4.6 Article

Gene expression profiles of liver cancer cell lines reveal two hepatocyte-like and fibroblast-like clusters

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PLOS ONE
卷 16, 期 2, 页码 -

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PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0245939

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  1. Project for Cancer Research and Therapeutic Evolution (PCREATE) from the Japan Agency for Medical Research and Development (AMED) [19cm0106303h0004]
  2. Ministry of Education, Culture, Sports, Science and Technology of Japan [20K08996, 17K10510]

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Cancer cell lines are widely used in research for studying cancer development and drug screening. This study analyzed liver cancer cell lines and found two main clusters based on gene expression patterns, one resembling hepatocytes and the other fibroblasts. The findings may aid in selecting appropriate cell lines for liver cancer research, and utilizing public databases for comparing cell line properties could be a useful strategy for other research fields.
Cancer cell lines are widely used in basic research to study cancer development, growth, invasion, or metastasis. They are also used for the development and screening of anticancer drugs. However, there are no clear criteria for choosing the most suitable cell lines among the wide variety of cancer cell lines commercially available for research, and the choice is often based on previously published reports. Here, we investigated the characteristics of liver cancer cell lines by analyzing the gene expression data available in the Cancer Cell Line Encyclopedia. Unsupervised clustering analysis of 28 liver cancer cell lines yielded two main clusters. One cluster showed a gene expression pattern similar to that of hepatocytes, and the other showed a pattern similar to that of fibroblasts. Analysis of hepatocellular carcinoma gene expression profiles available in The Cancer Genome Atlas showed that the gene expression patterns in most hepatoma tissues were similar to those in the hepatocyte-like cluster. With respect to liver cancer research, our findings may be useful for selecting an appropriate cell line for a specific study objective. Furthermore, our approach of utilizing a public database for comparing the properties of cell lines could be an attractive cell line selection strategy that can be applied to other fields of research.

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