The Genomic Landscape and Its Clinical Implications in Hepatocellular Carcinoma

The pathogenesis of hepatocellular carcinoma (HCC) is a complex process. During the last decade, advances in genomic technologies enabled delineation of the genomic landscape of HCC, resulting in the identification of the common underlying molecular alterations. The tumor microenvironment, regulated by inflammatory cells, including cancer cells, stromal tissues, and the surrounding extracellular matrix, has been extensively studied using molecular data. The integration of molecular, immunological, histopathological, and clinical findings has provided clues to uncover predictive biomarkers to enhance responses to novel therapies. Herein, we provide an overview of the current HCC genomic landscape, previously identified gene signatures that are used routinely to predict prognosis, and an immune-specific class of HCC. Since biomarker-driven treatment is still an unmet need in HCC management, translation of these discoveries into clinical practice will lead to personalized therapies and improve patient care, especially in the era of targeted and immunotherapies.

Predictive Value of Antiviral Effects in the Development of Hepatocellular Carcinoma in the General Korean Population with Chronic Hepatitis B

BACKGROUND/AIMS: The benefit of oral antiviral therapy in preventing hepatocellular carcinoma (HCC) in the general population is not well understood. We used a novel prediction method to estimate the risk of HCC in the Korean population based on various treatment guidelines. METHODS: The 5-year risk of HCC following antiviral therapy was calculated using an HCC risk prediction model. A virtual cohort that represented Koreans (>40 years old) with chronic hepatitis B virus (HBV) infection was established using the fifth National Health and Nutrition Examination Survey. The antiviral indications tested were the Korean National Health Insurance (NHI) and European Association for the Study of the Liver (EASL) guidelines as well as a new extended indication (serum HBV DNA >2,000 IU/mL regardless of serum aminotransferase level). RESULTS: A total of 993,872 subjects were infected with HBV in the general Korean population. Over a 5-year period, 2,725 HCC cases were predicted per 100,000 persons (0.55%/yr). When the cohort was treated based on the Korean NHI, the EASL, and the newly extended indications, HCC risks decreased to 2,531 (−7.1%), 2,089 (−23.3%), and 1,122 (−58.8%) cases per 100,000 persons, respectively (p<0.0001). CONCLUSIONS: Simulated risk prediction suggests that extending of oral antiviral indication may reduce the HCC risk in the general population.

The mutational landscape of hepatocellular carcinoma

The development of hepatocellular carcinoma (HCC) is a complex process, and HCC arises from the accumulation of multiple genetic alterations leading to changes in the genomic landscape. Current advances in genomic technologies have revolutionized the search for genetic alterations in cancer genomes. Recent studies in which all coding exons in HCC were sequenced have shed new light on the genomic landscape of this malignant disease. Catalogues of these somatic mutations and systematic analysis of catalogued mutations will lead us to uncover candidate HCC driver genes, although further functional validation is needed to determine whether these genes play a causal role in the development of HCC. This review provides an overview of previously known oncogenes and new oncogene candidates in HCC that were uncovered from recent exome or whole-genome sequencing studies. This knowledge provides direction for future personalized treatment approaches for patients with HCC.

Genomic Profiling of Liver Cancer

Development of liver cancers is driven largely by genomic alterations that deregulate signaling pathways, influencing growth and survival of cancer cells. Because of the hundreds or thousands of genomic/epigenomic alterations that have accumulated in the cancer genome, it is very challenging to find and test candidate genes driving tumor development and progression. Systematic studies of the liver cancer genome have become available in recent years. These studies have uncovered new potential driver genes, including those not previously known to be involved in the development of liver cancer. Novel approaches combining multiple datasets from patient tissues have created an unparalleled opportunity to uncover potential new therapeutic targets and prognostic/predictive biomarkers for personalized therapy that can improve clinical outcomes of the patients with liver cancer.

Genes Associated with Recurrence of Hepatocellular Carcinoma: Integrated Analysis by Gene Expression and Methylation Profiling

Gene expression is suppressed by DNA methylation. The goal of this study was to identify genes whose CpG site methylation and mRNA expression are associated with recurrence after surgical resection for hepatocellular carcinoma (HCC). Sixty-two HCCs were examined by both whole genome DNA methylation and transcriptome analysis. The Cox model was used to select genes associated with recurrence. A validation was performed in an independent cohort of 66 HCC patients. Among fifty-nine common genes, increased CpG site methylation and decreased mRNA expression were associated with recurrence for 12 genes (Group A), whereas decreased CpG site methylation and increased mRNA expression were associated with recurrence for 25 genes (Group B). The remaining 22 genes were defined as Group C. Complement factor H (CFH) and myosin VIIA and Rab interacting protein (MYRIP) in Group A; proline/serine-rich coiled-coil 1 (PSRC1), meiotic recombination 11 homolog A (MRE11A), and myosin IE (MYO1E) in Group B; and autophagy-related protein LC3 A (MAP1LC3A), and NADH dehydrogenase 1 alpha subcomplex assembly factor 1 (NDUFAF1) in Group C were validated. In conclusion, potential tumor suppressor (CFH, MYRIP) and oncogenes (PSRC1, MRE11A, MYO1E) in HCC are reported. The regulation of individual genes by methylation in hepatocarcinogenesis needs to be validated.

Systems Biology Approaches to Decoding the Genome of Liver Cancer / Journal of the Korean Cancer Association, 대한암학회지

Molecular classification of cancers has been significantly improved patient outcomes through the implementation of treatment protocols tailored to the abnormalities present in each patient's cancer cells. Breast cancer represents the poster child with marked improvements in outcome occurring due to the implementation of targeted therapies for estrogen receptor or human epidermal growth factor receptor-2 positive breast cancers. Important subtypes with characteristic molecular features as potential therapeutic targets are likely to exist for all tumor lineages including hepatocellular carcinoma (HCC) but have yet to be discovered and validated as targets. Because each tumor accumulates hundreds or thousands of genomic and epigenetic alterations of critical genes, it is challenging to identify and validate candidate tumor aberrations as therapeutic targets or biomarkers that predict prognosis or response to therapy. Therefore, there is an urgent need to devise new experimental and analytical strategies to overcome this problem. Systems biology approaches integrating multiple data sets and technologies analyzing patient tissues holds great promise for the identification of novel therapeutic targets and linked predictive biomarkers allowing implementation of personalized medicine for HCC patients.