Objective: To investigate whether gene expression profiles can be used to determine risk genes and predict HBV-related cirrhosis progression to liver carcinoma using Significance Analysis of Microarray (SAM) and Prediction Analysis of Microarray (PAM) methods.
Methods: The Affymetrix GeneChip was used to establish the gene expression profiles of liver tissues from 15 patients with chronic hepatitis B and cirrhosis or hepatocellular carcinoma (HCC). Differentially expressed genes (fold-change more than 2; P value less than 0.01) were selected by GeneSpring GX software. Risk genes related to cirrhosis and liver carcinoma were generated by SAM and PAM methods. Real-time PCR was used to verify the expression of risk genes in the liver tissues.
Results: Samples were clustered into the cirrhosis subgroup (n =15) or the HCC subgroup (n =15). A total of 497 differentially expressed genes were identified, SAM identified 162 significant genes, including 18 up-regulated genes and 144 down-regulated genes (fold-change:-1.46 to 1.28). PAM identified 22 genes with a "poor risk signature" (defined with a threshold of 5.5), which were associated with classifying cirrhosis and liver carcinoma; of these risk genes, 4 were down-regulated and 18 were up-regulated in the HCC group compared to the cirrhosis group (fold-change: 2.038 to 7.897, P value less than 0.01). The correction of classification was more than 80% . FOXP1, SPINK1 and KCNJ16 were verified by real-time PCR as differently expressed in the two subgroups (P value =0.011, 0.002 and 0.004, respectively).
Conclusion: The altered gene profiles of carcinogenesis in HBV-related cirrhosis involves hundreds of genes. The combination of three "poor risk genes" may represent potential targets for diagnosis and prediction of liver carcinoma progression.