2 Cells

The CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP3A4 and UGT1A1 activities in WT-HepG2 cells, CYPs-UGT1A1 KI-HepG2 cells, CYP2D6*10 KI-HepG2 cells and 48-h cultured primary human hepatocytes (PHHs 48 h) were examined by quantifying the metabolites of CYP and UGT substrates (10 µM phenacetin, 10 µM diclofenac, 50 µM S-mephenytoin, 1 µM bufuralol, 10 µM midazolam and 10 µM 7′-hydroxy coumarin; these compounds are substrates for CYP1A2, 2C9, 2C19, 2D6, 3A4 and UGTs, respectively). The quantity of metabolites (acetaminophen, 4′-hydroxy diclofenac, 4′-hydroxy mephenytoin, 1′-hydroxy bufuralol, 1′-hydroxy midazolam and 7′-hydroxy coumarin glucuronide; these compounds are metabolites for CYP1A2, 2C9, 2C19, 2D6, 3A4 and UGTs, respectively) were measured by HPLC. Data represent the means ± S.D.s. (n = 3). N.D. not detected. Statistical significance was evaluated by one-way ANOVA followed by Tukey’s post hoc test (p < 0.05). Groups that do not share the same letter had significantly different results.

To assess whether bufuralol is metabolized by CYP2D6 in CYP2D6*10 KI-HepG2 cells, CYP2D6 inhibition experiments using terbinafine, quinidine or paroxetine (CYP2D6 inhibitors) were performed. In the presence of terbinafine, quinidine or paroxetine, the CYP2D6 activities in CYP2D6*10 KI-HepG2 cells and CYPs-UGT1A1 KI-HepG2 cells were significantly decreased (Figs. 4A, 4B). This suggests that the CYP2D6*10 KI-HepG2 cells had high CYP1A2, 2C9, 2C19, and 3A4 activity but low CYP2D6 metabolic capacity.

Fig. 4. Effects of Terbinafine, Quinidine or Paroxetine on CYP2D6-Mediated Bufuralol 1′-Hydroxylation in CYP2D6*10 KI-HepG2 Cells and CYPs-UGT1A1 KI-HepG2 Cells

The CYP2D6 activities in 10 µM terbinafine, 10 µM quinidine or 10 µM paroxetine (CYP2D6 inhibitors)-treated CYP2D6*10 KI-HepG2 cells (A) or CYPs-UGT1A1 KI-HepG2 cells (B) were evaluated by quantifying the metabolites of 1 µM bufuralol (a CYP2D6 substrate). The quantity of 1′-hydroxy bufuralol were measured by HPLC. Data represent the mean ± S.D. (n = 3). Statistical significance was evaluated by one-way ANOVA followed by Dunnett’s post hoc test (** p < 0.01: compared with “Control”).

Cell Toxicity of Primaquine-Treated CYP2D6*10 KI-HepG2 Cells

Primaquine, which is metabolized by CYP2D6 and has enhanced cytotoxicity, was used to assess whether CYP2D6*10 KI-HepG2 cells can predict metabolic toxicity reflecting SNPs due to CYP2D6 metabolism. Cell viability was measured by WST-8 assay. We found that the CYP2D6*10 KI-HepG2 cells had higher viability than the CYPs-UGT1A1 KI-HepG2 cells (Fig. 5). Furthermore, primaquine-induced cell death in CYPs-UGT1A1 KI-HepG2 cells and CYP2D6*10 KI-HepG2 cells was suppressed by quinidine (a CYP2D6 inhibitor) (Supplementary Fig. S3). These results suggest that CYP2D6*10 KI-HepG2 cells showed the potential to predict hepatotoxicity due to CYP2D6 metabolites, reflecting the influence of SNPs.

Fig. 5. Cell Toxicity of Primaquine-Treated CYP2D6*10 KI-HepG2 Cells

WT-HepG2 cells, CYPs-UGT1A1 KI-HepG2 cells and CYP2D6*10 KI-HepG2 cells were treated with various concentrations of primaquine. After 48 h, the cell viabilities were examined by WST-8 assay. The cell viability was calculated as a percentage of the number of cells after treatment with solvent only. Data represent the means ± S.D.s. (n = 3).

