Molecular signatures for liver cancer diagnosis and treatment stratification

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We are using a global gene expression profiling approach based on state-of-the-art microarray technology to profile clinical specimens that are associated with different stages of liver diseases. For example, by comparing liver samples from chronic liver disease patients with varying degrees of risk for developing hepatocellular carcinoma, we have identified a unique signature that may be useful in diagnosing patients with early onset of liver cancer. Several serum proteins have been identified as potential diagnostic markers for hepatocellular carcinoma that are present at an early stage or in those negative for alpha-fetoprotein. We have also developed a unique molecular signature based on the mRNA gene expression of metastatic primary hepatocellular carcinoma specimens to predict prognosis and metastasis of hepatocellular carcinoma patients. Since hepatocellular carcinoma is usually present in inflamed liver, due to fibrosis, cirrhosis and/or chronic hepatitis, we also developed a unique molecular prognostic signature based on mRNA gene expression of the liver microenvironment of hepatocellular carcinoma patients. We found that a predominant humoral cytokine profile occurs in the metastatic liver microenvironment and that a shift toward anti-inflammatory/immune-suppressive responses may promote hepatocellular carcinoma metastases. These studies therefore suggest an important role of the local tissue microenvironment in hepatocellular carcinoma metastasis. Interestingly, the tumor signature is principally different from that of liver microenvironment. In addition, we have used molecular profiling to identify five genes that may serve as biomarkers for early onset of hepatocellular carcinoma, especially for those that are negative for alpha-fetoprotein. We have also explored the role of small non-coding RNAs, termed microRNAs, in hepatocellular carcinoma metastasis and survival. We found that certain microRNA expression changes are associated with metastasis and could significantly predict patient survival and relapse even in early stage disease. These microRNAs may provide a simple profiling method to assist in identifying HCC patients who are likely to develop metastases. In addition, functional analysis of these microRNAs may enhance our biological understanding of hepatocellular carcinoma metastasis. Our findings have been extremely fruitful and offer useful tools for patient management and also challenge the current paradigm of tumor evolution. Clearly, gene expression profiling has expanded our knowledge of the global changes that occur in liver cancer, and has provided numerous insights into the molecular mechanisms of this disease. In addition, these studies will undoubtedly contribute to the establishment of novel markers with potential diagnostic and prognostic value, as well as potential therapeutic targets for direct clinical intervention.