Decoding human liver cancer signatures.

Because alterations of expression patterns and genomic copy numbers of thousands of genes are fundamental properties of cancer cells, and the application of high-throughput microarray-based genomic technologies for the analysis of cancer inevitably generate many false-positive results, it is rarely possible to select a reasonable number of candidate genes for therapeutic targets and/or biomarkers for diagnosis and prognosis. Therefore, it will be necessary to devise new experimental and analytical strategies to overcome this problem. This review summarizes recent advances in gene expression profiling of hepatocellular carcinoma and discusses future strategies for analyzing large and complicated data sets from microarray studies and how to integrate these with diverse genomic data.