3D hepatic spheroids and liver-organ on chip models displayed maintenance of hepatic functions and maturation profile in a long-term culture of the humanized HepaSH cells, a human cell population harvested from chimeric mice

Hanyuan Wang, Carla Meschini, Stéphane Poulain, Soo Hyeon Kim, Hiroshi Arakawa, Yukio Kato, Cecile Legallais, Ulysse Pereira, Yasuyuki Sakai, Eric Leclerc

► To cite this version:

Hanyuan Wang, Carla Meschini, Stéphane Poulain, Soo Hyeon Kim, Hiroshi Arakawa, et al. 3D hepatic spheroids and liver-organ on chip models displayed maintenance of hepatic functions and maturation profile in a long-term culture of the humanized HepaSH cells, a human cell population harvested from chimeric mice. Biotechnology Progress, 2025, 10.1002/btpr.70043. hal-05109229

HAL Id: hal-05109229

https://hal.science/hal-05109229v1

Submitted on 15 Jun 2025

**HAL** is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire **HAL**, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Public Domain
3D hepatic spheroids and liver-organ on chip models
displayed maintenance of hepatic functions and
maturation profile in a long-term culture of the humanized
HepaSH cells, a human cell population harvested from
chimeric mice.

Hanyuan Wang<sup>1,2+</sup>, Carla Meschini <sup>2,3+</sup>, Stéphane Poulain<sup>4</sup>, Soo Hyeon Kim<sup>2,4</sup>,
Hiroshi Arakawa<sup>5</sup>, Yukio Kato<sup>5</sup>, Cecile Legallais<sup>3</sup>, Ulysse Pereira<sup>3</sup>, Yasuyuki Sakai<sup>1,2</sup>,
Eric Leclerc <sup>2*</sup>

+ authors with equal contributions

1 Department of Chemical System Engineering, graduate school of Engineering, the University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan.

2 CNRS/IIS IRL 2820; Laboratory for Integrated Micro Mechatronic Systems, Institute of Industrial Science, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo, 153-8505, Japan

³ CNRS UMR 7338, Laboratoire de Biomécanique et Bioingénierie, Sorbonne universités, Université de Technologies de Compiègne, France.

⁴ Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba; Meguro-ku;
Tokyo, 153-8505, Japan

⁵ Faculty of Pharmacy, Institute of Medical, Pharmaceutical and Health Sciences,
Kanazawa University, Kanazawa 920-1192, Japan
**Aim:** Long term functional hepatocyte and reproducible cultures are required in pharmaceutical industries to model chronic liver disorders and to perform associated drugs testing. In this frame we have investigated the behavior of the HepaSH cells when cultivated in liver Biochips, in 3D Spheroids and in Petri for 20 days. HepaSH is a newly developed humanized hepatocytes harvested from chimeric mice.

**Methods:** After the cells' harvesting and inoculation, the HepaSH were successfully maintained in cultures in Petri, Spheroids and Biochips for 20 days.

**Results:** The immunostaining confirmed the expressions of albumin, CYP1A2 and CYP3A4 in all conditions. Furthermore, the CYP1A2, CYP2A6, CYP2B6, CYP2C9, CYP2D6, CYP3A4 activities were successfully detected in all conditions after 20 days of cultures. Continuous production of albumin and biliary acids were detected in Biochips, Spheroids and Petri, among which Biochip culture shew highest albumin secretion level. The RNA sequencing analysis revealed that Biochips and Spheroids cultures enriched hepatic maturation, xenobiotic, lipid, small molecule, steroid and alcohol metabolisms compared to Petri cultures.

**Conclusions:** Overall, our data demonstrated the feasibility to cultivate the HepaSH cells in Petri, Biochips and Spheroids for 20 days in the presented protocol, while keeping important liver functions. Biochip and Spheroids cultures shew advantages on hepatic maturation, drug metabolism related genes expression and albumin secretion (in biochips) compared with conventional Petri culture.

**Keywords:** HepaSH, liver, biochips, spheroids, honeycombs, transcriptomic analysis.
# 1. Introduction

Culturing functional hepatocytes for extended periods is crucial for the pharmaceutical industries. Long-term cultures are essential for studying chronic disease, chronic drug therapy, prolonged chemical interactions, and slow metabolic processes (Chen et al., 1998). However, primary hepatocytes tend to lose their functional properties, including cytochrome P450 (CYP450) enzyme activities, relatively quickly (Guguen-Gillouzo et al., 2010). Furthermore, the hepatocyte availability depends on donors' sources and extraction protocols (Solanas et al., 2022), leading to large variability in their performance.

To address these issues, several cellular alternatives using cell engineering were proposed including new advanced cells lines (such as HepaRG cells; Cerec et al., 2007; Nelson et al., 2017; Settivari et al., 2017). However, these immortalized cells can exhibit metabolic variations compared to primary cells (such as differences in the urea cycle for the HepG2, Makris et al., 2024). An alternative strategy has emerged with the development of human induced pluripotent stem cells (hiPSC) -derived hepatocytes (Si-Tayeb et al., 2010; Telles-Silva et al., 2024). However, these cells may lack of some physiological functional levels (Corbett et al., 2019) and require complex, long, costly differentiation protocols, which limits their use in high-throughput screening applications (nevertheless, one recent update showed potential cost reduction via the substitution of growth factors by small chemicals: Vanmarcke et al., 2023).

More recently, a new approach based on the expansion of batches of human primary hepatocytes in chimeric mice (such as PXB cells, FRG cells, HepaSH cells) is opening new perspectives. These cell batches are proposed as a potential alternative to primary human hepatocytes (Zerdoug et al., 2022), while ensuring a quantity, availability, and reproducibility similar to that of cell lines. These cells were produced for liver preclinical drug development (Tateno et al., 2020; Kakuni 2022) and to investigate liver physiological functions (Zerdoug et al., 2022). In this frame, the HepaSH cells were recently developed as an advanced human hepatocyte model (Uehara et al., 2023; Zerdoug et al., 2023). HepaSH cells maintain several critical features of liver cells, such as the expression of CYP450 enzymes and other drug-
metabolizing enzymes, which are essential for studying liver-related processes (Uehara et al., 2023; Zerdoug et al., 2023). Unlike primary hepatocytes, which can exhibit variability due to donor differences and have a limited lifespan in culture, HepaSH cells offered a more stable and reproducible system (Uehara et al. 2023) while supporting longer term cultures.

