Analysis of differentially expressed genes among human hair follicle-derived iPSCs, induced hepatocyte-like cells, and primary hepatocytes

Differentiation of human induced pluripotent stem cells (hiPSCs) into hepatocytes has important clinical significance in providing a new stem cell source for cell therapy of terminal liver disease. The differential gene expression analysis of hiPSCs, induced hepatocyte-like cells (HLCs), and primary human hepatocytes (PHHs) provides valuable information for optimization of an induction scheme and exploration of differentiation mechanisms.

We presented the differences in gene expression among hHF-iPSCs, HLCs, and PHHs through transcriptome array data and provided new ideas for the optimization of induction.

Human hair follicle-derived iPSCs (hHF-iPSCs) were induced in vitro by mimicking the environment of a developing liver for 19 days. Expression of specific proteins was determined by immunofluorescence staining; the function of HLCs in storage and metabolism was identified by detecting periodic acid-Schiff, indocyanine green, and low-density lipoprotein. Based on the transcriptomics data, the differential gene expression profiles of hHF-iPSCs, HLCs, and PHHs were analyzed by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway, FunRich, and network analysis methods.

HLCs were able to express albumin (ALB), alpha-fetoprotein, CYP3A4, and CYP7A1, and exhibited matured liver cell functions such as glycogen synthesis and storage. Complement and coagulation cascades and metabolic pathways ranked top in the downregulated list of HLCs/PHHs, while the cell cycle ranked top in the upregulated list of HLCs/PHHs. In the protein-protein interaction network, according to the degree rankings, TOP2A, CDK1, etc. were the important upregulated differentially expressed genes (DEGs), while ALB, ACACB, etc. were the major downregulated DEGs in HLCs/PHHs; the module analysis indicated that CDCA8, AURKB, and AURKA were the top upregulated DEGs in HLCs/PHHs. Conclusions: We presented the differences in gene expression among hHF-iPSCs, HLCs, and PHHs through transcriptome array data and provided new ideas for the optimization of induction.