The incidence of hepatocellular carcinoma (HCC) is rising in the USA because of the increased prevalence of cirrhosis from HCV infection. Surgical resection (SR) and liver transplantation (LT) still represent the only potentially curative treatments. Since 80% of HCC patients in the USA have cirrhosis, optimum care requires the analysis of cancer stage to predict recurrence, and the determination of liver reserve to predict suitability of SR vs. LT to prevent death from liver failure. LT is limited by the shortage of organs, with up to 30% of patients developing contraindications to the procedure while waiting for a donor. Living Donor Liver Transplant (LDLT) is one way to shorten the waiting time. Accurate tumor staging in patients with HCC is critical to provide a potentially curative treatment. Molecular markers for HCC metastasis and recurrence could provide additional information to that gained from traditional clinical and histopathological. features. We ? will explore the hypothesis that establishment of a molecular-based method for the classification of HCVHCC at diagnosis will permit the detection of distinct subgroups of HCC patients with different prognoses,- allowing greater accuracy in the selection of patients for treatment cure with transplantation. In this multicenter prospective project, nested within the A2ALL NIH-NIDDK Cohort Study, gene expression profiling and genome-wide LOH analysis will be used for the studies. We propose: 1- To study HCV-HCC initiation (comparing gene expression profiles and LOH patterns in HCV infected patients with and without HCC awaiting LT) and to identify a set of significant genes for classifying high-risk patients with a potential for developing HCC; 2-To analyze disease progression, establishing a molecular fingerprint for distinguishing HCV-HCC patients awaiting a donor with the greatest risk for developing HCC recurrence; 3-The molecular fingerprint established in aim 2 will be studied for it's accuracy to predict outcomes post-LT by performing survival analysis and comparing the risk of post-LT HCC recurrence stratified by LDLT and Deceased Donor Liver Transplant recipient groups. We propose that establishment of a molecular-based method for the classification of HCV-HCC at diagnosis II permit the detection of distinct subgroups of HCC patients with different prognoses, allowing greater accuracy in selection of patients for treatment cure with transplantation. ? ? ? ? ? ? ? ? ? ? ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project (R01)
Project #
1R01DK069859-01A2
Application #
7092812
Study Section
Epidemiology of Cancer Study Section (EPIC)
Program Officer
Doo, Edward
Project Start
2006-04-01
Project End
2011-03-31
Budget Start
2006-04-01
Budget End
2007-03-31
Support Year
1
Fiscal Year
2006
Total Cost
$567,628
Indirect Cost
Name
Virginia Commonwealth University
Department
Surgery
Type
Schools of Medicine
DUNS #
105300446
City
Richmond
State
VA
Country
United States
Zip Code
23298
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Archer, K J; Mas, V R (2009) Ordinal response prediction using bootstrap aggregation, with application to a high-throughput methylation data set. Stat Med 28:3597-610

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