Comparative Transcriptomic Analysis of Three Common Liver Cell Lines

Abstract

Background: Comparative transcriptomic analysis is a powerful approach for investigating the molecular mechanisms underlying various physiological and pathological processes, including liver disease. The liver is a vital organ with diverse functions, including metabolism and detoxification. In vitro models of liver cells, such as HepG2, Huh7, and Hep3B, have been widely used to study liver biology and pathology. However, there is limited information on the heterogeneity of these cell lines at the transcriptomic level. Objective: This study aimed to conduct a comparative transcriptomic analysis of three common liver cell lines (HepG2, Huh7, and Hep3B) using publicly available RNA-sequencing data. In addition, we compared these cell lines to primary hepatocytes, cells isolated directly from liver tissue and considered the gold standard for studying liver function and disease. Methods: Our study included sequencing data with the following criteria: total number of reads over 20,000,000, average read length of over 60 base pairs, Illumina sequencing, and non-treated cells. The data for the three cell lines were compiled: HepG2 (97 samples), Huh7 (39 samples), and Hep3B (16 samples). We performed differential gene expression analysis using the DESeq2 package, principal component analysis, hierarchical clustering on principal components, and correlation analysis to explore the heterogeneity within each cell line. Results: We identified numerous genes and pathways differentially expressed between HepG2, Huh7, and Hep3B, such as oxidative phosphorylation, cholesterol metabolism, and DNA damage. We report that the expression levels of important genes differ significantly between primary hepatocytes and liver cell lines. Conclusion: Our study provides new insights into the transcriptional heterogeneity of commonly used liver cell lines and highlights the importance of considering specific cell line. Consequently, transferring results without considering the heterogeneity of cell lines is impractical and may lead to inaccurate or distorted conclusions.

Deciphering the Genetic Orchestra: Unveiling Splice Form Dynamics in Human Cell Lines

“…Given the limited number of cell lines and relevant samples available, our results should be considered preliminary. Gene expression, as a set of transcript expressions, is a more constant value within samples of a single cell line than the expression of each transcript [30]. At the same time, for normalizing the use of housekeeping genes, it has been proposed that the focus is on stably expressed transcripts [4].…”

“…The search for raw public RNAseq data was performed in the NCBI SRA database (https://www.ncbi.nlm.nih.gov/sra, accessed on January 22, 2024). We applied criteria established in a previous study [30]: total first/second fragment count > 20,000,000; average read length > 60 base pairs; untreated cells; Illumina sequencing technology. Accession numbers for the experiments are provided in Supplementary Table S1.…”