Alessia
Paradiso†
a,
Marina
Volpi†
a,
Chiara
Rinoldi
b,
Nehar
Celikkin
c,
Nicola
Contessi Negrini
d,
Muge
Bilgen
c,
Giorgio
Dallera
d,
Filippo
Pierini
b,
Marco
Costantini
c,
Wojciech
Święszkowski
*a and
Silvia
Farè
*de
aFaculty of Materials Science and Engineering, Warsaw University of Technology, Warsaw, Poland. E-mail: wojciech.swieszkowski@pw.edu.pl
bInstitute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland
cInstitute of Physical Chemistry, Polish Academy of Sciences, Warsaw, Poland
dDepartment of Chemistry, Materials and Chemical Engineering “G. Natta”, Politecnico di Milano, Milan, Italy. E-mail: silvia.fare@polimi.it
eINSTM, National Consortium of Materials Science and Technology, Local Unit Politecnico di Milano, Milan, Italy
First published on 29th November 2022
Liver is one of the most important and complex organs in the human body, being characterized by a sophisticated microarchitecture and responsible for key physiological functions. Despite its remarkable ability to regenerate, acute liver failure and chronic liver diseases are major causes of morbidity and mortality worldwide. Therefore, understanding the molecular mechanisms underlying such liver disorders is critical for the successful development of novel therapeutics. In this frame, preclinical animal models have been portrayed as the most commonly used tool to address such issues. However, due to significant species differences in liver architecture, regenerative capacity, disease progression, inflammatory markers, metabolism rates, and drug response, animal models cannot fully recapitulate the complexity of human liver metabolism. As a result, translational research to model human liver diseases and drug screening platforms may yield limited results, leading to failure scenarios. To overcome this impasse, over the last decade, 3D human liver in vitro models have been proposed as an alternative to pre-clinical animal models. These systems have been successfully employed for the investigation of the etiology and dynamics of liver diseases, for drug screening, and – more recently – to design patient-tailored therapies, resulting in potentially higher efficacy and reduced costs compared to other methods. Here, we review the most recent advances in this rapidly evolving field with particular attention to organoid cultures, liver-on-a-chip platforms, and engineered scaffold-based approaches.
To date, in vitro liver models have gained popularity due to the liver's critical role in various physiological processes – such as the regulation of fat metabolism, long-term mineral and vitamin storage, detoxification, and monitoring of innate and adaptive immunity – and increased mortality rates in the event of liver failure. Recent statistics, in fact, have shown that acute liver failure and chronic liver diseases (CLD) represent major causes of morbidity and death worldwide, causing approximately 2 million deaths (3.5% of total deaths) annually. Unfortunately, these figures are expected to continue rising due to the increasing obesity rate and alcohol consumption.9 As a result, understanding the molecular mechanisms underlying liver function and failure is critical for developing novel therapeutic strategies.
From a cellular and architectural point of view, the liver is shaped in a unique micro- and macro-architecture containing a variety of specialized cell types. Hepatocytes constitute the primary cell population fulfilling most of the liver functions. Other cell types include Kupffer cells, stellate cells, endothelial cells, and lymphocytes.10,11 Regarding its native architecture, the liver is microscopically arranged into hexagonal spatial units called lobules where hepatocytes line up in radial cords, separated by sinusoid branches of microvascular channels (Fig. 1). Such unique spatial and heterogeneous cellular organization generate a graded microenvironment enabling various metabolic functions to simultaneously occur in localized zones of the lobule.12 Another notable feature of the liver is its extraordinary regenerative capacity which allows vulnerable liver tissue to be fully replaced upon re-organization of the heterogeneous cell population – in particular hepatocytes and epithelial cells – restoring the hepatic functions required for body homeostasis.13–15
Without a doubt, thoroughly recapitulating such complex biological processes within an in vitro liver model is currently out of our possibilities. Nevertheless, several in vitro assays and pre-clinical animal models have been developed to study further the liver's physiological functions, biomolecular mechanisms, and pathology development.16–20 Among in vitro models, 2D monolayer cultures (2DMCs) have been the most commonly used strategies due to their cost-efficacy, reproducibility, ease-to-perform, and easy-to-scale protocols.21 Despite the significant advantages of 2DMC, they also exhibit several limitations. For instance, the evaluation of specific hepato-functionality is possible only in short-term studies (e.g., 24–48 h) as cells progressively tend to lose their polarity and dedifferentiate into fibroblast-like cells.22,23 Along with 2DMCs, animal and humanized animal models are also relevant tools for modeling liver disease and accessing drug discovery processes. In this frame, rodents have been conventionally used for research and development purposes. However, such models cannot thoroughly recapitulate human liver architecture and functions, being thus poorly reliable for many diseases and hepatotoxicity studies.24,25 Herein, the development of 3D biomimetic human liver models for in vitro research is considered a promising bridge between 2DMCs and pre-clinical animal testing for drug screening, as well as for the investigation of CLD and the efficient design of patient-tailored therapies in liver diseases.26
In this review, we present an overview of the current state-of-the-art on main strategies for 3D liver model biofabrication. Specifically, engineered liver tissue constructs such as organoids,27 liver-on-a-chip platforms,28,29 and 3D scaffold-based constructs are thoroughly described (Fig. 2).30–32 Key advantages together with ongoing challenges and future outlooks of the current liver models are highlighted, especially from 3D manufacturing and biomaterials perspectives.
