Molecular prognostication of liver cancer: End of the beginning

Abstract

New technological developments have frequently preceded major advances in biomedical research and medicine [1]. For example, the development of fluorescent DNA sequencing techniques made it possible to establish the large-scale high-throughput technology needed for human genome sequencing. Polymerase chain reaction (PCR), fluorescent DNA sequencing, and other techniques have enabled the discovery of about 1700 mendelian disease genes [2]. The advent of the DNA microarray based technologies has now made it possible to measure simultaneously the expression of tens of thousands of genes in different tissues under a variety of conditions. This high-throughput technology has afforded biomedical scientists a unique opportunity to integrate the descriptive characteristics (i.e. ‘phenotype’) of a biological system under study with the genomic readout (i.e. gene expression). The opportunity to contemplate the integrated view of biological systems has provoked a shift in biological sciences away from the classical reductionism to systems biology [1,3,4]. The systems approach to a disease is based on the hypothesis that disease processes perturb a regulatory network of genes and proteins in a way that differs from the respective normal counterpart. Consequently, by using multi-parametric measurements it may be possible to transform current diagnostic and therapeutic approaches and enable a predictive and preventive personalized medicine [4]. The application of microarray technologies to characterize tumors at the gene expression level has significantly impacted clinical oncology [5,6]. Global gene expression analysis of various human tumors has resulted in