CellMinerHCC: A microarray-based expression database for hepatocellular carcinoma cell lines

Frank Staib, Markus Krupp, Thorsten Maass, Timo Itzel, Arndt Weinmann, Ju Seog Lee, Bertil Schmidt, Martina Müller, Snorri S. Thorgeirsson, Peter R. Galle, Andreas Teufel

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)621-631
Number of pages11
JournalLiver International
Volume34
Issue number4
DOIs
StatePublished - Apr 2014

Keywords

  • Bioinformatics
  • HCC
  • Liver cancer
  • Oncogenomics
  • Systems biology

ASJC Scopus subject areas

  • Hepatology

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