Fig. 3 Liver organoid-based models. (A) Schematic of organoid formation: in the case of healthy donors, the final organoids can be formed from stem cells, hepatocytes, cholangiocytes, endothelial cells, or their combination; in the case of pathologic cells (affected by tumor, hepatitis, etc.), the organoids represent a liver disease model formed from pathological or cancer liver cells. (B) Bright-field images of hepatic organoid growth at different culture passages (P). Reproduced with permission.72 Copyright 2019, The Authors, published by Elsevier. (C) Representative tissue biopsies of tumor and healthy liver used to form organoids. (D) Culture of organoids. Bright-field images of organoids derived from tumor and healthy livers: tumor organoids appear as compact spheroids, while healthy liver organoids show cystic structures. P = passage number; scale bar: 500 μm. (C and D). Reproduced with permission.75 Copyright 2018, The Authors, published by Elsevier. |
Organoid formation protocols have been mainly developed from principles in organogenesis. To achieve self-organization, it is essential that organoids should be treated with appropriate biochemical (in liver organoids, e.g., growth factors/glucose addition) and biophysical (e.g., matrix stiffness, mechanical properties) stimuli to promote maturation, tissue-specific or disease-specific differentiation. More specifically, organoid culture media must contain growth factor such as R-spondins (Rspo1) to promote organoid formation as well as Noggin (NOG) and bone morphogenetic protein (BMP) signaling antagonists to either inhibit or prevent other tissue-specific differentiations cues (e.g., mineralization).62,63 Parallelly, ascertained medium glucose levels have to be utilized to control cellular proliferation, investigate drug, and hepatic metabolism outcomes, as well as glucose production.64–66 Moreover, specific interactions among cell populations and biophysical environment should also be strictly controlled to recapitulate heterogeneous structures like the liver tissue.67,68 Organoids can be formed via 3D suspension culture systems (i.e., using ultra-low attachment plates), spinning bioreactors, air–liquid interface methods, and extracellular matrix (ECM)-based embedding matrices (e.g., Matrigel). Also, combinations of different methods may enhance the organoid formation and boost tissue-specific functions.69 For instance, ECM embedded organoids can be used as a scaffolding material, and bioreactors may be employed to improve nutrient absorption.70
One of the first attempts that demonstrated the successful generation of a functional human liver organoid from pluripotent stem cells was reported by Takebe et al., who obtained a vascularized functional human liver from iPSCs upon transplantation of liver buds.71 More recently, Akbari et al. obtained in vitro differentiation of endoderm-derived hepatic organoids into functional hepatocytes using a human-derived iPSC organoid culture system, producing both healthy and disease models from healthy human donors and citrullinemia patients, respectively.72 These liver organoid models were then further investigated to model the urea cycle disorder referred to as citrullinemia type 1 (CTLN1), a disease caused by a mutation in the argininosuccinate synthetase 1 (ASS1) gene causing ammonia accumulation in the blood. The authors modeled CTLN1, using EpCAM+ (Epithelial Cell Adhesion Molecule positive) endodermal cells as an intermediate, thus generating functional pathologic hepatic organoids (eHEPOs) that exhibited epithelial morphology and a pseudostratified structure (Fig. 3B).72 Moreover, this study indicated that eHEPOs were suitable to be expanded for more than six months without any significant loss in their phenotypic characteristics and proliferation rate, confirming the pluripotency of citrullinemia patient-derived iPSCs.72 Disease-related ammonia accumulation and ASS1-enzyme related overexpression were detected in CTLN1 patient organoids compared to healthy eHEPOs, thus recapitulating the urea cycle-related disease phenotype in the hepatic organoids. Human iPSCs have also been manipulated to generate heterogeneous functional liver organoids for modeling infectious diseases such as hepatitis B virus (HBV), which may cause life-threatening liver infections.73,74 Nie et al., investigated the host–HBV interactions causing hepatic dysfunction. The outcomes of the study were correlated to the patient-specific genetic background to develop a promising tool for personalized hepatitis treatment.73
Also, organoid platforms have been used to model alcoholic liver diseases (ALD), a CLD caused by an excess of alcohol in the liver. An interesting ALD-model was obtained using hESC-derived expandable hepatic organoids, which in turn incorporated human fetal liver mesenchymal cells (hFLMCs) to mimic ALD-related pathogenesis (e.g., liver inflammation).50 An ethanol (EtOH) treatment was assessed to recapitulate the ALD mechanism successfully. Upon optimization, the EtOH-treated hepatic organoids showed increased pro-inflammatory signaling of interleukins-1 (IL-1) and interleukins-17 (IL-17) compared to untreated control organoids, as well as fibrosis and ECM accumulation. Recently, ALD-related fatty liver diseases such as steatohepatitis have also been modeled with organoid cultures to recapitulate the pathology progression and potentially use of the developed platform for drug screening purposes.47 Multi-cellular human liver organoids (HLOs) were generated using 11 different types of healthy and diseased patient-derived iPSCs and hESCs. A free fatty acid exposure was assessed on HLOs via oleic acid treatment which significantly induced the progression of the steatohepatitis-like pathology over time (i.e., steatosis, inflammation, and fibrosis), as well as increased organoid stiffness due to the extensive liver fibrosis. Surely, the successful development of such multi-cellular in vitro organoid models should be considered relevant for further screening of human liver disease treatments.
Besides iPSCs and hESCs, primary cell-derived organoids have been reported as 3D models that may represent the donor tissue closely.75–77 In light of this, Gómez-Mariano et al. obtained adult human liver organoids from liver biopsies to model liver disease originating from different mutations of the alpha-1 antitrypsin (AAT) protein, an inhibitor produced by PHH that protects organs from infections and irritation effects.76 Such engineered organoids successfully recapitulated the typical features of deficient AAT liver cells. Indeed, results showed typical hypoalbuminemia and lower AAT secretion caused by AAT deficiency, providing a preclinical model for AAT-related liver diseases. Similarly, Nuciforo et al. generated long-term human liver tumoroids able to maintain histological features of the originating tumor from hepatocellular carcinoma (HCC) patient needle biopsies, allowing for the in vitro recapitulation of the cancer growth pattern up to 1 year (Fig. 3C and D).75 In the same study, patient-specific sensitivity to sorafenib – a kinase inhibitor drug used to treat HCC – was tested on tumoroids, leading to potentially reduced differences in the efficacy of current clinical HCC treatments among patients and ultimately suggested as a valid tool for tailored therapies.
Over the last decade, liver organoids have been widely investigated also for drug development and screening platforms, toxicity testing tools, as well as for the design of patient-specific therapies.78–80 For instance, patient-derived organoids have been described to validate drug studies for specific groups of patients to predict the effectiveness of therapies against drug-induced liver injuries (DILI).81 Relevant outcomes were shown by Skardal et al., who tested the cytotoxic effect of the chemotherapy medication 5-fluorouracil (5-FU) at different concentrations (i.e., from 0 up to 100 mM) on liver tumoroids for drug screening purposes.82 Organoids consisted of crosslinked dextran (Sephadex®) microbeads that were coated with thiol-functionalized hyaluronic acid (HA)/thiol-functionalized gelatin hydrogel blend by using a reduced pressure method, thus obtaining hyaluronic acid-coated microcarriers (HAMs). Subsequently, human colon carcinoma cells HCT-116 Tumor Foci and HepG2 cells were seeded on the HAMs surface to finally generate liver organoids with a rotating wall vessel bioreactor culture system. A 5-FU dose-dependent decrease in the organoid metabolism was revealed within the range 0–10 mM.82 Similar to 5-FU, patient-derived organoids treated with sorafenib has also showed a dose-dependent trend on decreased growth of hepatocellular carcinoma cells directly obtained from human tumor needle biopsies.75 An interesting study on patient-specific cholangiocyte organoid-laden collagen type-1/Matrigel culture revealed the potential cancer medication effect of VX-770 (i.e., Ivacaftor) on cystic fibrosis (CF) by restoring the CFTR gene, which causes such genetic disorder.49 In addition, octreotide- a synthetic analog of somatostatin- was also tested for polycystic liver disease reducing the organoid size, thus revealing its role in reducing the cyst size.48
Besides CF and liver tumors, organoids have also been employed to investigate in vitro the treatment of DILI. Indeed, DILI is one of the major causes of liver damage worldwide, and it can be classified as direct- and idiosyncratic-drug hepatoxicity.83–85 Direct hepatoxicity is mostly dose-dependent; on the other side, drug sensitivity reactions may lead to idiosyncratic reactions. Herein, various studies have been designed to assess the hepatic toxicity of medical drugs.86–89 Standard evaluation methods include the measurement of hepatic enzyme activity and structural changes in hepatocytes. An interesting study by Au et al. proposed a microfluidic drug screening platform for collagen type 1-based liver organoids treated with dexamethasone (i.e., CYP3A4 inducer) and ketoconazole (i.e., CYP3A4 inhibitor) to assess the model's drug metabolism.88 Liver organoids were formed in the custom-made device by co-culturing HepG2 and NIH 3T3 fibroblast cells embedded in the hydrogel matrix. Given that the organoid volume has decreased enabling cell–cell interaction and tissue functionalities due to higher and native-like cell densities in a reduced volume, a contractility test was performed.90 Results showed that the presence of the fibroblasts may reduce the volume of the organoid over 4 days, compared to sole HepG2-organoids. Likewise, albumin secretion after 4 days was significantly higher in co-culture organoids than in HepG2 mono-culture 3D structures, thus showing the role of fibroblasts in the improved functional activity of HepG2 hepatocytes and organoid densification. Additionally, the 3T3-HepG2 co-culture organoids treated with dexamethasone exhibited higher CYP activity and metabolism, while ketoconazole-treated organoids revealed a lower metabolism as expected from the chemical inducer and inhibitor treatment, respectively. Similar studies on CYP activity and organoid microstructure have been modeled using common drugs such as acetaminophen (APAP) and troglitazone on Matrigel-based 3D cultures.54,86,87 For instance, Ramli et al. developed hepatic organoids that closely mimicked the 3D interaction of two different human liver cell types (i.e., hepatocytes and cholangiocytes) to engineer an organized functional bile canaliculi system.54 A drug-induced cholestasis was modeled by incubating the organoids in troglitazone for different time periods, showing their role in the loss of the bile canaliculi system. Both hepatocyte and cholangiocyte functionalities were confirmed from the increased CYP450 activity expressed over the differentiation time and the alkaline phosphatase (biliary) activity, respectively; thus, suggesting that the model can be used to explore and further study liver cholestasis.