DISCUSSION

CYP2D6 gene expression in CYP2D6*10 KI-HepG2 cells was similar to those in CYPs-UGT1A1 KI-HepG2 cells, but CYP2D6 protein expression levels were lower (Figs. 2A, 2B). As previously reported, CYP2D6.10 is an unstable protein; therefore, CYP2D6 protein expression levels were markedly reduced, despite high gene expression levels.^6,8,10) Therefore, consistent with CYP2D6 protein expression levels, CYP2D6 activity in CYP2D6*10 KI-HepG2 cells showed lower metabolic capacity than CYPs-UGT1A1 KI-HepG2 cells (Fig. 3).

Two bands corresponding to CYP2C9 and CYP2C19 were detected in the WB analysis (Fig. 2B). In this study, a polyclonal antibody recognizing CYP2C8, CYP2C9, CYP2C18, and CYP2C19 was used. Given the high similarity in amino acid sequences and near-identical molecular weights of CYP2C8, 2C9, 2C18, and 2C19, it is challenging to accurately distinguish and detect these enzymes using antibodies alone. Consequently, attributing specific bands to CYP2C9 or CYP2C19 based on the Western blot results is difficult. Future proteomic analyses, employing techniques with higher resolution, would enable more precise quantification of their expression levels.

The molecular weight of CYP2D6 differed slightly between CYPs-UGT1A1 KI-HepG2 cells and PHHs 48 or PHHs 0 h (Fig. 2B). Ser135 of CYP2D6 is known to be phosphorylated.²³⁾ Post-translational modifications, such as the phosphorylation of CYP2D6, may differ slightly between HepG2 cells and PHHs, resulting in slight differences in the molecular weight of CYP2D6.

The protein expression levels of CYP3A4 in CYPS-UGT1A1 KI-HepG2 cells were higher than PHHs 48 h (Fig. 2B). However, the CYP3A4 activity levels of PHH 48 h and CYPs-UGT1A1 KI-HepG2 cells was comparable (Fig. 3). The active sites of CYPs, including CYP3A4, contain heme. The absence of heme in the active site of CYPs reduces their activity.²⁴⁾ Presumably, CYP3A4 in CYPs-UGT1A1 KI-HepG2 cells and CYP2D6*10 KI-HepG2 cells has some immature CYP3A4 with no heme coordination to the active site. The expression levels of all CYP isoforms and UGT isoforms in human hepatocytes are inconsistent with those in CYPs-UGT1A1 KI-HepG2 cells and CYP2D6*10 KI-HepG2 cells. Therefore, drug metabolism experiments using only CYPs-UGT1A1 KI-HepG2 cells or CYP2D6*10 KI-HepG2 cells may incorrectly predict the metabolism of drug candidates. Combining CYPs-UGT1A1 KI-HepG2 cells or CYP2D6*10 KI-HepG2 cells and human liver microsomes would be a more accurate way to predict drug metabolism.

CYP2D6*10 KI-HepG2 cells were generated by inserting the CAG-CYP2C9-CYP2D6*10-HygR-pA cassette (Fig. 1). CYP2D6 activity was markedly lower in CYP2D6*10 KI-HepG2 cells than in CYPs-UGT1A1 KI-HepG2 cells, while CYP2C9 activity was comparable (Fig. 3). The CAG-CYP2C9-CYP2D6*10-HygR-pA cassette can co-express CYP2C9 and CYP2D6.10 using 2A peptide. It is therefore improbable that CYP2D6*10 gene silencing would reduce CYP2D6*10 protein expression levels.

The protein levels of CYP2D6 in human liver microsomes of patients with CYP2D6*1/*1 or CYP2D6*10/*0 were reported to be 7.1 and 0.81 pmol/mg, respectively.²⁵⁾ The CYP2D6 activity in human liver microsomes of patients with CYP2D6*1/1, CYP2D6*1/*10 and CYP2D610/*10 has been reported to be 18.2 pmol/min/mg protein, 9.6 pmol/min/mg protein, and 4.9 pmol/min/mg protein, respectively.²⁶⁾ CYP2D6 protein in CYP2D6*10 KI-HepG2 cells could not be detected by WB analysis (Fig. 2B, Supplementary Fig. S2). On the other hand, CYP2D6 activity in CYP2D6*10 KI-HepG2 cells was about 1/10 of those in CYPs-UGT1A1 KI-HepG2 cells (Fig. 3). The CYP2D6 expression pattern in CYP2D6*10 KI-HepG2 cells compared to CYPs-UGT1A1 KI-HepG2 cells may be similar to those of patients with CYP2D610/*0 and CYP2D610/*10.