In addition to progresses in cell engineering, advanced culture methods using bioengineering and material science progresses are proposed to recapitulate the liver architecture and the liver physiology. Various strategies have been proposed to sustain hepatocyte performance, including co-cultures with liver sinusoidal cells, sandwich cultures using Matrigel (Lecluyse et al., 1994). However, the conventional *in vitro* methods often fall short in replicating physiologically relevant conditions, likely because they lack an adequate local microenvironment, particularly in static 2D cultures. Promising approaches to address these limitations involve the usage of advanced micro technologies to build 3D liver spheroids (Shinohara et al., 2017; Brooks et al., 2021; Underhill et al., 2018; Pasqua et al., 2020) and liver-based organ on chip (Ebrahimkhani et al., 2014). These technologies can create a 3D microenvironment and contribute to maintain high level of metabolic performance such as CYP biotransformation (Jellali et al., 2016; Bell et al., 2016). 3D organization of liver cells was also enhanced by these technologies, as well as supporting the co-culture of various liver cell types (Ebrahimkhani et al., 2014; Underhill et al., 2018). In the case of organ on chip, more specifically, flow chambers, bioreactors, and microfluidic biochips have shown potential in partially recreating periportal and pericentral-like profiles in hepatic cells (Allen et al., 2005; Lee-Montiel et al., 2017; Danoy et al., 2023) and allow the continuous waste removal and nutrient supply (Yeon et al., 2007).

As HepaSH is a recently established hepatic model, there is a lack of characterization of this model using advanced bioengineering *in vitro* tools such as organ on chip and 3D spheroids. In this study, we have proposed culture protocols and investigated the behaviour of HepaSH over a culture period of 20 days using liver organ on chip (Biochips), 3D spheroids (Spheroids) and 2D well plate (Petri). We then compared the transcriptome profiles of the HepaSH in those three culture conditions. We particularly focussed our analysis on the mRNA levels of genes involved in the drug metabolisms, lipids and carbohydrates metabolism and the cellular remoulding.
Furthermore, we analysed drug metabolism performance and the production of key
liver biomarkers including albumin and biliary acids between Biochips, Spheroids and
Petri cultures.

**2. Material and methods**

**2.1 Cells and medium**

HepaSH were provided by Kacnet (Japan). The fresh cells were shipped from the supplier (Day -1) at 5x10⁶ cells per vial. The HepaSH were used upon delivery (Day 0) for the experiments (Supplementary File 1, SFig. 1). Three independent batch of the FSSH001 lot were used in this study. Following the supplier recommendation, we used the MIL1330C medium for cell recovery, collection and counting from the transport vial, and the MIL221 medium for seeding. After 24h in the seeding medium (Day 1), we changed for the Takara Cellaris Power Primary Hepatocyte Y20020 medium that was used until the end of the experimental campaign.

**2.2 Biochip cultures**

Biochips made of Polydimethylsiloxane (PDMS) were fabricated according to previously published design and protocol (Baudoin et al., 2007) The construction of the biochips includes two PDMS layers. The bottom layer possesses microstructures for cell attachment, containing a series of microchambers and microchannels inside a larger cell culture chamber. The top layer includes an inlet microchannel network and a chamber to distribute the culture medium homogenously, aiming at closing the chip (Baudoin et al., 2007). The perfusion circuit included the microfluidic biochips, a culture medium bubble trap of 2 mL and a peristaltic pump to maintain a 10 µL/min flow rate perfusion during culture process. Silicone tubes were used to connect each part of the circuit.

The biochips and the perfusion circuits were autoclaved for sterilization. Then biochips were subsequently coated overnight with a collagen solution (1:9 v:v of a collagen solution diluted in water, Nitta Gelatin Inc., Cellmatrix type I-P, a pepsin-solubilized collagen obtained from pig tendons, stock solution at 3mg/mL). The HepaSH cells were inoculated at density of 0.25x10⁶ cells/biochip. Then, before to
start the perfusion culture, the cells were cultured statically for 24h in the seeding
medium in order to ensure full cell attachment. After those 12h, the none attached
were washed with the Takara Cellartis Power Primary Hepatocyte medium and kept
for another 36h at rest (medium refreshed every 12h, overall, it led to 48h of culture in
static condition, at rest, before perfusion). Finally, the biochips were perfused for 18
days using the Takara Cellartis Power Primary Hepatocyte medium. The medium was
changed periodically. Overall, this led to 20 days of experiment.

## 2.3 Honeycomb cultures

We created the 3D Spheroids using the polydimethylsiloxane (PDMS) honeycomb technology developed by Shinohara et al., 2014, 2017. For that purpose, the 126 µm honeycombs array located at the bottom of 24 well plates were precoated with Pluronic F-127 (0.01 g/ml, Wako). After washing with PBS, the cells were inoculated at a density of 2x10⁵ cells per well. We changed the culture medium at similar sequence than in Biochips and Petri leading to 20 days of culture. The total amount of medium in each well was 1mL. To avoid spheroids aspiration by pipetting, only half of the culture media was changed (500 µL).

## 2.4 Petri cultures

Following the supplier recommendation, the Petri were coated with 10% collagen type 1 water solution overnight and washed with MIL221 medium. Then, the cells were inoculated at 0.5x10⁴ cells per well in a 96 multi well plate. The cells were kept in the seeding medium for 24h. Then the cells culture was performed for 19 days in the Takara medium, leading overall to 20 days of culture. The culture medium was renewed periodically as for Spheroids and Biochips cultures.

## 2.5 Immunostaining

Cells in the biochips were fixed by 4% paraformaldehyde (PFA) for 20 min at room temperature, then washed 3 times in PBS and finally stored in PBS at 4°C. Immunostaining was performed on fixed cell samples using two series of primary
antibodies and secondary antibodies (list is provided in Supplementary File 1, STable 1). Cell samples were washed 3 times with 0.2% PBS-Tween (5 min/wash), permeabilized with 0.1% Triton X-100 (PlusOne) for 15 min at room temperature, and washed 3 times with 0.2% PBS-Tween (5min/wash). A blocking step, for 2h, with 3% BSA in 0.2% PBS-Tween, was performed. The primary antibody solution was coated overnight at 4°C (Supplementary File 1, STable 1). The next day, the cells were washed 3 times with 0.2% PBS-Tween (5 min/wash). After washing, the cells were coated overnight in dark at 4°C with secondary antibodies solution. The next day, the cells were washed once more 3 times with 0.2% PBS-Tween (5 min/wash). After this washing, the cells were incubated with DAPI (342-07431, Dojindo) for 10 min. A final washing step was performed with 3 times with 0.2% PBS-Tween (5 min/wash).

The immunostaining images were acquired using a confocal microscope (PowerIX70, Olympus).