Alongside disease models, liver organoids in microfluidic systems have also gained attention for the possibility of developing large-scale high-throughput toxicity- and drug testing platforms.91 In a study proposed by Shinozawa et al., a robust protocol to form human iPSC (hiPSC)-based liver organoids for the preclinical identification of DILI has been developed and tested for 238 active components of commercially available drugs including antibiotics (erythromycin), chemotherapy agents (floxuridine), antivirals (Ritonavir), and anti-inflammatory drugs (nimesulide).81 Similarly, on a smaller scale, vascularized ECM-based human pluripotent stem cell-derived liver organoids have also been utilized for high-fidelity screening of different marketed drugs based on cholestatic and mitochondrial toxicity.80
Ultimately, the most significant advantage of the organoids is that they are the only 3D in vitro models that can be cryopreserved, presenting promising opportunities for specifically biobanking applications.92–95 Especially, cryopreservation of human ESC (hESC)-derived organoids hold great attention of biotech companies for pharmaceutical purposes. Despite ethical concerns on both research and therapeutic use of hESC organoids, their unlimited capability for self-renewal as well as the potential to differentiate into different tissues make them unique tools for personalized therapies to model liver diseases such as CF,49 ALD,47,50 and injuries,50 together with toxicity prediction purposes.86,92–95
Among others, cell patterning is one of the most pioneering techniques in fabricating liver-on-a-chip platforms, as it enables appropriate positioning of the different cell populations in complex designed systems, including Liver Acinus MicroPhysiology System (LAMPS), Tapered Stencil for Cluster Culture (TASCL), and OrganoPlate® (Fig. 4A). In one work by Ho et al., hepatic-like lobule arrays have been designed to recreate the lobule pattern, allowing for the precise positioning of two different cell lines (i.e., human liver cancer cell line (e.g., HepG2) and human umbilical vein endothelial cells (HUVEC)).100 In such a system, an organized cell distribution with appropriate morphology was obtained by increasing liver-specific enzymatic activity.
Fig. 4 Liver-on-a-chip platforms. (A) Different cell sources, such as stem cells, endothelial cells, and liver-derived cells (e.g., healthy and pathological parenchymal and non-parenchymal cells) can be introduced into a microfluidic chip to obtain liver-on-a-chip models. The microfluidic devices, including LAMPS (i), TASCL (ii), and OrganoPlate® (iii), can be employed for disease modeling or drug testing purposes. (i) Reproduced with permission.115 Copyright 2017, SAGE. (ii) Reproduced under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).118 Copyright 2015, published by SAGE. (iii) Reproduced under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).120 Copyright 2021, The Authors, published by Elsevier. (B and C) Evaluation of hepatocyte spheroid response into the chip: (B) cell morphology observed in phase contrast micrographs up to 24 days of culture; (C) cell viability evaluated via live/dead staining at day 24 of culture. Scale bar: 100 μm. Reproduced under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).102 Copyright 2017, The Authors, published by Springer Nature. (D) Fluorescent images of 3-cell type liver-on-a-chip: organ and perfusion channels are seeded with pluripotent stem cell-derived hepatocytes (iHep) clusters and endothelial (HMEC-1) cells/Kupffer (THP-1) cells, respectively. Cells are stained with nuclei/F-actin/CD68 in blue/red/yellow colors. (E) 3D reconstruction of the perfusion channel. (D and E) Reproduced under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).120 Copyright 2021, The Authors, published by Elsevier. |
Similarly to other 3D in vitro models, liver-on-a-chip platforms provide a suitable microenvironment allowing for mimicking cell–cell interaction and in turn maintaining of cell morphology and polarization.101 Moreover, liver-on-a-chip platforms enable the study of both static and dynamic cell culture conditions. Although static cell cultures have been successfully employed in pre-clinical disease modeling and drug development studies, in vitro perfused cell culture systems are characterized by a more biomimetic condition (Fig. 4B and C).102 In fact, static culture systems may limit the nutrient supply and accumulate waste, likely inducing hepatocyte dedifferentiation and decreasing liver-specific functions.103 On the other hand, perfusable systems can provide continuous transfer of nutrients and metabolites to finally mimic the multiple cell–cell interactions of the liver sinusoidal structure.104,105 Furthermore, dynamic culture conditions allow for the creation of a stable oxygen gradient, thus replicating the peculiar metabolic zonation of the liver.28,106–109 For these attractive features, research on liver-on-a-chip platforms has gained enormous attention in recent years, and various strategies have been established.
For instance, Lee et al. designed a biologically inspired artificial liver sinusoid in a microfluidic chip that mimics the liver endothelial barrier layer. A collar region of parallel microchannels (2 μm × 1 μm, width × height) was designed to reproduce the endothelial-like barrier, which in turn surrounds a main cell inlet channel. A sinusoid-like flow channel was patterned at the frame of the chip, thus allowing for hepatic microcirculation. Herein, different mass transport parameters (e.g., channel length, height and width, fluidic resistance, volumetric flow rate, Reynolds number) were set.110 In the middle of the device, a cell culture area was placed. Primary rat and human hepatocytes (PRH and PHH, respectively) were loaded into the cell culture area. At the same time, the microfluidic platform was continuously perfused with culture medium in a standard incubator. Since the barrier channels had a cross-section much smaller than the cell diameter, hepatocyte packing was enabled without causing membrane damage. Moreover, due to the small scale of the device, continuous nutrient exchange was possible through simple diffusion, and extensive cell–cell interactions were allowed. In light of this, such culture conditions promoted high hepatocyte viability (>90%) for over 7 days of culture.