Cell viability of CYP2D6*10 KI-HepG2 cells due to primaquine treatment was higher than that of CYPs-UGT1A1 KI-HepG2 cells (Fig. 5). CYP2D6 metabolizes primaquine to produce 5-hydroxy primaquine.^27,28) 5-Hydroxy primaquine is an unstable intermediate and therefore reacts with water to form 5,6-ortho-quinone. 5-Hydroxy primaquine to 5,6-ortho-quinone produces reactive oxygen species such as H₂O₂. CYP2D6*10 KI-HepG2 cells have lower CYP2D6 activity than CYPs-UGT1A1 KI-HepG2 cells, which may result in reduced 5-hydroxy primaquine production and differences in cell viability.

Tamoxifen, a breast cancer drug, is metabolized by CYP2D6 to produce endoxifen. Endoxifen has been reported to have stronger anti-cancer activity than tamoxifen.²⁹⁾ Consistent with the previous report, treatment with tamoxifen has been reported to have a poor prognosis in breast cancer patients with CYP2D6*10.^30,31) In recent years, the use of microfluidic devices to create organ-on-a-chip models that accurately reproduce organ–organ connections in vitro has gained significant attention.^32,33) If a liver chip carrying CYP2D6*10 KI-HepG2 cells and a breast cancer chip carrying biopsy-derived breast cancer cells from breast cancer patients could be linked to a microfluidic device, it would be possible to predict tamoxifen drug efficacy in vitro in advance.

There have been several reports on the overexpression of CYP2D6*10 in cultured cells,^6,34,35) including HepG2 cells, and assessments of CYP2D6.10 metabolic capacity. Naturally, these reports only assessed CYP2D6 metabolic capacity. CYP2D6*10 KI-HepG2 cells stably express functional CYP1A2, 2C9, 2C19, 2D6*10, 3A4. It would therefore have the potential to be a new model that could predict drug metabolism by multiple drug-metabolizing enzymes and toxicity due to metabolites, taking into account the effects of CYP2D6*10.

To predict the pharmacokinetics of drug candidates in vitro models, it is essential to experiment under conditions that allow the effects of drug transporters as well as drug-metabolising enzymes to be assessed. HepG2 cells express P-glycoprotein [P-gp; ATP binding cassette subfamily B member 1 (ABCB1)], a vital drug transporter for pharmacokinetics, but bile salt export pump [BSEP; ATP binding cassette subfamily B member 11 (ABCB11)] is rarely expressed.³⁶⁾ Therefore, when using HepG2 cells, CYPs-UGT1A1 KI-HepG2 cells or CYP2D6*10 KI-HepG2 cells, care must be taken when assessing drugs excreted by BSEP.

CONCLUSION

We have successfully generated CYP2D6*10 KI-HepG2 cells that express not only functional CYP2D6*10 but also CYP1A2, 2C9, 2C19 and 3A4 at high levels. The CYP2D6*10 KI-HepG2 cells could be a helpful model for liver metabolism and hepatotoxicity studies in East Asians, including Japanese.

Funding

This research was supported by The Nakatomi Foundation and Japan Agency for Medical Research and Development (AMED) (Grant Number: JP21mk0101214), the Mochida Memorial Foundation for Medical and Pharmaceutical Research, Takeda Science Foundation.

Author Contributions

Ryosuke Negoro: Research design, Methodology, Conducted experiments, Data analyses, Funding acquisition, Writing paper, Final approval

Ayu Ouchi: Conducted experiments

Sayaka Deguchi: Primary human hepatocyte culture

Kazuo Takayama: Primary human hepatocyte culture

Takuya Fujita: Discussion

Conflict of Interest

The authors declare no conflict of interest.

Data Availability

The authors declare that all the data related to this study are available within the paper or can be obtained from the authors upon reasonable request.

Supplementary Materials

This article contains supplementary materials.

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