## 2.6 Transcriptomics analysis

### 2.6.1 RNA sequencing

Biological replicates derived from independent samples were processed for each experimental condition (n=4 for Biochips, n=3 for Spheroids, n=3 for Petri, n=4 Post extraction). Cell samples were stored in TRIzol™ Reagent (Life Technologies) at the end of each experiment. RNA extraction, library preparation and sequencing were performed by Azenta Life Sciences (Tokyo, Japan). Sequencing libraries were prepared with the Poly(A) mRNA Magnetic Isolation Module (New England Biolabs, Tokyo, Japan) and the NEBNext Ultra II Directional RNA Library Prep Kit for Illumina E7760 (New England Biolabs, Tokyo, Japan). Sample indices were added using NEBNext Multiplex Oligos for Illumina (New England Biolabs, Tokyo, Japan). Multiplexed libraries were sequenced on a NovaSeq 6000 system (Illumina, San Diego, CA, USA) with 150+150bp paired read length (PE150) and at a sequencing depth of over 20M PE reads/sample.
### 2.6.2 Data post treatment

Sequencing data collected for all samples (pairs of demultiplexed FASTQ files) were processed for bulk RNA-seq analysis with the Nextflow workflow system v23.10.1 (Di Tommaso et al., 2017) using the nf-core/rnaseq pipeline v3.14.0 (https://nf-co.re/rnaseq/3.14.0/) (Ewels et al., 2020 and Patel et al., 2024 doi: 10.5281/zenodo.1400710). Default pipeline settings and software parameters were used. Sequencing quality was evaluated based on the MultiQC report (Ewels et al., 2016) created from log files produced by the bioinformatics tools included in the pipeline. Adapter sequences and low-quality bases were trimmed from the reads with Trim Galore (Krueger F, 2015). The STAR aligner (Dobin et al., 2013) was used for mapping sequencing reads on the human reference genome assembly GRCh38 using GENCODE v44/Ensembl 112 annotations. Transcripts were quantified using Salmon (Patro et al., 2017). The output table containing raw expression data for all samples was further uploaded online on the iDEP web server (Ge et al., 2018) (http://bioinformatics.sdstate.edu/idep/) to perform differential gene expression (DGE) analysis. In iDEP the EdgeR:log2(CPM=c) method was used to transform raw transcript counts for exploratory data analysis (nb: this normalization was done using all samples). The DGE analysis was conducted with DESeq2 (Love et al., 2014), applying a false discovery rate cutoff of 0.1 (FDR = 0.1) and a minimum fold change equal to 2 (FC = 2). An additional pathway and gene set enrichment analysis (PGSEA, GSEA) were performed in iDEP using the fold-change values of all genes to identify coherently overall altered pathways with an FDR cutoff fixed at 0.2.

BAM files produced by the rnaseq pipeline and containing aligned sequences for each sample were used as input for Motif Activity Response Analysis (MARA) to identify key transcriptional regulators (TRs). Files were uploaded on the ISMARA web server (Balwierz, et al., 2014) (https://ismara.unibas.ch/mara/) for analysis.

## 2.7 Albumin measurement

The production of albumin by the HepaSH in biochips, Petri and Spheroids was measured via sandwich ELISA assay using anti-Human Albumin IgG (Bethyl, capture
antibody) and anti-Human Albumin IgG coupled with peroxidase (Bethyl, detection
antibody). After revelation of peroxidase using o-phenylenediamine and H₂O₂, the
absorbance data was read by iMark Microplate reader (Bio Rad).

2.8 CYP assay

A drug metabolism assay by cytochrome P450 (CYP) (n≥4) was performed to access the drug biotransformation capabilities. The Biochips, Petri and Spheroids were washed one time by Williams' Medium E (Gibco), then incubated for 1h with Williams' Medium E containing CYP substrate mixture (detailed of the cocktail is given in Supplementary File 1, STable 2), at 37°C, 20% O₂, 5 % CO₂ atmospheric condition. After 1 hour incubation, medium inside each biochip was collected. The collected supernatant samples were mixed with three-times volume of methanol containing the internal standard (imipramine) and centrifuged at 21,500 g for 10 min at 4°C. Metabolite concentrations were then measured via high performance liquid chromatography separation paired with tandem mass spectrometry detection on a LC-30A system equipped with an LCMS8050 triple quadrupole mass spectrometer (both Shimadzu, Japan). The detected mass numbers of the measured compounds were summarized in Supplementary File 1, STable 2. LabSolutions software (Shimadzu) was used for data manipulation.

## 2.9 Biliary acids measurement

Measurement of bile acid concentrations in the culture medium (n≥4) was
performed by LC-MS/MS. The collected sample (50 µL) was mixed with 100 µL of
internal standard (TCA-d4) solution in acetonitrile. After mixing, the solutions were
centrifuged at 21,500 g for 10 min at 4 °C, and the resulting supernatants were injected
into the LC-MS/MS system. The detected mass numbers were summarized at
Supplementary File 1 STable 3. LabSolutions software (Shimadzu) was used for data
manipulation.
## 2.10 Statistical treatment

The concentrations of the albumin, biliary acids and the drugs metabolites were analyzed using GraphPad Prism 9 and ANOVA tests were performed with Tukey's multiple comparison test. The RNA sequencing statistics are described in 2.6.

# 3 Results

**3.1 Morphological analysis displayed hepatocyte phenotypes until 20 days of cultures**

Upon reception, the HepaSH cells were inoculated in the Biochips, in the honeycombs for spheroids formation and in Petri. After 4h at rest in the seeding medium, the HepaSH successfully attached in the Biochips and in the Petri. After 24h, we observed confluent like layers. The cells displayed large and clear nucleus. They also present typical hepatic cuboidal shape (Figures 1A and 1B). In honeycombs, the cells start to aggregate but the spheroids were not completely formed after 24h of culture (Figure 1C). The Spheroids round shape were observed after 48h of culture. We notice a heterogeneity in their diameter. This heterogeneity was remained until the end of the culture and we did not detect any specific growth or over growth of the spheroid when comparing the situation after 48h and day 20 (Supplementary File 1, SFigures 2A and 2B). At the end of the culture, at day 20, the typical hepatic morphologies of the HepaSH, i.e. large nucleus and cuboid shape, were still visualized in Biochips and Petri (Figures 1D and 1E). The tissues were dense along the microchamber walls in the biochip leading to form locally multilayer like structure (Figure 1D). The spheroids presented round shape but as mentioned above they displayed a heterogeneous distribution in their size and diameter (Figure 1F).

**3.2 Immunostaining confirmed protein expression of CYP and ALB protein in Biochips, Spheroids and Petri**

The immunostaining of the important functional hepatic markers, ALB, CYP3A4 and CYP1A2 was performed at the end of the experiments (Figure 2). We confirmed
that the HepaSH expressed those three proteins in Biochips, Spheroids and Petri at
the end of the experiments. From the immunostainings, we did not detect any
particular difference in the investigated models.