Another advanced perfusable 3D in vitro liver chip was developed to model Non-Alcoholic Fatty Liver Disease (NAFLD) by encapsulating sacrificial thermoresponsive poly(N-isopropyl acrylamide) (pNIPAAm) fibers into enzyme-crosslinked spheroid-laden gelatin hydrogels.111 The fibers were then dissolved away from the hydrogel with medium perfusion below the gel–sol transition temperature (i.e., 32 °C) to obtain hollow channels mimicking the liver microvasculature, thus generating an interconnected network of microchannels with physiologically relevant capillary-like diameters (i.e., 17.78 ± 8.73 μm on average). Liver cell spheroids were prepared using a monoculture of normal mouse liver hepatocytes and a hepatocytes/endothelial cells/HSC tri-culture. Here, the perfused system promoted the lipid metabolic activity of hepatocytes. Also, hollow gelatin-based channels with perfusion revealed higher albumin and CYP3A4 expression over 10 days of culture than non-perfused groups, confirming the role of micro-vascularization in liver maintenance. Afterward, NAFLD was modeled in its early inflammatory and late fibrosis stages (i.e., nonalcoholic steatohepatitis (NASH)) on the liver-on-a-chip platform upon palmitic acid treatment, a fatty acid that may induce reactive oxygen species (ROS)-mediated apoptosis in a dose-dependent manner. Results showed that a 10-day treatment led to intracellular ROS accumulation and increased inflammatory markers expression (interleukins-6 (IL-6) and Tumour Necrosis Factor α (TNFα)), thus successfully replicating inflammation, lipid accumulation, and fibrosis occurring during the progressive processes of NAFLD.111 Another study successfully developed a microfluidic chip to model NAFLD progression using different free fatty acid gradients to perfuse primary hepatocytes. Moreover, such a microfluidic platform was used to create oxygen-driven steatosis zonation to investigate the role of oxygen deprivation in hepatocyte lipid accumulation. The model successfully mimicked the sinusoidal lipid distribution on a single continuous tissue and ultimately showed that such fat zonation disappears under progressed steatosis.112
To boost the mimicking of in vitro hepatic microenvironment, liver-on-a-chip platforms can also be employed to real-time monitor parameters such as oxygen gradients and the expression of metabolic enzymes.108 Sato et al. monitored the cellular oxygen consumption rate of hepatocytes in a microfluidic device that can simultaneously expose cell layers to areas with different oxygen concentrations (i.e., area 1 – hyperoxia, areas 2/3 – physiological conditions, area 4 – hypoxia) and automatic medium exchange for long-term culture.113 The measurement of partial oxygen pressure was performed via a laser-assisted phosphorescence quenching method. The in vitro zone-specific mRNA expression of metabolic genes such as phosphoenolpyruvate carboxykinase (PEPCK) and glucokinase (GK) increased in the periportal and pericentral regions (i.e., areas 2/3) as in in vivo condition. Moya et al. used a microfluidic layer-by-layer device integrated with oxygen sensors to attain the real-time metabolic activity of the liver system.114 Similarly, Lee-Montiel et al. developed a microfluidic platform (i.e., LAMPS, Fig. 4A(i)).115,116 The LAMPS model was constructed in a microfluidic chamber (50 μl volume) to recapitulate the liver acinus structure and multiple zone-specific functions by recreating liver Zone 1 and Zone 3 oxygen microenvironments. The microfluidic chamber incorporated sequential cell layers composed of primary human endothelial cells, hepatocytes, and HUVECs, as well as human monocyte cells (Kupffer-like immune cells), LX-2, and immortalized human hepatic stellate cells (HSCs), where the structural organization of the model was improved by depositing a thin layer of porcine liver ECM between the hepatocytes and the endothelial cells to mimic the space of Disse.116 Finally, specific in vitro liver oxygen zonation was achieved by perfusing LAMPS at both 15 μl h−1 and 5 μl h−1 to recreate Zone 1 and Zone 3, respectively. These values were calculated via a computational model of oxygen flows directly installed into the device, thus considering media transport, material permeability, and cellular consumption. As a result, zonation-dependent lipogenesis (i.e., steatosis) showed that LAMPS could be used to model and investigate zone-specific liver metabolism and diseases, as Zone 3 was found to consistently possess higher lipid-filled cells than those located in Zone 1.115
Microfluidic platform features can also be exploited to perform liver drug screening and hepatotoxicity studies. For instance, Skardal et al. realized a microfluidic platform with four parallel culture chambers to produce multiple and identical liver structures for toxicology testing.117 A HA/gelatin-based hydrogel formulation containing liver cancer cells (HepG2) was mixed in a 1:1 ratio with a Glycosyl/Gelin S/polyethylene glycol diacrylate (PEGDA) pre-polymer formulation (2:1:1 ratio) to obtain a hydrogel precursor cell-mixture with the addition of a photo-crosslinkable precursor. The solution was inoculated through separate channels for a localized in situ crosslinking. Once the chambers were filled, a photomask was positioned above the microfluidic device to selectively crosslink the structures via thiolene reaction. After 7 days of culture, high cell viability was quantified in the liver constructs (>75%). Samples were also tested upon EtOH treatment at different concentrations (0 mM–500 mM) to evaluate the constructs’ functionality and toxicity effects. A dose-dependent behavior was found, as albumin and urea secretion significantly decreased with the increase of EtOH concentration and exposure, suggesting the platform as a potential tool for drug development and toxicology screening.117
Similarly, a patterned toxicity evaluation system was developed to simultaneously assess different drug screenings in the same microfluidic device (i.e., TASCL, Fig. 4A(ii)).118 The TASCL device was fabricated with an overall size of 10 mm × 10 mm, in which 400 microwells were designed and patterned with a top and a bottom aperture, measuring 500 μm × 500 μm (square) and 300 μm in diameter (circular) each, respectively. TASCL was seeded at different cell densities to investigate the formation of HepG2 spheroids. As a result, the microfluidic platform ensured suitable spherical aggregation, high viability, and albumin secretion upon highly precise positioning.
Also, commercial microfluidic platforms can be used for liver drug screening. Among them, OrganoPlate® platforms have been employed for hepatotoxicity studies (Fig. 4A(iii)).119,120 Such a device contains a specific number of microfluidic tissue culture chambers (e.g., 40, 64, or 96, according to the model) designed and embedded on the bottom of a commercial 364-well plate. Each culture chamber consists of one culture channel containing an ECM-based hydrogel of choice and up to two adjacent perfusion channels separated by specific phase guides to prevent the patterned hydrogel from flowing into the adjacent channels. Moreover, OrganoPlate® platforms are stimulated by a gravity-driven leveling technology that enables the induction of a continuous passive perfusion flow without using an external pump or tubing line. Thus, such microfluidic platforms allow for the separation of the cell culture area and the perfusion flow without any physical barrier, as well as indirect contact between the cells and the flow due to the polymerization of the hydrogel matrix. In particular, Bircsak et al. developed a liver-on-a-chip platform for high throughput hepatotoxicity screening, using an OrganoPlate® model with 96 culture chambers with two separate channels (i.e., one perfusable and one containing an ECM-based hydrogel).120 Specifically, hiPSC-derived hepatocytes (iHep) were seeded in the ECM channel and co-cultured with endothelial cells and THP-1 monoblasts differentiated to macrophages seeded in the perfusable channel. Such multicellular microfluidic structure allowed the formation of iHep clusters in the ECM-channel and a 3D tubular endothelial layer structure in the perfusable channel (Fig. 4D and E). After 15 days of culture, cells were viable and exhibited stable albumin and urea secretion. Moreover, an increase in the CYP3A4 activity and the decreased alpha-fetoprotein (AFP) secretion suggested further maturation of the iHeps. In addition, troglitazone and a small library of 159 compounds with known liver effects have been employed to successfully validate the device as a platform for liver drug testing.
