Hepatocellular carcinoma (HCC) is a fatal disease occurring worldwide and developing mainly in chronic liver diseased patients. Despite routine screening of individuals at high risk, most of the patients are diagnosed at late stages of HCC. In addition, the recurrence rate after surgical resection of small tumors is high. Molecular profiling, including expression analysis, comparative genomics and proteomics, provides powerful tools to gain insight into the molecular mechanisms underlying carcinogenesis. Advances in bioinformatics have also allowed for the evaluation of large data sets. Therefore, molecular profiling of HCC using a Biological Expression Network Discovery (BLEND) strategy that integrates global molecular profiling data, including mRNA, miRNA, DNA methylation and DNA copy numbers from both the tumor and the surrounding microenvironment, along with mechanistic studies, may improve the diagnosis, treatment and prognosis of HCC patients. Such an approach will provide mechanistic insight into the pathogenesis of HCC, potentially leading to personalized medicine and the identification of new therapeutic targets.