3.3 RNA sequencing revealed higher activities of HNF1A_HNF1B, HNF4A and HNF3B transcription regulators in biochips and spheroids when compared to Petri

The ISMARA processing allowed to extract the 131 transcription regulators (TR) motifs significantly activated (with a z_value > 1), when Biochip, Spheroids and Petri samples were compared (Supplementary File 2). Using the z-score (mean activities values divided by the SD values), a one-way ANOVA analysis extracted 301 TR motifs significantly activated with a p_value < 0.05 (Supplementary File 2). We presented the top 50 TRs extracted Supplementary File SFigure 3. Then, we proposed a short list of 29 TR motifs differentially modulated (ANOVA p_value < 0.1, Supplementary File 2) involved in hepatic maturation, lipids and carbohydrates metabolisms, cell cycles and inflammation as shown in Figure. 3. Thus, HNF4A and HNF1B_HNF1A and FOXA1 (HNF3B) were highly activated in Biochips and Spheroids illustrating a higher hepatic maturation when compared to Petri. The Petri and Spheroids displayed higher motif activity of FOXA2 and ONCUT2_ONECUT3. In parallel, CEBPA, AHR_ARNT2, and SREBF2 were more particularly activated in biochips. The cells of the spheroids presented a higher motif activity of NR1I2 (PXR) and NR3C1 (glucocorticoid receptor). The Petri displayed also the highest activities of a cell cycle related transcription regulator (E2F7_E2F1), of the metabolic genes PPARA, HIF1A, RXRG (concomitantly with high activity of MAFA, and FOXO4). Finally, both cells from Petri and Biochip displayed important activities of NKFB2, REL and RELA transcription regulator motifs when compared to cells from Spheroid.

**3.4 The transcriptomic profiles revealed the specificity of each culture models**

As the main purpose of this study is to compare the cells response in long term
*in vitro* cultures, we presently focus our analysis on the comparison of the
transcriptome of Biochips vs Petri, Spheroids vs Petri and Biochips vs Spheroids. The
differentially expressed genes (FC=2, FDR=0.1) are given in Supplementary Files 3, 4 and 5.

Although 2477 and 1382 were differentially expressed in Biochips and in Spheroids, when compared to Petri, both Biochips and Spheroids presented a large similarity in their enrichment profiles. Indeed, using the differentially expressed genes in Biochips and Spheroids, both lists enriched GO biological processes such as xenobiotic metabolism, lipid metabolism, small molecule metabolism, steroid metabolism, alcohol metabolism when compared to Petri (Figures 4A and 4B). This observation was consistent with the higher motif activity of liver transcription regulators (such as HNF4A, HNF1B_HNF1A, FOXA1, SREBF1_TFE3, SREBF2, ESRRA_ESR2) in Biochips and Spheroids when compared to Petri). In parallel Petri culture enriched extracellular matrix organization, blood and vasculature development, external encapsulation (Figures 4A and 4B).

To refine our analysis, we created a heatmap of expression for a short list of genes involved in the drug metabolism that were found differentially expressed in Biochips and Petri in Figure 5A (data extracted from Supplementary File 3). Major phase I metabolism genes, (such as CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9 and CYP3A4), several phase II metabolism genes (such as UGT1A1, UGT1A7, UGT1A9, SULT1A1, SULT1A2) were highly expressed in Biochips (n.b. CYP1A2, CYP2A6, CYP2B6, CYP2C9, CYP3A4, UGT1A7, UGT1A9, SULT1A1 were also differentially over expressed in Spheroids when compared to Petri, Supplementary File 4). Transporters involved in the multi drug resistance such as ABCB1, ABCB6, ABCC4 were also upregulated in Biochips (ABCA3, ABCA8 in Spheroids vs Petri Supplementary File 4).

Then, we presented in Figure 5B, a heatmap of a selected genes list involved in the extracellular matrix organization, the blood vessel development and in the TGFβ signaling (data extracted from Supplementary File 3). The cells in Biochips particularly expressed higher level of laminin genes (LAMA3 and LAMA4) when compared to Petri. The cells in Petri over expressed collagen genes (such as COL1A1, COL1A2, COL2A1, COL3A1, COL6A5. n.b those 5 genes were also upregulated in Petri vs Spheroids, Supplementary File 4) and blood vessel development genes (such as ENG, THBS2, PDGFRB, ANGPT4, ICAM5 that were commonly up regulated in Petri vs Biochips and Petri vs Spheroids, Figure 5B, Supplementary Files 3 and 4). In parallel,
the mRNA levels of SMAD6, SMAD7, BMP6, TGFBR1, TGFBR3 genes, involved in
TGFβ signaling were upregulated in the cells cultivated in Petri compared to Biochips
(n.b. cells in Petri showed the upregulated expressions of SMAD7, BMP2, BMP5 and
TGFBR3 when compared to Spheroids, Supplementary File 4).

The comparison of the Biochips and Spheroids conditions contributed to extract
the specificity of both culture modes. We found that 687 genes were differentially
expressed (FDR = 0.1, FC = 2, Supplementary File 5). Among them, the cells in
Spheroids expressed higher mRNA levels of mitochondrial genes (MTCO1P52,
MTCO1P35, MTCYBP31, MTCO2P17, NDUFA4L2) and of the glycolysis genes
(ENO2, PFKFB1, MAFB) depicting a probable increase in the OXPHOS respiration.
Furthermore, the Spheroids presented an upregulation of extra cellular matrix related
genes such as FBLN2, COL3A1, COL1A2, LUM, COL6A5 genes when compared to
Biochips. Conversely Biochips expressed higher levels of PCK1 illustrating a probable
gluconeogenesis status. In parallel, the cells in the Biochips expressed higher mRNA
level of cytokine and interleukin genes. In addition, the cell cycle genes CDK1, CCND1,
CCNE1 were upregulated in Biochips. A selection of differentially expressed genes
between the two culture conditions is presented in Figure 6A.

Overall, the 687 differentially expressed genes listed in this dataset enriched
biological processes related to ions and collagen in Spheroids whereas Biochips
overexpressed genes involved in response to cytokines and external stimuli. The
clustering tree of the enriched GO_Biological Processes is presented in Figure 6B.

## 3.5 Functional analysis confirmed hepatic and metabolic functions

Finally, we compared the metabolic performances of the cells when cultivated
in Petri, Biochips and Spheroids (Figure 7). The albumin was successfully secreted in
all conditions. However, we found a larger production in the biochips when compared
to Petri and Spheroids at day 20 (Figure 7A). Thus, at the end of the culture we
reached 65.4±51.3; 11.8±6.7; and 5.1±1.9 µg/day/10⁶ inoculated cells respectively.

We confirmed that the cells cultivated in Biochips, Petri and Spheroids were
able to metabolize well-known drug substrates, demonstrating the functionality of
CYP1A2, CYP2A6, CYP2B6, CYP2C9, CYP2D6 and CYP3A4 (Figure 7B). CYP1A2 activity was higher in Biochips and Spheroids when compared to Petri. No statistical difference was measured for the CYP2A6, CYP2B6, CYP2C9, CYP2D6. However, we found higher CYP3A4 activity in Petri as far as the cells culture in the Petri conditions more largely produced 1'-OH midazolam when compared to Biochips and Spheroids cultures. Furthermore, for all model, the CYP2C8 and CYP2C19 were not active as far as we did not detect clear secretion (or very dispersed) of N-Desethylamodiaquine and 4'-OH mephenytoin respectively.