Furthermore, different biomaterials such as ECM components and naturally derived hydrogels can be integrated into liver-on-a-chip platforms to enhance their biomimetic potential.119 The addition of a 3D in vivo-like tissue microenvironment can be beneficial for cell maturation. Hence, a 3D architecture can provide suitable physicochemical properties to mimic physiologically relevant conditions (i.e., cell–cell interaction and metabolic pathways). Although ECM-derived materials possess fast degradation rates and lack robust mechanical properties, components such as Matrigel, collagen, and fibronectin (FN) have been widely employed,115,121–123 as well as decellularized liver matrices,115,124 gelatin-based hydrogels,111 and hybrid formulations.125 For instance, Toh et al. performed a collagen-coating on a multiplexed microfluidic hepatocyte culture system, allowing for the investigation of the metabolic functions of hepatocytes.126 Furthermore, the liver chip was used to predict in vivo hepatotoxicity testing for five different drugs in an in vitro dose-dependent manner (i.e., acetaminophen, diclofenac, quinidine, rifampin, and ketoconazole). Also, the integration of liver decellularized ECM (dECM) and gelatin methacryloyl (GelMA) in a dynamic microfluidic-based 3D cell culture system displayed a linear dose-dependent drug response to the toxicity of Acetaminophen and sorafenib.125
In conclusion, coupling liver-on-a-chip technologies with perfusion-based systems can be beneficial for the development of 3D in vitro models that aim to functionally recapitulate the liver microarchitecture and realize robust platforms for high-throughput screening of hepatic diseases and drug compounds.
In this section, a discussion of the most thought-provoking advances in 3D liver models obtained by 3D scaffolding strategies is provided. In light of this, biofabrication techniques such as 3D printing, 3D bioprinting, and electrospinning for in vitro disease modeling and drug testing are thoroughly described. Due to the limited possibility of developing controllable and complex architectures for physiologically relevant structures, more conventional methods like molding, extrusion, and micropatterning are out of the scope of this review.
3D printed architectures have also been developed to evaluate the influence of 3D porous structures and dynamic mass transport on drug testing platforms.74,105 Vinci et al. proposed an interesting scalable in vitro liver model investigated in terms of 3D topology and convective flow, two primary cues influencing hepatocytes’ function.105 Synthetic materials such as PLGA and PLLA were used to prepare liver constructs employing a pressure-assisted microsyringe (PAM). The 3D scaffolds mimicked the characteristic size of hepatic lobules with three different layers, composed of 70 hexagonal unit cell structures each, thus creating an overall construct with high porosity suitable for cell penetration and adhesion. The authors showed that the 3D porous architecture increased cell density and promoted the formation of aggregates compared to 2D films, thus maximizing cell–cell interactions. Another novel bio-inspired 3D printed construct based on a PEG hydrogel was embedded with polydiacetylene (PDA) nanoparticles to fabricate a detoxification model that may provide an alternative strategy to drug intoxication.167 Herein, PDA nanoparticles showed their potential in neutralizing melittin toxins in vitro. Mimicking the liver lobule-like configuration, the platform was able to attract, catch and sense the melittin toxins, a harmful poisonous substance to humans that can result from animal bites and bacteria.
3D bioprinting techniques have been widely used to develop highly accurate/precise/realistic disease liver models. A high geometrical complexity can be achieved by optimizing bioink formulations and 3D bioprinting parameters. Thus, a proper recapitulation of the liver structure similar to in vivo pathological conditions can be performed. For example, Wu et al. incorporated cellulose nanocrystals (CNCs) into an alginate/GelMA formulation to enhance shear-thinning behavior and shape fidelity upon bioink deposition.185,186 Indeed, CNCs were found to align along the printing direction, thus enhancing the bioink extrudability compared to pristine alginate/GelMA bioink. The bioink was extruded directly on a cover glass or in an alginate/calcium chloride (CaCl2) supporting bath and subsequently crosslinked by UV light exposure. A high-accuracy liver-biomimetic 3D honeycomb structure was successfully produced. Such structure was employed as a 3D platform for co-culturing two different cell types (i.e., NIH 3T3 and HepG2). Specifically, NIH 3T3/Alginate/GelMA/CNCs bioink was deposited to create the lobule-like structure, while HepG2/GelMA was deposited inside the hexagonal holes. The precise positioning of cells allowed for the alignment of NIH 3T3 fibroblasts and the formation of HepG2 spheroids, thus recapitulating the overall 3D biomimetic structure. Moreover, intracellular interactions enhanced albumin secretion compared to HepG2 culture used as a control. Pathological conditions can be reproduced by mimicking intracellular events and cross-talks. To this aim, 3D bioprinting enables the fabrication of biomimetic microenvironment hosting multiple cell types.187 For instance, Cuvellier et al. established a tri-culture model consisting of HepaRG/LX-2/HUVECs to recapitulate the progressive development of fibrosis in vivo.188 HepaRG/LX-2 were mixed with GelMA and 3D bioprinted in a square-shaped construct. Afterwards, scaffolds were crosslinked by UV-photopolymerization. HUVECs were seeded after one week of culture to recreate a pseudo-endothelial barrier following colonization of the surface structure. The 3D bioprinted structures exhibited long-term viability, proliferative ability, hepatocyte phenotype and functions. Moreover, the 3D bioprinted model was suitable for the interaction between parenchymal and non-parenchymal cells, which was modulated by the secretion of TGFβ-1 that in turn induced the activation of myofibroblastic genes (i.e., ACTA2 and COL1A1). As a result, a fibrillar collagen synthesis deposition was observed, which was not evidenced in monocultures of either HepaRG or LX-2.
Besides single-cell dispersion, 3D bioprinting was found to be suitable also for the encapsulation of 3D spheroids. Goulart et al. performed a study to compare 3D bioprinting of iPSC-derived hepatocyte-like spheroids and single cell dispersion, both in combination with iPSC-derived mesenchymal cells and ECs in alginate/Pluronic F-127 blend bioink formulation.180 3D hepatic spheroids were successfully 3D printed in a donut-shaped geometry construct and crosslinked with CaCl2 upon biofabrication. After 18 days of culture, the viability of the cultured spheroids was significantly higher than single cells. Moreover, 3D spheroids exhibited higher expression of liver-specific markers, including increased urea production and prolonged secretion of albumin. In addition, single cells revealed epithelial–mesenchymal transition, resulting in a rapid loss of hepatocyte phenotype. By tuning 3D printing parameters, constructs with tunable mechanical properties can be obtained. In particular, light-assisted 3D bioprinting technologies offer the possibility to modulate the photo-polymerization processes, thus allowing for the fabrication of constructs with regionally different mechanical properties. Such interesting feature provides a valuable tool for fabricating platforms that aim to replicate liver pathologic conditions (e.g., cirrhotic liver) characterized by higher mechanical properties than the native liver tissue in physiological conditions. Ma et al. used light-assisted 3D bioprinting to pattern a photo-crosslinkable GelMA/dECM formulation with tunable mechanical properties as a platform for studying the effects of stiffness on HCC progression.189 HepG2 cells were encapsulated in a lobule-like hexagonal structure with different mechanical properties to recapitulate both the native and cirrhotic liver tissue. For scaffolds with lower stiffness, cellular aggregation and spheroid formation were observed with increasing spheroid size during the culture period. Contrarily, reduced growth was observed for HepG2 cells cultured in scaffold with cirrhotic mechanical properties. Moreover, stiffer scaffolds showed an upregulation of invasion markers (i.e., insulin-like growth factor 2 (IGF-2)) compared to physiological native-like controls. To further investigate the HepG2 invasion potential, a biomimetic design consisting of three hexagonal lobules, each possessing different stiffness (e.g., soft, medium, and stiff scaffolds), was developed. Each hexagonal unit was interconnected with a collagen I-based scaffold to recapitulate the fibrous septa-like structure found in the native liver architecture. Such engineered cancer platform enabled the validation of the highest degree of invasion of HepG2 cultured in a cirrhotic mechanical environment into the surrounding stromal region.
