Molecular-based prediction of early recurrence in hepatocellular carcinoma

Abstract

Background/aims: Hepatocellular carcinoma (HCC) has a very poor prognosis, due to the high incidence of tumor recurrence. As the current morphological indicators are often insufficient for therapeutic decisions, we sought to identify additional biologic indicators for early recurrence.

Methods: We analyzed gene expression using a PCR-based array of 3,072 genes in 100 HCC patients. Informative genes predicting early intrahepatic recurrence were selected by random permutation testing, and a weighted voting prediction method was constructed. Following estimation of prediction accuracy, a multivariate Cox analysis was performed.

Results: By permutation testing, we selected 92 genes demonstrated distinct expression patterns differing significantly between recurrence cases and recurrence-free cases. Our prediction method, using the 20 top-ranked genes, correctly predicted the early intrahepatic recurrence for 29 of 40 cases within the validation group, and the odds ratio was 6.8 (95%CI 1.7-27.5, P = 0.010). The 2-year recurrence rates in the patients with the good signature and those with the poor signature were 29.4 and 73.9%, respectively. Multivariate Cox analysis revealed that molecular-signature was an independent indicator for recurrence (hazard ratio 3.82, 95%CI 1.44-10.10, P = 0.007).

Conclusions: Our molecular-based prediction method using 20 genes is clinically useful to predict early recurrence of HCC.