MICROARRAYS CAN DETERMINE DISEASE SPECIFIC GENES IN VIRAL HEPATITIS

David N Moskovitz¹, Limin Chen², Tim Hughes², Jenny Heathcote¹, Katryn Furuya³, Aled Edwards²

University Health Network, University of Toronto¹, Banting and Best Department of Medical Research², Hospital for Sick Children³, Toronto, Canada

INTRODUCTION: Disease-specific transcription changes can only be recognized in the context of a large database of transcription profiles from a variety of liver diseases.We are collecting needle biopsy samples from a range of liver diseases, including hepatitis C(HCV), hepatitis B(HBV), and hepatocellular carcinoma (HCC). Our aim is to use DNA microarray technology to understand the basis of liver disease.
METHOD: RNA was extracted from liver biopsy samples using the Trizol method. Universal human reference RNA served as controls. RNA was prepared from each of the samples and compared with control RNA. Each sample was tested on two separate arrays and each gene spotted twice on each array. Microarray analysis was done on needle biopsy samples, which yielded mRNA in quantities ranging from 10-20 micrograms. Transcription profiles for 19,000 genes were generated and key results confirmed by RT-PCR.
RESULTS: The transcription profiles obtained from needle biopsy samples were of sufficient quality and reproducibility to differentiate HCV, HBV and HCC using clustering algorithms. Our initial dataset comprised 61 samples: 11 HCV, 10 HBV, 12 normal, 6 HCC, and 12 miscellaneous liver diseases. We were able to isolate disease-specific genes (fewer than 50 for HCV, 100 HBV, and 200 HCC), and genes that are commonly affected by the various viral diseases. The cluster of gene changes associated with chronic HCV infection is distinct from that associated with either chronic HBV infection or HCC. The finding that transcription profiles of HCV livers are distinct from that of HBV, and that there may be a discrete number of profiles in individual patients with chronic HCV, argue that the gene clusters are reasonable candidates for pathogenic changes in the response to HCV. Correlating with the clinical data, we found that the average grade of fibrosis between 2 sub-clusters of patients with HCV were different.
CONCLUSIONS: We have established a highly reproducible procedure to prepare RNA. We are able to isolate viral specific and disease specific genes using microarray techniques. Liver microarray results can be used to diagnose diseased liver.