SEARCH

SEARCH BY CITATION

Keywords:

  • bioinformatics;
  • HCC ;
  • liver cancer;
  • oncogenomics;
  • systems biology

Abstract

Background & Aims

Therapeutic options for hepatocellular carcinoma (HCC) still remain limited. Development of gene targeted therapies is a promising option. A better understanding of the underlying molecular biology is gained in in vitro experiments. However, even with targeted manipulation of gene expression varying treatment responses were observed in diverse HCC cell lines. Therefore, information on gene expression profiles of various HCC cell lines may be crucial to experimental designs. To generate a publicly available database containing microarray expression profiles of diverse HCC cell lines.

Methods

Microarray data were analyzed using an individually scripted R program package. Data were stored in a PostgreSQL database with a PHP written web interface. Evaluation and comparison of individual cell line expression profiles are supported via public web interface.

Results

This database allows evaluation of gene expression profiles of 18 HCC cell lines and comparison of differential gene expression between multiple cell lines. Analysis of commonly regulated genes for signaling pathway enrichment and interactions demonstrates a liver tumor phenotype with enrichment of major cancer related KEGG signatures like ‘cancer’ and ‘inflammatory response’. Further molecular associations of strong scientific interest, e.g. ‘lipid metabolism’, were also identified.

Conclusions

We have generated CellMinerHCC (http://www.medicalgenomics.org/cellminerhcc), a publicly available database containing gene expression data of 18 HCC cell lines. This database will aid in the design of in vitro experiments in HCC research, because the genetic specificities of various HCC cell lines will be considered.