Norikazu Takemoto

Differential gene expression in distinct virologic types of hepatocellular carcinoma: association with liver cirrhosis

Using oligonucleotide microarray data of 45 hepatocellular carcinoma (HCC) samples, we evaluated gene expression in hepatitis B virus-positive and hepatitis C virus-positive HCCs (HBV- and HCV-HCCs) for an association with liver cirrhosis (LC). In all, 89 genes were expressed differentially between HBV-HCCs associated with LC and those not associated with LC. Among them, tumors from LC patients showed significantly lower expression levels of 72 genes and significantly higher levels of 17 genes than the levels found in tumors from non-LC patients. The former included genes responsible for signal transduction, transcription, metabolism, and cell growth. The latter included a tumor suppressor gene and a cell-growth-related gene. Only eight genes were expressed differentially between HCV-HCCs associated with and without LC. Our findings provide as a framework for clarifying the role of LC in HBV- and HCV-related hepatocarcinogenesis.

Tumor HLA-DR expression linked to early intrahepatic recurrence of hepatocellular carcinoma

The outcome of patients with hepatocellular carcinoma (HCC) remains poor because of the high frequency of intrahepatic recurrence (IHR), particularly early IHR within 1 year of hepatectomy. To search for genes involved in early IHR, we performed DNA microarray analysis in a training set of 33 HCCs and selected 46 genes linked to early IHR from approximately 6,000 genes by means of a supervised learning method. Gene selection was validated by a false discovery rate of 0.37%. The 46 genes included many immune response‐related genes, which were all downregulated in HCCs with early IHR. Four of these genes (HLA‐DRA, HLA‐DRB1, HLA‐DG and HLA‐DQA), encoding MHC class II antigens, were coordinately downregulated in HCCs with early IHR compared to levels in HCCs with nonrecurrence. A cluster analysis reproduced expression patterns of the 4 MHC class II genes in 27 blinded HCC samples. To localize the major site of production of HLA‐DR protein in the tumor, we used 50 frozen specimens from 50 HCCs. Immunofluorescence staining showed that HLA‐DR protein levels in tumor cells, but not in stromal cells, were associated with the transcription levels of HLA‐DRA determined by both DNA microarray analysis and real‐time quantitative reverse transcription‐PCR. Univariate analysis showed that tumor HLA‐DR protein expression, pTNM stage and venous invasion were associated with early IHR. Multivariate analysis showed that tumor HLA‐DR protein expression was one of the independent risk factors for early IHR, suggesting HLA‐DR protein potential as a biomarker and a molecular target for therapeutic intervention.

Gene expression profile linked to p53 status in hepatitis C virus‐related hepatocellular carcinoma

To clarify the role of p53 in 22 hepatitis C virus (HCV)‐infected hepatocellular carcinomas (HCCs), we compared the gene expression profiles of HCCs with wild‐type p53 (wt‐p53) (n=17) and those with mutant‐type p53 (mt‐p53) (n=5) by oligonucleotide microarray analysis. Among 83 p53‐related genes identified by a supervised learning method, 25 were underexpressed, and 58 were overexpressed in mt‐p53 HCCs compared with wt‐p53 HCCs. With a computer search, we identified consensus p53‐binding sequences in the 3‐kb region upstream of the translation initiation site in 59 of the 83 genes, suggesting that the in vivo p53‐associated transcription system is very complicated. These data will provide additional insights into p53‐related pathogenesis in HCV‐infected HCC.

Self-organizing-map-based molecular signature representing the development of hepatocellular carcinoma

Using high‐density oligonucleotide array, we comprehensively analyzed expression levels of 12 600 genes in 50 hepatocellular carcinoma (HCC) samples with positive hepatitis C virus (HCV) serology (well (G1), moderately (G2), and poorly (G3) differentiated tumors) and 11 non‐tumorous livers (L1 and L0) with and without HCV infection. We searched for discriminatory genes of transition (L0 vs. L1, L1 vs. G1, G1 vs. G2, G2 vs. G3) with a supervised learning method, and then arranged the samples by self‐organizing map (SOM) with the discriminatory gene sets. The SOM arranged the five clusters on a unique sigmoidal curve in the order L0, L1, G1, G2, and G3. The sample arrangement reproduced development‐related features of HCC such as p53 abnormality. Strikingly, G2 tumors without venous invasion were located closer to the G1 cluster, and most G2 tumors with venous invasion were located closer to the G3 cluster (P = 0.001 by Fishers exact test). Our present profiling data will serve as a framework to understand the relation between the development and dedifferentiation of HCC.