We also measured the productions of the biliary acids, namely cholic acid (CA), chenodeoxycholic acid (CDCA) and their taurine and glycine conjugates (TCA, TCDCA, GCA, GCDCA, respectively) in our culture medium samples at day 12 and day 19 (Figures 7C and 7D). The levels of secretions were not statistically different between all conditions for the CA, CDCA, TCA, TCDCA, GCDCA biliary acids. However, the glycine conjugation of CA (GCA) appeared more active in Spheroids when compared to Petri and Biochips.

## 4 Discussion

The purpose of this work was to confirm the possibility of long-term *in vitro* culture of HepaSH inside honeycombs to create 3D spheroids and inside liver biochips to build HepaSH based organ on chip. As HepaSH cells are a newly establish cell model, we seek out feasibility and potential advantage of novel culture models by comparing functionality performances with conventional 2D Petri culture. Our overall data set demonstrated the HepaSH successful cultures in biochips and spheroids. After, 20 days of culture, the HepaSH were able to produce albumin, biliary acids and to metabolize drugs. To be able to establish a stable protocol, we kept using a single type and a single lot of HepaSH to avoid cellular variability. As a result, we reduced our dependance on the cell source to better establish the conditions for the cell adhesion step, the cell capability to form spheroids, and the cell response to the dynamic cultures in biochips. Indeed, those steps are critical steps to build new and relevant protocol using those complex *in vitro* system with newly developed and marketed cells. Consequently, the present protocol would need to be extended to a broader range of HepaSH sources.
Nevertheless, our protocol allowed to compare the basal liver function in biochip or spheroids with literature data that are using primary human hepatocytes. The present albumin secretions reached up to 65.4±51.3 and 11.8±6.7 µg/day/10⁶ inoculated cells in biochip and 3D spheroids respectively. The HepaSH biochip values appeared in similar range than our human primary hepatocytes data (~270 to 1000 ng/h/10⁶ cells for cryopreserved hepatocytes, Jellali et al., 2016), of other perfused bioreactor (about 10 µg/day/10⁶ cells in Tostoes et al., 2012; 0.3 to 0.8 pg/h/10⁶ cells in Torok et al., 2011), and of primary rat hepatocyte biochip secretions (Legendre et al., 2013). In parallel, the secretion in the 3D spheroids HepaSH were in the range of literature data of human primary hepatocytes (ranging from 7 to 30 pg/day/hepatocytes in Riede et al., 2021 for spheroids). Furthermore, those values were larger than the range of estimated human in vivo albumin secretion (0,742 pg/h/hepatocytes, Torok et al., 2011) illustrating the basal performance of the present new culture models. A tentative synthetic table is provided in Supp File 1.

Then, we have characterized the transcriptome profile of the cells when cultivated in Biochips, Spheroids, Petri. The Spheroids, and Biochips commonly presented an expression profile with higher motifs activities of important hepatic transcription factors (HNF1A_HNF1B, HNF4A and HNF3B). At the transcriptomic levels, it was associated with a modulation of genes enriching drug metabolism when compared to Petri. Similar mRNA upregulations with hepatic cells lines, primary human hepatocytes and primary rat hepatocytes were previously observed in our biochips when compared to Petri cultures (Prot et al., 2012; Baudoin et al., 2014; Jellali et al., 2016). The upregulations of proteins and genes involved in the drug metabolism in primary hepatocytes or advanced cell lines Spheroids are also largely reported in the literature (Bell et al., 2016; Berger et al., 2016). To extract specificity of Biochips and Spheroids cultures, the differentially expressed genes in Spheroid models may come from its hypoxic profile, indicating different oxygen supply situations between spheroids and biochips (up regulation of glycolytic genes ENO2, PFKFB1, MAFB and various mitochondrial ones in spheroids, versus PCK1 a gluconeogenesis gene in biochips, nb glycolysis/glucogeneosis are oxygen dependent profile, Cunningham et al., 2021). Biochips were totally fabricated by oxygen permeable material PDMS and possessed perfused medium fluid during culture process, leading to richer oxygen supply than Spheroids model. In parallel, the Biochips and Spheroids cultures, process
analysis revealed up regulated copper and zinc ion metabolisms within Spheroids.
Copper ion was reported to be associated with HIF-1 (hypoxia-inducible factor) (Falk
Martin et al. 2005). Besides, Copper & Zinc ion are involved in regulation of lipid &
glucose metabolism (Olechnowicz J et al. 2017), leading to assume a specific way for
spheroids to adapt their metabolism.

Furthermore, the present work confirmed the functional CYP1A2, CYP2A6, CYP2B6, CYP2C9, CYP2D6, CYP3A4 capabilities. However, we did not detect a metabolism for the CYP2C8 and CYP2C19. Despite the upregulation of drug metabolism genes at the transcriptome level in Biochips and Spheroids (when compared to Petri), we did not measure a better drug metabolism in the spheroids and biochips when compared to Petri (on contrary to what was largely reported in our biochips and in spheroids literatures with hepatic cells lines and primary hepatocytes, Prot et al., 2012; Baudoin et al., 2014; Jellali et al., 2016; Bell et al., 2016; Berger et al., 2016). Furthermore, the metabolic performances appeared lower than some of the ones of the literature using human primary hepatocytes. For instance, typical results for suspension, spheroids or biochips of 1-OH Midazolam secretions ranged from 17 to 1000 pmol/min/10⁶ cells (comparative data are provided in Supp. Table 5 in Supp. File 1, Hallifax et al. 2005; Berger et al., 2016; Kukla et al., 2024; Ohri at al., 2025). Several hypotheses can be proposed to explain those results. Firstly, the diversity of the protocols makes difficult a direct comparison (due to various reported time points, time of drug incubation, cells pre-induction, substrates concentrations, intracellular metabolites recovery, etc...). In our case, we checked the metabolism after 20 days of culture, whereas most of reported values correspond to either post thawing situation or shorter culture time points. Secondly, we used PDMS as material for the biochips and for the honeycombs housing the 3D spheroids in which non-specific adsorption of the drugs' substrates and metabolites is expected (Prot et al., 2011; van Meer et al., 2017; Nishikawa et al., 2022). Thirdly, we did not address the full phase II metabolisms, and the UGT/SULT activities can generate drug conjugated that were not presently measured (and we did stop those reactions with salicylamide). We can hypothesize that if the advanced maturation profile of HepaSH was maintained in Biochips, Petri and Spheroids, then it led to the necessity to address also this phase II metabolism. Furthermore, CYP activities are depending on cell polymorphism and genetic pattern of the donors (Zanger et al., 2013) leading to the necessity of checking not only other sources of HepaSH but also a spectrum of primary human hepatocytes for
comparative purpose. As a result, additional investigations would be required to get
larger screening comparisons of the metabolic performance of human primary
hepatocytes and the HepaSH cells.

