A liver‐specific gene expression panel predicts the differentiation status of in vitro hepatocyte models

Abstract

Alternative cell sources, such as three‐dimensional organoids and induced pluripotent stem cell–derived cells, might provide a potentially effective approach for both drug development applications and clinical transplantation. For example, the development of cell sources for liver cell–based therapy has been increasingly needed, and liver transplantation is performed for the treatment for patients with severe end‐stage liver disease. Differentiated liver cells and three‐dimensional organoids are expected to provide new cell sources for tissue models and revolutionary clinical therapies. However, conventional experimental methods confirming the expression levels of liver‐specific lineage markers cannot provide complete information regarding the differentiation status or degree of similarity between liver and differentiated cell sources. Therefore, in this study, to overcome several issues associated with the assessment of differentiated liver cells and organoids, we developed a liver‐specific gene expression panel (LiGEP) algorithm that presents the degree of liver similarity as a “percentage.” We demonstrated that the percentage calculated using the LiGEP algorithm was correlated with the developmental stages of in vivo liver tissues in mice, suggesting that LiGEP can correctly predict developmental stages. Moreover, three‐dimensional cultured HepaRG cells and human pluripotent stem cell–derived hepatocyte‐like cells showed liver similarity scores of 59.14% and 32%, respectively, although general liver‐specific markers were detected. Conclusion: Our study describes a quantitative and predictive model for differentiated samples, particularly liver‐specific cells or organoids; and this model can be further expanded to various tissue‐specific organoids; our LiGEP can provide useful information and insights regarding the differentiation status of in vitro liver models. (Hepatology 2017;66:1662–1674).

Tumor Cell Biodiversity Drives Microenvironmental Reprogramming in Liver Cancer

“…The inferred CNV profiles are consistent with the CNV profiles in HCC and iCCA from previously published studies (Chaisaingmongkol et al, 2017;Katoh et al, 2007;Roessler et al, 2012). We further confirmed the successful enrichment of malignant and non-malignant cells based on the epithelial marker genes and liver marker genes, which differ in their expression between malignant cells and stromal cells (Kim et al, 2017;Puram et al, 2017). The expression of these marker genes is highly concordant with the karyotypes of malignant cells and non-malignant ones ( Figure 1E).…”

Developing scalable cultivation systems of hepatic spheroids for drug metabolism via genomic and functional analyses

“…A comparison study to detect possible paracrine effects (unknown soluble factors) from populated spheroids on CYP3A4 activity was performed and did not show any significant differences between the group used in this study and a group with fewer spheroids (three spheroids in one conical tube, i.e., 15 ml volume; Figure S7) during the differentiation culture period. The heat map analysis of the liver‐specific gene expression panel (LiGEP) illustrated the high shear stress‐elevated differentiation level of the 3D HepaRG spheroids (Figure f(i); Kim et al, ), and also showed the shear stress dependence of Phase I and II enzyme gene expression; overall high in SFU, intermediate in OS, and low in static mode (Figure f(ii,iii)). CYP3A4 is the most important Phase I enzyme related to drug metabolism, with various CYP3A4 activity‐related factor‐binding sites existing in the promoter region (Figure f(iv)).…”

In vitro and in vivo imaging and tracking of intestinal organoids from human induced pluripotent stem cells

“…After 2-3 wk, hESC-like hiPSC colonies were selected and subsequently expanded for further characterization. Fibroblasts and hiPSCs were cultured as previously described (13,14).…”