Systems biology approaches to decoding the genome of liver cancer

Systems Challenges of Hepatic Carcinomas: A Review

Hepatocellular Carcinoma (HCC) is ubiquitous in its prevalence in most of the developing countries. In the era of systems biology, multi-omics has evinced an extensive approach to define the underlying mechanism of disease progression. HCC is a multifactorial disease and the investigation of progression of liver cirrhosis becomes much extensive with cultivating omics approaches. We have performed a comprehensive review about such challenges in multi-omics approaches that are concerned to identify the immunological, genetics and epidemiological factors associated with HCC.

The impact of network medicine in gastroenterology and hepatology

In the footsteps of groundbreaking achievements made by biomedical research, another scientific revolution is unfolding. Systems biology draws from the chaos and complexity theory and applies computational models to predict emerging behavior of the interactions between genes, gene products, and environmental factors. Adaptation of systems biology to translational and clinical sciences has been termed network medicine, and is likely to change the way we think about preventing, predicting, diagnosing, and treating complex human diseases. Network medicine finds gene-disease associations by analyzing the unparalleled digital information discovered and created by high-throughput technologies (dubbed as "omics" science) and links genetic variance to clinical disease phenotypes through intermediate organizational levels of life such as the epigenome, transcriptome, proteome, and metabolome. Supported by large reference databases, unprecedented data storage capacity, and innovative computational analysis, network medicine is poised to find links between conditions that were thought to be distinct, uncover shared disease mechanisms and key drivers of the pathogenesis, predict individual disease outcomes and trajectories, identify novel therapeutic applications, and help avoid off-target and undesirable drug effects. Recent advances indicate that these perspectives are increasingly within our reach for understanding and managing complex diseases of the digestive system.

Epigenetic regulation of hepatocellular carcinoma in non-alcoholic fatty liver disease

Emerging evidence that epigenetics converts alterations in nutrient and metabolism into heritable pattern of gene expression has profound implications in understanding human physiology and diseases. Non-alcoholic fatty liver disease (NAFLD) is the hepatic manifestation of metabolic syndrome including obesity and diabetes which elevate the risk of hepatocellular carcinoma (HCC) especially in male. This review focuses on the molecular connections between metabolic dysfunction and aberrant epigenetic alterations in the development of HCC in NAFLD. The metabolites derived from excessive insulin, glucose and lipid may perturb epigenetic gene regulation through DNA methylation, histone modifications, and RNA interference, leading to activation of pro-inflammatory signaling and deregulation of metabolic pathways. The interplay and crosstalk of chromatin-modifying enzymes, microRNAs, signaling pathways and the downstream transcription factors result in epigenomic reprogramming that drives hepatocellular transformation. The interactions between sex hormone pathways and the epigenetic machineries that influence chromatin states in NAFLD provide potential molecular mechanisms of gender disparity in HCC. A deeper understanding of these connections and comprehensive molecular catalog of hepatocarcinogenesis may shed light in the identification of druggable epigenetic targets for the prevention and treatment of HCC in obese or diabetic patients.

Hepatocellular carcinoma: a systems biology perspective

Hepatocellular carcinomas (HCCs) have different etiology and heterogenic genomic alterations lead to high complexity. The molecular features of HCC have largely been studied by gene expression and proteome profiling focusing on the correlations between the expression of specific markers and clinical data. Integration of the increasing amounts of data in databases has facilitated the link of genomic and proteomic profiles of HCC to disease state and clinical outcome. Despite the current knowledge, specific molecular markers remain to be identified and new strategies are required to establish novel-targeted therapies. In the last years, mathematical models reconstructing gene and protein networks based on experimental data of HCC have been developed providing powerful tools to predict candidate interactions and potential targets for therapy. Furthermore, the combination of dynamic and logical mathematical models with quantitative data allows detailed mechanistic insights into system properties. To address effects at the organ level, mathematical models reconstructing the three-dimensional organization of liver lobules were developed. In the future, integration of different modeling approaches capturing the effects at the cellular up to the organ level is required to address the complex properties of HCC and to enable the discovery of new targets for HCC prevention or treatment.