Patients

were staged according to the TNM 6th edition (2006) and Barcelona Clinic Liver Cancer staging system.19 Tumor size was based on the largest dimension of the tumor specimen. Tumor grade was scored using the modified nuclear grading scheme outlined by Edmondson and Steiner.20 Grades 1 and 2 were defined as well-differentiated and grades 3 and 4 as moderately/poorly differentiated. The majority of patients in the three cohorts had not received anti-HBV treatment after surgery. The Eastern Cooperative Oncology Group (ECOG) performance score of all patients was 0 or 1. The presence of cirrhosis was also confirmed on the surgical specimen. OS was defined as the NVP-AUY922 solubility dmso time from surgery to death and censored when a patient was alive at last contact. Table 1 shows the pathologic and clinical characteristics of the patients in all five cohorts. All patients had undergone surgical resection as their primary treatment. Patient data were retrospectively collected from medical records. BCLC staging is based on preoperation data, and vasculature

invasion is pathologically defined as the presence of endolymphatic or lymphovascular tumor emboli within tumors. Survival data are not publicly available for the MSH and INSERM cohorts; thus, these patients were not used for survival analyses. For generation of gene expression data from the Korean cohort, total RNA was isolated from tissue samples using a mirVana RNA Isolation labeling kit (Ambion, Austin, TX). Five hundred nanograms Everolimus solubility dmso of total RNA were used for labeling and hybridization, in accordance with the manufacturer’s protocols (Illumina).

After the bead chips were scanned with an Illumina BeadArray Reader (Illumina), the microarray data were normalized using the quantile normalization method in the Linear Models for Microarray Data package in the R language environment (http://www.r-project.org).21 The expression level of each gene was transformed into a log-2 base for further analysis. Primary microarray data are available from the NCBI GEO public database check (accession number GSE16757). BRB-ArrayTools were primarily used for statistical analysis of gene expression data22 and all other statistical analyses were performed in the R language environment. We estimated patient prognoses using Kaplan-Meier plots and the log-rank test. Stratification of patients in the NCI cohort according to Seoul National University (SNU) recurrence signature was done as described.18 Receiver-operating characteristic (ROC) curve analyses were carried out to estimate discriminatory power of the prognostic gene expression signatures and clinical variables. We calculated the area under the curve (AUC), which ranges from 0.5 (for a noninformative predictive marker) to 1 (for a perfect predictive marker) and a bootstrap method (1,000 resampling) was used to calculate the 95% confidence internal (CI) for AUC.