Finally, up to date, there is no available data on the metabolic performance of HepaSH in long term complex *in vitro* culture. Nevertheless, in suspension, post extraction, the metabolic performances of freshly isolated HepaSH were reported to roughly range from 20 to 125 pmol/min/10⁶ cells, from 10 to 150 pmol/min/10⁶ cells from 20 to 80 pmol/min/10⁶ cells, from 250 to 1000 pmol/min/10⁶ cells, from 20 to 40 pmol/min/10⁶ cells for CYP1A2, CYP2B6, CYP3A4/5, CYP2C9, and CYP2D6 respectively (Uehara et al., 2023). Those performance were higher that similar control in a pool of primary hepatocyte comparison (Uehara et al., 2023) demonstrating the HepaSH interest. Furthermore, those HepaSH performances are in the range of our day 20 analysis for CYP1A2 (Petri, Biochip, 3D spheroids), and for Petri CYP3A4. However, as they are higher than our other measurements for other CYP450, this illustrated the importance of additional primary control in our studies. Finally, theses comparison demonstrated that our protocols, even if encouraging, still need to further development (such as culture medium optimization, liver non-parenchymal cell cocultures, assays optimization) to maintain *in vitro* the full capability of the *in vivo* like post extraction metabolism of HepaSH in organ on chip and 3D models.

**5 Conclusion**

In summary, we have investigated the behavior of HepaSH cells when cultivated in Biochips, Spheroids and Petri. The transcriptome of the Biochips and Spheroids presented large similarities when compared to Petri culture of HepaSH. Commonly, Biochips and Spheroids conditions presented higher expression of several important hepatic transcription regulators and typical genes required for drug metabolism. We successfully confirmed the metabolic performance in term of albumin production, biliary acids secretion and CYP biotransformation in Biochips, Spheroids and Petri. The albumin secretion was higher in biochips after 20 days of cultures. The glycine conjugation of cholic acid was found higher in Spheroids. CYP1A2 functionality was found higher in Biochips and Petri but CYP3A4 metabolism was higher in Petri. Although additional analyses are required to confirm several functional performances
(such as primary cell controls, cell polymorphism and phase II metabolism), these
results demonstrated the potential of the Biochips and Spheroids conditions to
investigate hepatic biology over long-term cultures using the newly developed
HepaSH models.

## 6 Acknowledgements

Wang Hanyuan's was supported by the CNRS/University of Tokyo joint PhD program. The work was carried out in the framework of the Research Training Innovation Chair, DOT project - Disruptive Organoids Technologies, action funded by the Research Department of the Université de Technologie de Compiègne. Carla Meschini's PhD funding was supported by the Région des Hauts-de-France (1/2) and DOT Chair (1/2). A part of the project was supported by the JSPS grant-in-aid for scientific research B (22H03934). We thank the CNRS/IIS LIMMS IRL 2820 for its financial support through the LIMMS internal projects 2021 and 2023 between the Kim and Sakai laboratories.

## 7 Ethical issues

No ethical approval was required for the work presented in this study.

## 8 Conflict of interest

We declare no conflict of interest for this study.

## 9 Data availability

Data are provided in supplementary files.

## 10 References

Allen, Jared W., Salman R. Khetani, and Sangeeta N. Bhatia. "In vitro zonation and toxicity in a hepatocyte bioreactor." *Toxicological sciences* 84.1 (2005): 110-119.
Baudoin R, Alberto G, Legendre A, Paullier P, Naudot M, Fleury MJ, Jacques S Griscom L, and Leclerc E. Investigation of the levels of expression and activity of detoxication genes of primary rat hepatocytes under various flow rates and cell densities in microfluidic biochips, Biotechnology Progress, 30: 401–410, 2014

Bell, C., Hendriks, D., Moro, S. et al. Characterization of primary human hepatocyte spheroids as a model system for drug-induced liver injury, liver function and disease. *Sci Rep* 6, 25187 (2016)

Bell CC, Dankers ACA, Lauschke VM, Sison-Young R, Jenkins R, Rowe C, Goldring CE, Park K, Regan SL, Walker T, Schofield C, Baze A, Foster AJ, Williams DP, van de Ven AWM, Jacobs F, Houdt JV, Lähteenmäki T, Snoeys J, Juhila S, Richert L, Ingelman-Sundberg M. Comparison of Hepatic 2D Sandwich Cultures and 3D Spheroids for Long-term Toxicity Applications: A Multicenter Study. Toxicol Sci. 2018 Apr 1;162(2):655-666.

Berger B, Donzelli M, Maseneni S, Boess F, Roth A, Krähenbühl S, Haschke M. Comparison of Liver Cell Models Using the Basel Phenotyping Cocktail. Front Pharmacol. 2016 Nov 21;7:443.

Brooks A, Liang X, Zhang Y, Zhao CX, Roberts MS, Wang H, Zhang L, Crawford DHG. Liver organoid as a 3D in vitro model for drug validation and toxicity assessment. Pharmacol Res. 2021 Jul;169:105608.

Chen HL, Wu HL, Fon CC, Chen PJ, Lai MY, Chen DS, Long-term culture of hepatocytes from human adults, *J Biomed Sci.* 1998; 5:435-440.

Chen J, Zhao KN, Chen C. The role of CYP3A4 in the biotransformation of bile acids and therapeutic implication for cholestasis. Ann Transl Med. 2014 Jan;2(1):7.

Cerec, V. et al. Transdifferentiation of hepatocyte-like cells from the human hepatoma HepaRG cell line through bipotent progenitor. Hepatology 45(4), 957–967. (2007).
Corbett JL, Duncan SA. iPSC-Derived Hepatocytes as a Platform for Disease Modeling and Drug Discovery. Front Med (Lausanne). 2019 Nov 15;6:265.

Cunningham RP, Porat-Shliom N. Liver Zonation - Revisiting Old Questions With New Technologies. Front Physiol. 2021 Sep 9;12:732929.

Danoy M, Poulain S, Jellali R, Scheidecker B, Tauran Y, Leduc M, Bruce J, Kim SH, Kido T, Miyajima A, Sakai Y, Leclerc E, Transcriptomic and proteomic studies suggest the establishment of advanced zonation like profiles in human induced pluripotent stem cells derived liver sinusoidal endothelial cells and carboxypeptidase M positive liver progenitor cells cocultured in a fluidic microenvironment, Hepatology research, 53, 661, 2023

Davidson, M., Ballinger, K. & Khetani, S. Long-term exposure to abnormal glucose levels alters drug metabolism pathways and insulin sensitivity in primary human hepatocytes. *Sci Rep* 6, 28178 (2016).