The potential of 3D bioprinting in replicating highly biomimetic constructs has been used to produce liver platforms for drug testing purposes (Fig. 5B). Ma et al. employed a light-based 3D bioprinting system to produce a UV-crosslinked GelMA-based platform, aiming to embed hiPSC-derived hepatic cells and endothelial- and mesenchymal-originated supporting cells (i.e., HUVECs and adipose-derived stem cells) in a high-resolution hexagonal geometrical pattern that closely mimicked the in vivo hepatic lobule structure.190 The hydrogel-based triculture model promoted cell organization and alignment within the biomimetic architecture. Moreover, higher expression of hepatic markers (i.e., HNF4a, TTR, and albumin) and metabolic product secretion was observed, compared to the 2DMC and the 3D hepatic progenitor cells (HPC) monoculture model. In another study, Sun et al. used extrusion-based bioprinting to fabricate a 3D liver cancer model composed of HepG2 suspended in gelatin/alginate. Upon fabrication, the 3D-bioprinted scaffolds were crosslinked with CaCl2 solution, finalizing the 3D model for liver cancer.138 Compared to the 2D model counterpart, HepG2-laden 3D scaffolds showed higher expression of tumor related genes including ALB, AFP, CD133, EpCAM, and TGFβ-1 genes. To validate the cancer model, the anti-tumor response to several drug treatments (i.e., cisplatin, sorafenib, regorafenib) was evaluated. As a result, it was observed that the half-maximal inhibitory concentration (IC50) values of the tested drugs were higher in the HepG2-laden scaffold model compared to the 2D model. Such findings suggested a higher sensibility of the 2D model compared to the 3D scaffold. However, the IC50 values obtained in the 3D-HepG2 model were closer to the effective blood concentration of the drugs in the human body. These outcomes were explained by the higher levels of drug resistance autophagy-related genes (e.g., ABCB1, MDR-1, MRP1, and EGFR) expressed in the 3D-bioprinted model.
The employment of the same 3D printed model was furtherly extended to establish in vitro model for patient-specific drug screening for HCC.191 Cells were isolated from HCC-specimens collected from six patients and then combined with gelatin/alginate to produce the bioink. Patient-derived 3D bioprinted scaffolds were successfully fabricated, showing high viability and proliferation rate during long-term culture. Moreover, HCC-scaffolds allowed for retaining the features of the originating HCC tumors, including stable expression of the AFP biomarker, as well as the constant maintenance of genetic alterations and expression profiles. Furthermore, the efficacy of four commonly used empirical targeted drugs for HCC-affected patients was assessed. Most of the HCC-scaffold models derived from the six patients resulted to be insensitive to the four targeted drugs in treatments. However, four patient-specific HCC-derived 3D scaffolds were found to be positively responsive to one or more drugs. For such scaffolds, a dose-dependent manner was observed. For two patients, sorafenib and lenvatinib showed enhanced anti-tumor effects than other drugs, respectively. Such findings encouraged the classification of patient-derived HCC-laden scaffolds as a potential candidate in the field of personalized cancer treatments. 3D bioprinting was also found to be a suitable technology to preserve the differentiation futures of encapsulated cells. For instance, Faulkner-Jones et al. performed inkjet-based 3D bioprinting of hepatocyte-like cells (HLCs) differentiated from both hiPSCs and hESCs mixed with RGD/alginate-based hydrogel solution.172 A cell-laden hydrogel was printed by dispensing an array of droplets of the bioink, followed by an overprinting of droplets of CaCl2 solution to allow the crosslinking. The droplets were dispensed following a circular path, and a ring-shaped structure was finally obtained when adjacent droplets overlapped together and formed a single continuous layer. Upon fabrication, the cell-laden structures continued the differentiation process into hepatocyte-like cells (HLCs) over 24 days of culture. As a result, encapsulated cells were viable and preserved the hepatocyte marker expression validating such 3D printed model as a potential platform for drug testing studies.
In vitro model | Biomaterials | Cell source | Aim of the work | Main outcomes | Limitations | Ref. |
---|---|---|---|---|---|---|
Organoids | — | Patient-derived HCC-biopsies | Modeling of human liver cancer derived from tumor needle biopsies | • Long-term cultures | • Reduced number of testing patients | 75 |
• Recapitulation of histological features and tumor markers expression comparable with the originating tumors | • Disadvantages related to liver biopsies (i.e., patient pain, bleeding, infection, accidental injury to nearby organs) | |||||
• Tumor formation with histological features of the original biopsy upon injection of organoids into immunodeficient mice | ||||||
• Dose-dependent trend in response to sorafenib treatment | ||||||
— | HSC HepaRG | Modeling of drug-induced liver fibrosis | • Metabolically active hepatic organoids | • Absence of biomaterial providing physico-chemical cues to support cell-growth | 60 | |
• Collagen secretion and HSC activation after exposure to pro-fibrotic compounds | • Replication of higher biomimetic fibrosis model that could be obtained including Kupffer cells, liver sinusoidal endothelial cells and PHH | |||||
HA | HCT-116 | Modeling of liver-tumor organoids for tumor growth and drug response | • Enhanced mesenchymal phenotype for cells compared to 2D culture | • Use of cell seeding over hydrogel cell-encapsulation | 82 | |
Gelatin PEGDA | HepG2 | • Dose-dependent behavior resulting from increased apoptosis and decreasing metabolism of HCT-116 with higher concentrations of 5-FU | ||||
Liver-on-a-chip | Collagen | HepG2 NIH 3T3 | Microfluidic organoid platform for drug screening | • Automated platform to confine organoids and perform on-chip dilution for hepatotoxicity screening | • HepG2 (cancer cells) prevent the result translation to healthy hepatocytes | 88 |
• Enhanced mimicry of fibroblasts contractile behavior and albumin secretion profiles compared to 2D systems | ||||||
• CYP3A4 activities and necrotic/apoptosis consistent with the dose-dependent effect of treatment of chemical inducer/inhibitors on hepatoma cells | ||||||
GelMA | HepG2 | Biomimetic liver tumor-on-a-chip model for toxicity testing | • Recapitulation of tumor microenvironment with biochemical factors and biophysical cues | • Use of animal-derived decellularized liver ECM instead of human-derived ECM | 125 | |
Decellularized liver matrix | • Enhanced hepatocyte viability and functions under flow conditions | |||||
• Linear dose-dependent drug response to the toxicity of APAP and sorafenib | ||||||
Gelatin pNIPAAm | Mouse liver hepatocytes (AML12) | Implantable vascularized liver chip for cross-validation of disease treatment with animal model | • Successful implantation and maintenance of liver buds in perfusable 3D hydrogels | • Low reproducibility and control over the fabrication methods to produce hydrogel-based nanofibers for the generation of vessel-like networks | 111 | |
Mouse endothelial cells | • Realistic replication of inflammation, lipid accumulation, and fibrosis due to the progression of NAFLD compared to animal model | |||||
HSCs | • Similar response of liver-on-a-chip model upon the use of hepatic steatosis-reducing drug (i.e., restoration of mitochondrial activities, reduction of inflammation, oxidative stress, and lipid accumulation) compared to animal model | |||||
3D printed scaffolds | PLGA | HepG2 | Biomimetic 3D scaffold coupled with a modular bioreactor to investigate hepatocyte function | • Increased cell density of seeded culture compared to monolayer controls | • Low biochemical and biological potential of the 3D printed scaffold | 105 |
PLLA | • Enhanced cell density, formation of aggregates, and gene expressions in 3D scaffolds compared with monolayer controls | |||||
• 3D porous scaffold mimicking the characteristic geometry of hepatic lobules | ||||||
• Increased cell metabolic in dynamic culture in comparison with static monolayer cultures | ||||||
Gelatin | HUH-7 | Modulation of hepatocyte function and gene expression using different pore geometries | • Precise control over pore geometry and orientation | • Limited 3D scaffold design and architecture complexity | 161 | |
• High viability and proliferation when cells are seeded on 3D-printed scaffolds with different geometries | ||||||
• Enhanced hepatocyte functions (albumin secretion, CYP activity, bile transport) in the interconnected scaffold compared to less interconnected geometries and 2D controls | ||||||
