The research to establish the recurrence predicting system for hepatocellular carcinoma patients by use of genome-wide microarray database and to identify therapeutic molecular targets

点击翻译按钮获取中文摘要

Results 1We observed a high frequency of LOH on chromosome 16, which correlated with vascular invasiveness of tumors. We performed deletion mapping of chromosome 16 and then identified SIAH1 and found a correlation between its suppressed expression and progression. It has been shown that SIAH1 functions in the phosphorylation-independent degradation of β-catenin and induces apoptosis and growth arrest. To examine if the effects of SIAH1 over-expression depend on the altered β-catenin signaling pathway, we transferred SIAH1 gene into hepatoma cells. SIAH1 significantly induced growth arrest and apoptosis, despite of accumulation of aberrant β-catenin. SIAH1 interacts with another target protein but β-catenin. Immunoblotting study demonstrated that SIAH1 also reduces the amount of PEG10 protein, which is known to be frequently over-expressed in HCC and to promote cell proliferation. SIAH1 induces apoptosis and growth arrest in hepatoma cells through different mechanisms.Results 2Through a genome-wide cDNA microarray of hepatocellular carcinomas(HCCs), we identified a number a number of genes associated with tumor progression. Thus, to analyze expression profiles more precisely and establish a predictive system of intrahepatic recurrence after surgery, we performed second screening of 47 HCCs by TaqMan PCR consisting of 120 genes. Then we divided 47 HCCs into two groups. 25 HCCs are for training and 22 HCCs are blinded sets for validation. We identified 27 genes that associated with intrahepatic recurrence within 1 year after curative resection. A predictive score, based on expression profiles of 15 of the genes, correctly predicted the recurrent status in 16 of 22 HCCs in the blinded sets. A positive predictive value was 75% and negative predictive value was 71.4%. Accumulation of such data will make it possible to define the nature of individual tumors, to provide clues for identifying new therapeutic targets, and ultimately to optimize treatment of each patient.