Genome-scale profiling of gene expression in hepatocellular carcinoma: classification, survival prediction, and identification of therapeutic targets

Abstract

The heterogeneous nature of human hepatocellular carcinoma (HCC) has hampered both treatment and prognostic predictions. Gene expression profiles of human HCC were analyzed to define the molecular characteristics of the tumors and to test the prognostic value of the expression profiles. By applying global gene expression analyses, including unsupervised and supervised methods, 2 distinctive subclasses of HCC that were highly homogeneous for both the underlying biology and the clinical outcome were discovered. Tumors from the low survival subclass had strong cell proliferation and antiapoptosis gene expression signatures. In addition, the low survival subclass displayed higher expression of genes involved in ubiquitination and sumoylation, suggesting an etiologic involvement of these processes in accelerating the progression of HCC. Genes most strongly associated with survival were identified by using the Cox proportional hazards survival analysis. This approach identified a limited number of genes that accurately predicted the length of survival and provided new molecular insights into the pathogenesis of HCC. Future studies will evaluate potential diagnostic markers and therapeutic targets identified during the global gene expression studies. Furthermore, cross-species similarity of gene expression patterns will also allow prioritization of a long list of genes obtained from human gene expression profiling studies and focus on genes whose expression is altered during tumorigenesis in both species.