Di Tommaso P, Chatzou M, Floden EW, Barja PP, Palumbo E, Notredame C. 2017. Nextflow enables reproducible computational workflows. Nat Biotechnol 35: 316–319.

Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR. STAR: ultrafast universal RNA-seq aligner Bioinformatics. 2013 Jan 1;29(1):15-21

Ebrahimkhani, M.R., Neiman, J.A.S., Raredon, M.S.B., Hughes, D.J. and Griffith, L.G., 2014. Bioreactor technologies to support liver function in vitro. *Advanced drug delivery reviews*, 69, pp.132-157.

Ewels PA, Magnusson M, Lundin S, Käller M, MultiQC: summarize analysis results for multiple tools and samples in a single report, *Bioinformatics*, Volume 32, Issue 19, October 2016, Pages 3047–3048.
Ewels PA, Peltzer A, Fillinger S, Patel H, Alneberg J, Wilm A, Garcia MU, Di Tommaso P, Nahnsen S. The nf-core framework for community-curated bioinformatics pipelines. *Nat Biotechnol.* 2020 Mar;38(3):276-278.

Ge, S.X., Son, E.W. and Yao, R., 2018. iDEP: an integrated web application for differential expression and pathway analysis of RNA-Seq data. *BMC bioinformatics*, 19(1), pp.1-24.

Guguen-Guillouzo C, Guillouzo A., General Review on In Vitro Hepatocyte Models and Their Applications. *In Hepatocytes; Methods in Molecular Biology; Humana Press: Totowa, NJ, USA*, 2010; 640: 1-40.

Hu N, Hu M, Duan R, Liu C, Guo H, Zhang M, Yu Y, Wang X, Liu L, Liu X. Increased levels of fatty acids contributed to induction of hepatic CYP3A4 activity induced by diabetes - in vitro evidence from HepG2 cell and Fa2N-4 cell lines. *J Pharmacol Sci.* 2014;124(4):433-44. doi: 10.1254/jphs.13212fp. PMID: 24739263.

Jellali R, Bricks T, Jacques S, Fleury MJ, Paullier P, Merlier F, Leclerc E, Long term human primary hepatocyte cultures in a microfluidic liver biochip show maintenance of mRNA levels and higher drugs metabolisms when compared to Petri cultures, *Biopharm Drug dispo*, 5:264-275, 2016

Kakuni M. Freshly Isolated Hepatocytes from Chimeric Humanized Liver Mice for the In Vitro Assessment of Drug Metabolism, Inhibition/Induction, and Safety Studies. *Curr Protoc. 2022 May;2(5):e429.*

Krueger, F. Trim galore: a wrapper tool around Cutadapt and FastQC to consistently apply quality and adapter trimming to FastQ files. (2015); https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/

LeCluyse EL, Audus KL, and Hochman JH, Formation of extensive canalicular networks by rat hepatocytes cultured in collagen-sandwich configuration. *Am J Physiol*, 1994; 266: C1764-C1774.
Lee-Montiel, F.T., George, S.M., Gough, A.H., Sharma, A.D., Wu, J., DeBiasio, R., Vernetti, L.A. and Taylor, D.L., 2017. Control of oxygen tension recapitulates zone-specific functions in human liver microphysiology systems. *Experimental Biology and Medicine*, 242(16), pp.1617-1632.

Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. *Genome Biol.* **15**, 1-21 (2014).

Lu J, Shang X, Yao B, Sun D, Liu J, Zhang Y, Wang H, Shi J, Chen H, Shi T, Liu M, Wang X. The role of CYP1A1/2 in cholesterol ester accumulation provides a new perspective for the treatment of hypercholesterolemia. Acta Pharm Sin B. 2023 Feb;13(2):648-661.

Makris G, Veit L, Rüfenacht V, Klassa S, Zürcher N, Matsumoto S, Poms M, Häberle J. Expression and function of the urea cycle in widely-used hepatic cellular models. J Inherit Metab Dis. 2024, doi: 10.1002/jimd.12701.

Martin F, Linden T, Katschinski DM, Oehme F, Flamme I, Mukhopadhyay CK, Eckhardt K, Tröger J, Barth S, Camenisch G, Wenger RH. Copper-dependent activation of hypoxia-inducible factor (HIF)-1: implications for ceruloplasmin regulation. Blood. 2005 Jun 15;105(12):4613-9.

Minegishi G, Kobayashi Y, Fujikura M, Sano A, Kazuki Y, Kobayashi K. Induction of hepatic CYP3A4 expression by cholesterol and cholic acid: Alterations of gene expression, microsomal activity, and pharmacokinetics. *Pharmacol Res* *Perspect*. 2024; 12:e1197.

Nelson LJ, Morgan K, Treskes P, Samuel K, Henderson CJ, LeBled C, Homer N, Grant MH, Hayes PC, Plevris JN. Human Hepatic HepaRG Cells Maintain an Organotypic Phenotype with High Intrinsic CYP450 Activity/Metabolism and Significantly Outperform Standard HepG2/C3A Cells for Pharmaceutical and Therapeutic Applications. Basic Clin Pharmacol Toxicol. 2017 Jan;120(1):30-37.
Nishikawa M, Ito H, Tokito F, Hirono K, Inamura K, Scheidecker B, Danoy M, Kawanishi T, Arakawa H, Kato Y, Esashika K, Miyasako H, Sakai Y. Accurate Evaluation of Hepatocyte Metabolisms on a Noble Oxygen-Permeable Material With Low Sorption Characteristics. Front Toxicol. 2022 Jun 6;4:810478.

Olechnowicz J, Tinkov A, Skalny A, Suliburska J. Zinc status is associated with inflammation, oxidative stress, lipid, and glucose metabolism. J Physiol Sci. 2018 Jan;68(1):19-31.

Pasqua M, Pereira U, Messina A, de Lartigue C, Vigneron P, Dubart-Kupperschmitt A, Legallais C. HepaRG Self-Assembled Spheroids in Alginate Beads Meet the Clinical Needs for Bioartificial Liver. Tissue Eng Part A. 2020 Jun;26(11-12):613-622.

Patel et al., 2024, nf-core/rnaseq: nf-core/rnaseq v3.15.1 - Augmented Aluminium Axolotl, Zenodo, doi: 10.5281/zenodo.1400710

Patro R, Duggal G, Love MI, Irizarry RA, Kingsford C. Salmon provides fast and bias-aware quantification of transcript expression. Nature methods. 2017 Apr;14(4):417-9.

