MicroRNA (miRNAs) are negative regulators of gene expression and can function as tumor suppressors or oncogenes. Expression patterns of miRNAs and their role in the pathogenesis of hepatocellular carcinoma (HCC) are still poorly understood. We profiled miRNA expression in tissue samples (104 HCC, 90 adjacent cirrhotic livers, 21 normal livers) as well as in 35 HCC cell lines. A set of 12 miRNAs (including miR-21, miR-221/222, miR-34a, miR-519a, miR-93, miR-96, and let-7c) was linked to disease progression from normal liver through cirrhosis to full-blown HCC. miR-221/222, the most upregulated miRNAs in tumor samples, are shown to target the CDK inhibitor p27 and to enhance cell growth in vitro. Conversely, these activities can be efficiently inhibited by an antagomiR specific for miR-221. In addition, we show, using a mouse model of liver cancer, that miR-221 overexpression stimulates growth of tumorigenic murine hepatic progenitor cells. Finally, we identified DNA damage-inducible transcript 4 (DDIT4), a modulator of mTOR pathway, as a bona fide target of miR-221. Taken together, these data reveal an important contribution for miR-221 in hepatocarcinogenesis and suggest a role for DDIT4 dysregulation in this process. Thus, the use of synthetic inhibitors of miR-221 may prove to be a promising approach to liver cancer treatment.hepatocarcinogenesis | microRNA | antagomiRs | mouse model | DDIT4

BACKGROUND-The advent of targeted therapies in hepatocellular carcinoma (HCC) has underscored the importance of pathway characterization to identify novel molecular targets for treatment. Based on its role in cell growth and differentiation, we evaluated mTOR signaling activation in human HCC, as well as the anti-tumoral effect of a dual-level blockade of the mTOR pathway.

RFA is a safe and effective treatment of small HCC in cirrhotics awaiting OLT, although tumor size (>3 cm) and time from treatment (>1 year) predict a high risk of tumor persistence in the targeted nodule. RFA should not be considered an independent therapy for HCC.

Epigenetic deregulation has emerged as a driver in human malignancies. There is no clear understanding of the epigenetic alterations in hepatocellular carcinoma (HCC) and of the potential role of DNA methylation markers as prognostic biomarkers. Analysis of tumor tissue from 304 patients with HCC treated with surgical resection allowed us to generate a methylation‐based prognostic signature using a training‐validation scheme. Methylome profiling was done with the Illumina HumanMethylation450 array (Illumina, Inc., San Diego, CA), which covers 96% of known cytosine‐phosphate‐guanine (CpG) islands and 485,000 CpG, and transcriptome profiling was performed with Affymetrix Human Genome U219 Plate (Affymetrix, Inc., Santa Clara, CA) and miRNA Chip 2.0. Random survival forests enabled us to generate a methylation signature based on 36 methylation probes. We computed a risk score of mortality for each individual that accurately discriminated patient survival both in the training (221 patients; 47% hepatitis C–related HCC) and validation sets (n = 83; 47% alcohol‐related HCC). This signature correlated with known predictors of poor outcome and retained independent prognostic capacity of survival along with multinodularity and platelet count. The subset of patients identified by this signature was enriched in the molecular subclass of proliferation with progenitor cell features. The study confirmed a high prevalence of genes known to be deregulated by aberrant methylation in HCC (e.g., Ras association [RalGDS/AF‐6] domain family member 1, insulin‐like growth factor 2, and adenomatous polyposis coli) and other solid tumors (e.g., NOTCH3) and describes potential candidate epidrivers (e.g., septin 9 and ephrin B2). Conclusions: A validated signature of 36 DNA methylation markers accurately predicts poor survival in patients with HCC. Patients with this methylation profile harbor messenger RNA–based signatures indicating tumors with progenitor cell features. (Hepatology 2015;61:1945–1956)

Background & Aims In approximately 70% of patients with hepatocellular carcinoma (HCC) treated by resection or ablation, disease recurs within 5 years. Although gene expression signatures have been associated with outcome, there is no method to predict recurrence based on combined clinical, pathology, and genomic data (from tumor and cirrhotic tissue). We evaluated gene expression signatures associated with outcome in a large cohort of patients with early-stage (BCLC 0/A), single-nodule HCC and heterogeneity of signatures within tumor tissues. Methods We assessed 287 HCC patients undergoing resection and tested genome-wide expression platforms using tumor (n=287) and adjacent non-tumor, cirrhotic tissue (n=226). We evaluated gene expression signatures with reported prognostic ability generated from tumor or cirrhotic tissue in 18 and 4 reports, respectively. In 15 additional patients, we profiled samples from the center and periphery of the tumor, to determine stability of signatures. Data analysis included Cox modeling and random survival forests to identify independent predictors of tumor recurrence. Results Gene expression signatures that were associated with aggressive HCC were clustered, as well as those associated with tumors of progenitor cell origin and those from non-tumor, adjacent, cirrhotic tissues. On multivariate analysis, the tumor-associated signature “G3-proliferation” (hazard ratio [HR]=1.75, P=0.003) and an adjacent “poor-survival” signature (HR=1.74, P=0.004) were independent predictors of HCC recurrence, along with satellites (HR=1.66, P=0.04). Samples from different sites in the same tumor nodule were reproducibly classified. Conclusions We developed a composite prognostic model for HCC recurrence, based on gene expression patterns in tumor and adjacent tissues. These signatures predict early and overall recurrence in patients with HCC, and complement findings from clinical and pathology analyses.