Linking molecular classification of hepatocellular carcinoma and personalized medicine: preliminary steps

Abstract

Purpose of review: The development of high-throughput technologies able to simultaneously investigate thousands of genes (e.g. single nucleotide polymorphism-array, gene expression microarray, etc.) has opened a new era in translational research. Obtaining a molecular classification of hepatocellular carcinoma, however, remains a striking challenge. This review summarizes the molecular classifications of hepatocellular carcinoma reported so far, analyzes the status of targeted therapies tested in clinical trials, and evaluates feasibility of personalized medicine approaches in hepatocellular carcinoma.

Recent findings: Different investigators attempted to classify patients according to their liver cancer molecular background, a feature that will path the way for trial enrichment and personalized medicine. Currently, hepatocellular carcinoma can be classified in molecular classes according to Wnt-beta-catenin pathway activation, proliferation signature activation (associated with chromosomal instability), and other subgroups. In parallel, the first-time-ever positive results of a phase III trial in advanced hepatocellular carcinoma with the multikinase inhibitor sorafenib have encouraged this approach.

Summary: Selection of patient candidates according to their tumor molecular background is a reality in human malignancies. Thus, a molecular classification is essential to allow the development of new targets, and to customize therapies in patients with hepatocellular carcinoma.

Figure 1

Signaling pathways and targeted therapies in HCC. This figure summarizes some of the most relevant signaling pathways analyzed in human HCC (RAS/MAPK, Akt/mTOR, Wnt-βcatenin and Hedgehog). Also, it shows different drugs in clinical and preclinical development for the specific blockade of these pathways.