PEGDA | — | Bio-inspired 3D printed scaffold functionalized with nanocomposites hydrogel for detoxification studies | • Successful encapsulation of functional polydiacetylene nanoparticles with detoxification potential | • High expensive and no commercial 3D printing equipment | 167 | |
• Highly biomimetic 3D scaffold structure enables access to toxins inside the hydrogel matrix | • Selection of inks limited to photo-crosslinkable hydrogels | |||||
• Effective interaction of nanoparticles and toxins | ||||||
• High functionality of nanoparticles enables the toxins capture | ||||||
• Loss of virulence potential in toxin solution after treatment | ||||||
3D bioprinted scaffolds | Alginate | HepG2 | Bi-cellular liver biomimetic structure | • High printability of high-resolution hexagonal scaffolds without cell damage | • Potential cell damage risk due to shear stress induced by extrusion of highly viscous bioinks | 186 |
Cellulose nanocrystal | NIH 3T3 | • Precise positioning of HepG2 and NIH 3T3 bioinks to mimic liver microenvironment | ||||
GelMA | • NIH 3T3 alignment at the boundary of the hexagonal lobule | |||||
• Enhancement of albumin secretion in the bicellular construct compared to NIH 3T3 and HepG2 singles cells culture | ||||||
Liver decellularized ECM | HepG2 | Mimicking of cirrhotic liver environment to predict the HCC development and growth invasion | • Constructs with regionally varied mechanical properties | • Labor intensive 3D bioprinting procedure | 189 | |
GelMA | • HepG2 reduced growth and high degree of stromal invasion from the nodules with cirrhotic-like stiffness compared to healthy controls | • Use of UV-photocrosslinking with potential cell damage risk | ||||
Gelatin alginate | Patient-derived HCC | Platform for personalized medicine of human hepatocellular carcinoma | • Patient-derived scaffolds with high viability and proliferation rate | • Limited 3D scaffold design and geometry in terms of biomimicry and complexity | 138 | |
• Good retainment of the features of the originating HCC tumors | ||||||
• Effective response to four commonly used empirical targeted drugs showing a dose-dependent manner | ||||||
Electrospun scaffolds | Liver decellularized ECM | THLE-3 hepatocytes | Nanofibrous hepatic-like scaffold for therapeutics research | • Bio-functional microenvironment | • Use of thermoplastic polymeric material with higher mechanical properties compared to the native liver tissue | 195 |
PLLA | • Cell attachment and survival | |||||
• Expression of key hepatic genes | ||||||
• Hepatocyte growth and albumin production | ||||||
Chitosan FN coating | Primary rat hepatocyte and 3T3-J2 fibroblasts | Biomimetic nanofibrous scaffolds and co-culture system for the long-term maintenance of liver functions | • Highly porous and randomly oriented nanofibrous structures | • Limited FN biomimetic potential compared to other biomaterials (e.g., decellularized ECM) | 201 | |
• Enhanced cell attachment and spreading due to FN coating | ||||||
• Formation of colonies, maintenance of cell morphology and function for prolonged periods of time | ||||||
• High levels of CYP450 A1 enzyme activity and albumin secretion |
In vitro model | Advantages | Disadvantages |
---|---|---|
Organoids | • Cost-effective procedure | • Labor-intensive procedures to develop suitable fabrication protocols |
• Facile method | • Use of expensive cell sources (i.e., iPSC) | |
• Ability to easily combine different cell types | • Relatively simple model with lack of flexibility enabling to reproduce complex tissue architecture and hierarchical structure | |
• Cells self-organization properties | • Limited control on organoid size and uniformity | |
• Cell–cell contact and interaction to reproduce in vivo conditions | • Lack of vascularization | |
• Ability to mimic oxygen gradients and drug diffusion of the liver lobule | • Limited tissue availability in case of patient-derived tissue biopsies | |
• Easy integration into 3D scaffold/microfluidic platform | ||
• Long-term culture and maintenance of the overall metabolic configuration and liver-specific functionality | ||
• Suitable for combination with soft biomaterials (i.e., hydrogels) | ||
• Allow the development of personalized model by using patient-derived tissue biopsies or pluripotent stem cells | ||
Liver-on-a-chip | • Cost-effective | • Expensive technology for the fabrication of the microfluidic platform |
• Ability to recreate tissue-like microarchitecture by tailoring and adapting different layouts and design | • Low throughput | |
• Low number of cells required and amount of tissue culture medium | • Multi-step fabrication process | |
• Ability to recreate the in vivo liver natural and pathological physiology by generating dynamic mechanical and physicochemical stimuli | • Large amount of dead space | |
• Ability to introduce fluidic channels to reproduce dynamic blood flow, wall shear stress, oxygen gradient, and metabolic zonation | • Not specific drug bindings to the chip biomaterial platform | |
• Precise cell spatial distribution | • Expensive device (i.e., bioreactor, syringe pumps) coupled to the microfluidic chip to create in vivo condition | |
• Ability to mimic the liver tissue functional unit (i.e., sinusoid, canicular system, acinus) | • Not suitable to reproduce physiological tissue-like structures in terms of complexity and size | |
• Ability to mimic molecular mechanism of disease and drug action | • Limited selection of biomaterials to recreate a biomimetic microenvironment | |
• Recapitulation of tissue/organ multi-cellular architectures and tissue–tissue interfaces to evaluate interorgan and intertissue interaction in drug metabolism. | ||
3D scaffolds | • High control over scaffold architecture and pore size | • Complex and expensive biofabrication apparatus Labor-intensive biofabrication procedures |
• Suitable for the fabrication of highly biomimetic construct in terms of tissue architectures and biomaterials | • Challenging coupling of materials and biofabrication techniques suitable to create complex and high-resolution structure | |
• Ability to precisely position different cell types and biomaterials to reproduce the complexity of the heterogeneous liver microenvironment in pathological and physiological state | • Not suitable to reproduce in vivo-like stimuli without perfusable systems | |
• Tissue-like cell density and composition | • Material choice not always highly ECM biomimetic | |
• Ability to load biomaterials with drug compounds | • Limited range of fabrication techniques allowing for functional cell encapsulation | |
• Ability to fabricate constructs with different mechanical properties by easily changing fabrication parameter processes |
Although recent advances focus on more automated biofabrication approaches to avoid significant errors and bias, it is still strongly believed that a further step towards this research direction should be made. As a result, the data-driven repeatability of analytical methods for drug testing and toxicity studies would actively encourage predicting and identifying possible outcomes of these pioneering biomedical technologies.224 Moreover, bioinformatics would speed up the final process involving governmental agencies (e.g., FDA approval, EC regulations) to authorize and market such advanced LTE in vitro tools at a commercial scale. Among others, deep learning methods for DILI prediction and toxicogenomic have been lately realized.225–230 In this frame, machine learning algorithms have been applied to the chemical structure of small molecule drugs as a model to predict the DILI compound-specific risk at the preclinical stage and to identify patient-specific drug treatments.225 Similarly, an artificial intelligence-based approach was developed to forecast and rank gene expression features acquired from rodent livers exposed to drug compounds. A toxicogenomic open database231 was used to extract such features to predict liver toxicity, while the computational model was optimized to predict whether a drug compound can cause liver necrosis and identify target gene biomarkers as disease indicators.228 Here, the model identified predictor biomarkers that are involved in liver metabolism and detoxification (i.e., Car3, Crat, Cyp39a1, Dcd, Lbp, Scly, Slc23a1, and Tkfc), carcinogenesis as well as transcriptional regulation (i.e., Ablim3). In the future, similar methods could be used to boost the prediction of drug toxicity effects in humans. In fact, developing machine learning algorithms and bioinformatics methodologies are relatively cost-effective and could reduce the overall time to market safe drug products.
