Relating hepatocellular carcinoma tumor samples and cell lines using gene expression data in translational research

BMC Med Genomics. 2015;8 Suppl 2(Suppl 2):S5. doi: 10.1186/1755-8794-8-S2-S5. Epub 2015 May 29.


Cancer cell lines are used extensively to study cancer biology and to test hypotheses in translational research. The relevance of cell lines is dependent on how closely they resemble the tumors being studied. Relating tumors and cell lines, and recognizing their similarities and differences are thus very important for translational research. Rapid advances in genomics have led to the generation of large volumes of genomic and transcriptomic data for a diverse set of primary cancer samples, normal tissue samples and cancer cell lines. Hepatocellular Carcinoma (HCC) is one of the most common tumors worldwide, with high occurrence in Asia and sub-Saharan regions. The current effective treatments of HCC remain limited. In this work, we compared the gene expression measurements of 200 HCC tumor samples from The Cancer Genome Atlas and over 1000 cancer cell lines including 25 HCC cancer cell lines from Cancer Cell Line Encyclopedia. We showed that the HCC tumor samples correlate closely with HCC cell lines in comparison to cell lines derived from other tumor types. We further demonstrated that the most commonly used HCC cell lines resemble HCC tumors, while we identified nearly half of the cell lines that do not resemble primary tumors. Interestingly, a substantial number of genes that are critical for disease development or drug response are either expressed at low levels or absent among highly correlated cell lines; additional attention should be paid to these genes in translational research. Our study will be used to guide the selection of HCC cell lines and pinpoint the specific genes that are differentially expressed in either tumors or cell lines.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Carcinoma, Hepatocellular / genetics*
  • Cell Line, Tumor
  • Gene Expression Regulation, Neoplastic*
  • Gene Ontology
  • Humans
  • Liver Neoplasms / genetics*
  • Statistics, Nonparametric
  • Translational Research, Biomedical*