[Frontiers in Bioscience E4, 620-630, January 1, 2012]

Peripheral blood mRNA expression patterns to differentiate hepatocellular carcinoma from other hepatic diseases

PJ Zhang 1, W Run 1, Liang P2, CB Wang3, XX Deng1, B Wang 1, B Chen 1, Jiao J1, HY Liu 1, ZN Dong 1, XJ Zhang 1, YP Tian1

1Department of Clinical Biochemistry, Chinese PLA General Hospital, Beijing, China, 2Department of Interventional Ultrasound, Chinese PLA General Hospital, Beijing, China, 3Department of Clinical Laboratory Medicine, Chinese PLA General Hospital, Beijing, China

TABLE OF CONTENTS

1. Abstract
2. Introduction
3. Material and methods
3.1. Patients
3.2. Blood collection and RNA isolation
3.3. Genes and GeXP primer design
3.4. GeXP multiplex RT-PCR
3.5. GeXP multiplex data analysis
3.6. Diagnosis model for hepatocellular carcinoma development
4. Results
4.1. RT-PCR of single gene by chimeric and universal primers
4.2. Multiplex primer RT-PCR and optimization
4.3. Gene expressions between five different groups
4.4. Diagnosis model to differentiate the five groups
4.5. Workflow for the diagnosis model by GeXP
5. Discussion
6. Acknowledgments
7. References

1. ABSTRACT

Peripheral blood genes expressions profiling (GeXP) have been convinced to be more specific for the diagnosis of cancer and other diseases, and the GeXP system provides an ideal method to analyze multiple genes expression in one normalized and equable system. We aim to differentiate hepatocellular carcinoma from other hepatic diseases based on peripheral blood and the GeXP system. Fifteen selected hepatic diseases related genes with two house-keeping genes for normalization were detected by the GeXP system. The diagnosis model was based on K nearest neighbor classifier and cross validation, and software based on MATLAB software was built for differential diagnosis of hepatic diseases. Eight hepatic related genes were demonstrated to show an obvious statistic difference in expressions while the K nearest neighbors classifier showed that the accuracy for normal controls, hepatitis B, liver cirrhosis, hepatocellular carcinoma and the Other group was separately 80.57%, 78.17%, 84.48%, 73.24% and 85.85%. The set of validation has been carried out to assess the accuracy of Model Two and the accuracy was even higher than the set of building for the model, except for the hepatitis B (HBV) group. A sensitive and specific GeXP system of eight genes has been developed for the accurate differential diagnosis of hepatic disease.