Moreover, the public debate should focus on emerging challenges such as biobanking frontiers, which would help long-term studies on patient-derived liver tissues for drug development. These biological samples, which can be collected in-hospital or during community screenings, can be maintained and used at a later stage for research purposes, at the border with healthcare outputs. Importantly, the engineered constructs should accomplish clinical-grade quality and good manufacturing practices (GMP).93 Herein, organoid models may closely recapitulate both the native and the diseased organs. Parallelly, they can be used to predict drug sensitivity and identify biomarkers for treatment response in different population groups. However, there is still an urgent need to fully validate the tissue heterogeneity and physiological relevance of 3D engineered in vitro models and the effectiveness of drug testing applications, respectively. Indeed, this would potentially allow for their clinical translation towards individualized treatments and therapy effects.232 Therefore, it is of foremost importance to clinically validate in vitro outcomes in humans.233–235
Similarly, somatic genome editing platforms (e.g., TALEN, ZFN, CRISPR/Cas9) could be also considered as an halfway point to design liver disease models for metabolic and acquired disorders with clinical therapy purposes, thus identifying responsible genes and mutational profile of liver diseases and hepatic cancer.93,211 For instance, such platforms were employed to model liver disease as HCC, inducing carcinogenesis in healthy liver 3D engineered constructs such as organoids.236
2DMC | Two-dimensional monolayer culture |
3T3-J2 | Mouse embryonic fibroblasts |
5-FU | 5-Fluorouracil |
ABCB1 | Atp binding cassette subfamily B member 1 |
AAT | Alpha-1 antitrypsin |
ACTA2 | Actin alpha 2 |
AFP | Alpha-fetoprotein |
ALD | Alcoholic liver disease |
AML12 | Alpha mouse liver 12 hepatocytes |
APAP | Acetaminophen |
ASS1 | Argininosuccinate synthetase 1 |
CF | Cystic fibrosis |
CFTR | Cystic fibrosis transmembrane conductance regulator |
CLD | Chronic liver disease |
COL1A1 | Collagen type I alpha 1 chain |
CNC | Cellulose nanocrystals |
CTLN1 | Citrullinemia type 1 |
CRISPR | Clustered regularly interspaced short palindromic repeat |
CYP2C9 | Cytochrome P450 family 2 subfamily C member 9 |
CYP3A4 | Cytochrome P450 3A4 |
CYP450 | Cytochrome P450 |
dECM | Decellularized extracellular matrix |
DILI | Drug-induced liver injury |
DNA | Deoxyribonucleic acid |
DOX | Doxorubicin |
ECM | Extracellular matrix |
EGFR | Estimated glomerular filtration rate |
EpCAM+ | Epithelial cell adhesion molecule positive |
EtOH | Ethanol |
FN | Fibronectin |
GelMA | Gelatin methacryloyl |
GK | Glucokinase |
HA | Hyaluronic acid |
HAM | Hyaluronic acid-coated microcarriers |
HCC | Hepatocellular carcinoma |
HCT-116 | Human colon carcinoma cells |
HBV | Hepatitis B virus |
HepG2 | Human hepatoma G2 cells |
HepaRG | Human hepatic progenitor cells |
hESC | Human embryonic stem cells |
hFLMC | Human fetal liver mesenchymal cells |
HHH | Healthy human hepatocytes |
hiHEP | Human induced hepatocytes |
hiPSC | Human induced pluripotent stem cells |
HLC | Hepatocyte-like cells |
hLECM | Human liver extracellular matrix |
HMEC-1 | Human microvascular endothelial cells |
HNF4A | Hepatocyte nuclear factor 4 alpha |
HPC | Hepatic progenitor cells |
hPH | Human primary hepatocytes |
HSC | Hepatic stellate cells |
HUH-7 | Human hepatoma cell line 7 |
HUVEC | Human umbilical vein endothelial cells |
IC50 | Half-maximal inhibitory concentration |
IGF-2 | Insulin-like growth factor 2 |
IPN | Interpenetrating network |
iPSC | Induced pluripotent stem cells |
LTE | Liver tissue engineering |
LX-2 | Lieming Xu-2 human hepatic stellate cells |
MDR-1 | Multidrug resistance protein 1 |
MPS | Mucopolysaccharidosis |
MRP1 | Multidrug resistance associated protein 1 |
NaB | Sodium butyrate |
NAFLD | Non-alcoholic fatty liver disease |
NASH | Non-alcoholic steatohepatitis |
NIH 3T3 | Mouse embryonic fibroblasts |
PCL | Polycaprolactone |
PEG | Polyethylene glycol |
PEGDA | Polyethylene glycol diacrylate |
PHH | Primary human hepatocytes |
PLA | Polylactide acid |
PLC | Primary liver cancer cells |
PLGA | Poly-DL-lactide-co-glycolide |
PLLA | Poly-L-lactic acid |
pNIPAAm | Poly(N-isopropyl acrylamide) |
PEPCK | Phosphoenolpyruvate carboxykinase |
PRH | Primary rat hepatocytes |
PU | Polyurethane |
PVA | Polyvinyl alcohol |
RGD | Arginine–glycine–aspartic acid |
RLC-18 | Rat liver cells |
ROS | Reactive oxygen species |
TALEN | Transcription activator-like effector nucleases |
TGFβ-1 | Transforming growth factor beta 1 |
THLE-3 | Transformed human liver epithelial-3 |
THP-1 | Tamm-horsfall protein 1 kupffer cells |
TNFα | Tumour necrosis factor A |
TTR | Transthyretin |
VA | Valproic acid |
ZFN | Zinc finger nucleases |
Fig. 1, 2, 3A, 4A, 5 and 6, and the graphical abstract are created with Biorender.com.
Footnote |
† These authors equally contributed to this work. |
This journal is © The Royal Society of Chemistry 2023 |