Gene expression profiling in paired human hepatocellular carcinoma and liver parenchyma biopsies and normal liver biopsies.

Hepatocellular carcinoma (HCC) is a heterogeneous disease, and despite considerable research efforts, no molecular classification of HCC has been introduced in clinical practice. The existing molecular classification systems were established using resected tumors, which introduces a selection bias towards patients without liver cirrhosis and with early stage HCCs. So far, these classification systems have not been validated in liver biopsy specimens from tumors diagnosed at intermediate and late stages. We generated and analyzed expression profiles from 60 HCC biopsies from an unselected patient population with all tumor stages. Unbiased clustering identified 3 HCC classes. Class membership correlated with survival, tumor size, and with Edmondson and BCLC stage. Most biopsy specimens could be assigned to the classes of published classification systems, demonstrating that gene expression profiles obtained from patients with early stage disease are preserved in all stages of HCC. When a reference set of healthy liver samples was integrated in the analysis, we observed that the differentially regulated genes up- or down-regulated in a given class relative to other classes were actually dysregulated in the same direction in all HCCs, with quantitative rather than qualitative differences between the molecular subclasses. With the exception of a subset of samples with a definitive -catenin gene signature, biological pathway analysis could not identify class specific pathways reflecting the activation of distinct oncogenic programs. Our results suggest that gene expression profiling of HCC biopsies has limited potential to direct therapies that target specific driver pathways, but can identify subgroups of patients with different prognosis.

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Makowska Z, Boldanova T, Adametz D, Quagliata L, Vogt JE, Dill MT, Matter MS, Roth V, Terracciano L, Heim MH