Cells (Sep 2024)
Human Multi-Lineage Liver Organoid Model Reveals Impairment of CYP3A4 Expression upon Repeated Exposure to Graphene Oxide
Abstract
Three-dimensional hepatic cell cultures can provide an important advancement in the toxicity assessment of nanomaterials with respect to 2D models. Here, we describe liver organoids (LOs) obtained by assembling multiple cell lineages in a fixed ratio 1:1:0.2. These are upcyte® human hepatocytes, UHHs, upcyte® liver sinusoidal endothelial cells, LSECs, and human bone marrow-derived mesenchymal stromal cells, hbmMSCs. The structural and functional analyses indicated that LOs reached size stability upon ca. 10 days of cultivation (organoid maturation), showing a surface area of approximately 10 mm2 and the hepatic cellular lineages, UHHs and LSECs, arranged to form both primitive biliary networks and sinusoid structures, alike in vivo. LOs did not show signs of cellular apoptosis, senescence, or alteration of hepatocellular functions (e.g., dis-regulation of CYP3A4 or aberrant production of Albumin) for the entire culture period (19 days since organoid maturation). After that, LOs were repeatedly exposed for 19 days to a single or repeated dose of graphene oxide (GO: 2–40 µg/mL). We observed that the treatment did not induce any macroscopic signs of tissue damage, apoptosis activation, and alteration of cell viability. However, in the repeated dose regimen, we observed a down-regulation of CYP3A4 gene expression. Notably, these findings are in line with recent in vivo data, which report a similar impact on CYP3A4 when mice were repeatedly exposed to GO. Taken together, these findings warn of the potential detrimental effects of GO in real-life exposure (e.g., occupational scenario), where its progressive accumulation is likely expected. More in general, this study highlights that LOs formed by many cell lineages can enable repeated exposure regimens (suitable to mimic accumulation); thus, they can be suitably considered alternative or complementary in vitro systems to animal models.
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