Worldwide, hepatocellular carcinoma (HCC) is the fifth most common solid malignancy and the third leading cause of cancer mortality. Hepatitis B virus (HBV) infection is the most prominent etiologic factor for HCC. The total number of patients with chronic HBV (CHB) infection is in excess of 400 million, over 5% of the world's population. However, only 20% of these patients eventually develop HCC, which underscores the importance of developing a clinically applicable risk assessment model in the prevention and mortality control of HBV- related HCC. MicroRNAs (miRNAs) belong to a class of noncoding small RNA molecules that regulate the expression of over one-third of all human genes, including many oncogenes and tumor suppressor genes. MiRNAs have been significantly associated with the etiology and clinical outcome of many tumors including HBV-related HCC. Several recent studies have demonstrated that in human serum, miRNAs are highly stable and constitute the major faction of small nucleic acids. This makes serum a valuable resource for miRNA- based biomarker research, especially in prospective studies that have been followed-up for extended time periods but only collected serum samples at the time of study initiation. Although serum miRNA expression signatures have been extensively used as biomarkers of clinical outcomes of various malignancies, to date, no studies have been reported on serum miRNA profile as the predictor of HCC risk in CHB patients. In this proposed study, we will employ a prospective case-control approach to systematically identify baseline (before anti-HBV treatment and cancer diagnosis) serum miRNA expression signatures that are associated with the risk of HCC.
The specific aims are: 1. To identify miRNA expression signatures as predictors of HCC development in 510 CHB patients. This study will be conducted in a unique and highly homogenous Asian American population of patients with chronic HBV infection that are completely enrolled in the United States. The 510 patients are divided into two populations: a discovery population including 30 cases and 30 controls that will be analyzed using miRNA microarray, as well as an internal validation population including 150 cases and 300 controls that will be analyzed using quantitative real-time PCR. 2. To develop a multivariate risk assessment model to analyze the cumulative and interaction effects between miRNA expression profiles and other important risk factors that modulate CHB to HCC transformation. 3. To conduct exploratory bioinformatics analyses and construct an in silico network of genes potentially targeted by miRNAs. Our study is highly cost- effective in that it capitalizes upon an established biorepository of CHB and HCC patients. It is one of the first systematic evaluations of baseline serum miRNA expression profile as prospective predictor of HCC risk in CHB patients. The strict matching between cases and controls as well as the two-stage study design greatly increases the possibility of discovering the bona fide miRNAs. The bioinformatics analyses are likely to provide us with novel insights into the mechanism of miRNAs and target genes that are important in CHB to HCC transformation. Furthermore, this study will facilitate the further establishment of our population that includes a large number of cancer-free CHB patients. Many of these patients have multiple visits to our institute and are still under intensive treatment and follow-up, which will enable us to conduct longitudinal studies in the future to in-depth evaluate the effects of antiviral treatments and other factors on the risk of HCC risk CHB patients.
About 20% of the 400 million patients worldwide with chronic hepatitis B virus (HBV) infection will develop hepatocellular carcinoma (HCC), underscoring the importance of developing a clinically applicable risk assessment model in the prevention and mortality control of HBV-related HCC. Recent studies have demonstrated that in human serum, miRNAs are highly stable and constitute the major faction of small nucleic acids. This makes serum a valuable resource for miRNA-based biomarker research, especially in prospective studies that have been followed-up for extended time periods but only collected serum samples at the time of study initiation. In this study, we aim to use a prospective case-control approach and a two-stage study design to identify robust miRNA expression signatures in the baseline serum samples of HBV patients as predictors of HCC development. The findings will be incorporated into a multivariate risk assessment model that will allow for the selection of CHB patients with the highest risk of malignant transformation to receive more intensive and personalized preventive intervention.
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