title: Hepatocellular carcinoma: a systems biology perspective.
abstract: Hepatocellular carcinomas (HCCs) have different etiology and heterogenic genomic alterations lead to high complexity. The molecular features of HCC have largely been studied by gene expression and proteome profiling focusing on the correlations between the expression of specific markers and clinical data. Integration of the increasing amounts of data in databases has facilitated the link of genomic and proteomic profiles of HCC to disease state and clinical outcome. Despite the current knowledge, specific molecular markers remain to be identified and new strategies are required to establish novel-targeted therapies. In the last years, mathematical models reconstructing gene and protein networks based on experimental data of HCC have been developed providing powerful tools to predict candidate interactions and potential targets for therapy. Furthermore, the combination of dynamic and logical mathematical models with quantitative data allows detailed mechanistic insights into system properties. To address effects at the organ level, mathematical models reconstructing the three-dimensional organization of liver lobules were developed. In the future, integration of different modeling approaches capturing the effects at the cellular up to the organ level is required to address the complex properties of HCC and to enable the discovery of new targets for HCC prevention or treatment.
authors: Division Systems Biology of Signal Transduction, DKFZ-ZMBH Alliance, German Cancer Research Centre (DKFZ) Heidelberg, Germany.
authors: Lorenza A
authors: LA
authors: D'Alessandro
authors: René
authors: R
authors: Meyer
authors: Ursula
authors: U
authors: Klingmüller
keywords: HCC; gene expression profile; hepatocytes; liver; mathematical modeling; network analysis; proteomic