Prot J-M, Videau O, Brochot C, Legallais C, Bénech H, Leclerc E, A cocktail of metabolic probes demonstrates the relevance of primary human hepatocyte cultures in a microfluidic biochip for pharmaceutical drug screening, International Journal of pharmaceutics, 408, 67-75, 2011

Riede J, Wollmann B, Molden E, Ingelman-Sunderg M, Primary Human Hepatocyte Spheroids as an In Vitro Tool for Investigating Drug Compounds with Low Hepatic Clearance, Drug Metabolism and Disposition, 49: 7, 501 – 508, 2021

Settivari R.S, J.C. Rowlands J.C, D.M. Wilson D.M., Arnold S.M, Spencer P.J., Chapter 32 - Application of Evolving Computational and Biological Platforms for Chemical Safety Assessment, Editor(s): Ali Said Faqi, A Comprehensive Guide to Toxicology in Nonclinical Drug Development (Second Edition), Academic Press, 2017, Pages 843-873,
Shinohara, M., Kimura, H., Montagne, K., Komori, K., Fujii, T., Sakai, Y., 2014.
Combination of microwell structures and direct oxygenation enables efficient and size-
regulated aggregate formation of an insulin-secreting pancreatic beta-cell line.
Biotechnol. Prog. 30, 178-187.

Shinohara, M., Komori, K., Fujii, T., Sakai, Y., 2017. Enhanced self-organization of size controlled hepatocytes aggregates on oxygen permeable honeycomb microwell sheets. Biomed. Phys. Eng. Express. 3, 045016.

Si-Tayeb K, Noto FK, Nagaoka M, Li J, Battle MA, Duris C, North PE, Dalton S, Duncan SA. Highly efficient generation of human hepatocyte-like cells from induced pluripotent stem cells. Hepatology. 2010 Jan;51(1):297-305

Solanas E, Sanchez-Fuentes N, Serrablo A, Lue A, Lorente S, Cortés L, Lanas A, Baptista PM, Serrano MT. How Donor and Surgical Factors Affect the Viability and Functionality of Human Hepatocytes Isolated From Liver Resections. Front Med (Lausanne). 2022 May 11;9:875147.

Tateno C, Kojima Y. Characterization and applications of chimeric mice with humanized livers for preclinical drug development. Lab Anim Res. 2020 Jan 8;36:2.

Telles-Silva KA, Pacheco L, Chianca F, Komatsu S, Chiovatto C, Zatz M, Goulart E. iPSC-derived cells for whole liver bioengineering. Front Bioeng Biotechnol. 2024 Feb 7;12:1338762.

Török E, Lutgehetmann M, Bierwolf J, Melbeck S, Düllmann J, Nashan B, Ma PX, Pollok JM. Primary human hepatocytes on biodegradable poly(I-lactic acid) matrices: a promising model for improving transplantation efficiency with tissue engineering. Liver Transpl. 2011, 17(2):104-14

Tostoes R, Leite S, Serra M, et al. Human liver cell spheroids in extended perfusion bioreactor culture for repeated-dose drug testing. Hepatology 2012; 55: 1227-1235.
Uehara S, Higuchi Y, Yoneda N, Ito R, Takahashi T, Murayama N, Yamazaki H, Murai K, Hikita H, Takehara T, Suemizu H. HepaSH cells: Experimental human hepatocytes with lesser inter-individual variation and more sustainable availability than primary human hepatocytes. *Biochem Biophys Res Commun.* 2023 Jun 30;663:132-141.

Underhill, G.H. and Khetani, S.R., 2018. Bioengineered liver models for drug testing and cell differentiation studies. *Cellular and molecular gastroenterology and hepatology*, 5(3), pp.426-439.

Vanmarcke G, Sai-Hong Chui J, Cooreman A, De Vos K, Cleuren L, Van Rossom R, García-Llorens G, Izuel Idoype T, Boon R, Kumar Gautam M, Castell JV, Annaert P, Lluis F, Verfaillie CM. Automated Generation of hiPSC-Derived Hepatic Progeny by Cost-Efficient Compounds. *Stem Cells*. 2023 Nov 5;41(11):1076-1088.

van Meer BJ, de Vries H, Firth KSA, van Weerd J, Tertoolen LGJ, Karperien HBJ, Jonkheijm P, Denning C, IJzerman AP, Mummery CL. Small molecule absorption by PDMS in the context of drug response bioassays. *Biochem Biophys Res Commun.* 2017 Jan 8;482(2):323-328.

Yeon JH, Park JK, Microfluidic cell culture systems for cellular analysis, *BioChip J.* 2007 ; 1: 17-27

Zanger U, Schwab M, Cytochrome P450 enzymes in drug metabolism: Regulation of gene expression, enzyme activities, and impact of genetic variation, Pharmacology & Therapeutics, Volume 138, Issue 1, 2013, Pages 103-141,

Zerdoug, A., Le Vée, M., Uehara, S. et al. Contribution of Humanized Liver Chimeric Mice to the Study of Human Hepatic Drug Transporters: State of the Art and Perspectives. *Eur J Drug Metab Pharmacokinet* 47, 621-637 (2022).

Zerdoug A, Le Vée M, Uehara S, Jamin A, Higuchi Y, Yoneda N, Lopez B, Chesné C, Suemizu H, Fardel O. Drug transporter expression and activity in cryopreserved human hepatocytes isolated from chimeric TK-NOG mice with humanized livers. *Toxicol In Vitro*. 2023 Aug;90:105592.
<figure><img src="image_1.png" /><figcaption>**Figure 1:** HepaSH morphologies after 24h of cultures in biochips (A), in Petri (B) in honeycombs forming spheroids (C) and after 20 days of cultures in biochips (D), in Petri (E) in honeycombs with spheroids (F)</figcaption></figure>
<figure><img src="image_2.png" /><figcaption>**Figure 2:** Immunostaining of the expression of the albumin, CYP3A4 and CYP1A2 at day 20 of the cells cultivated in Biochips, Petri and Spheroids</figcaption></figure>
<figure><img src="image_3.png" /><figcaption>**Figure 3:** Heatmap of selected transcription regulators differentially activated in Biochips, Spheroids and Petri.</figcaption></figure>
<figure><img src="image_4.png" /><figcaption>**Figure 4:** (A) Enriched biological process by the top genes differentially expressed between the Petri and Biochips; (B) Enriched biological process by the top genes differentially expressed between the Petri and Spheroids;</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>**Figure 5:** (A) Heatmap of selected genes involved in the xenobiotic metabolism and drugs transport. (B) Heatmap of selected genes involved in the extracellular matrix processing and TGFβ signalling</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>**Figure 6:** (A) Heatmap of selected genes highlighting the specificity of the Biochips and Spheroids signatures (B) Enriched biological process by the 687 genes differentially expressed between the Spheroids and Biochips.</figcaption></figure>
<figure><img src="image_7.png" /><figcaption>**Figure 7:** (A) Kinetics of albumin secretion; (B) Drug metabolism capability assessed at day 20; (C) Biliary secretion assessed at day 12; (D) Biliary secretion assessed at day 19;</figcaption></figure>

**** p_value < 0.0001; * p_value < 0.05