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Previous papers reported the effectiveness in classification of cancers with their gene expression portraits [1, 2, 3]. Golub et al. [3] selected 50 genes of high predictive value to differentiate 2 types of leukemia by ‘weighted voting algorithm’. However it remains to be known whether we can apply this type of specific algorithms to classify different types of cancer. We, therefore, attempted to classify liver tissues by expression profiles among non-cancer, well-differentiated hepatocellular carcinomas (WDH) and moderately-differentiated hepatocellular carcinomas (MDH) by applying clustering method and ‘weighted voting algorithm’.

Classification of hepatocellular carcinoma with gene expression profiling analysis