The notion that application of global approaches to the analysis of complex biological phenomena including human diseases may be useful has gained considerable strength in the postgenome area. For example, several independent studies have illustrated that previously unrecognized distinct subtypes of cancers could be identified by examining the genome-wide transcriptional profiles of clinical or experimental tumor samples. In fact, expression profiles obtained from microarray analysis of both tumor cell lines and primary tumors have been used to classify several human cancers including melanoma, breast cancer, leukemias and lymphomas. Similarly, global analysis of chromosomal alterations in neoplastic diseases by comparative genomic hybridization (CGH) has provided positional identifications of gains and losses of DNA sequences in the entire genome. In a recent study from our laboratory using CGH analysis of 19 HCC cell lines, a distinct pattern of genomic imbalance was defined that, in addition to revealing novel recurrent regions of DNA gains and losses, also confirmed genomic alterations previously identified by CGH in primary HCC tumors. These results suggest that cell lines derived from human HCC essentially retain the genomic alterations of the primary tumors. We are currently using the cDNA microarray technique to define global expression profiles in liver tumors from both human and mouse. Our long-term goal is to use the expression profiles to construct a molecular classification of human and mouse liver tumors. In our initial approach we have used the HCC cell lines, previously characterized by CGH, to conduct a systematic characterization of global gene expression by cDNA microarray. Two questions were addressed: (1) are HCC cell lines useful in defining expression modules that can be utilized to define interactive pathways critical in development of liver tumors; and (2) is the structural genomic alterations retained in the HCC cell lines reflected in the expression patterns of the transcriptome. Current results have revealed two distinct subtypes of hepatocellular carcinoma (HCC) that are distinguished from each other by the differential expression of hundreds of different genes. Remarkably, expression of a-fetoprotein was highly correlated with the molecular subtypes of HCC. Sets of co-expressed known and unknown genes that are specific for the subtypes of HCC were also identified. Comparison of gene expression patterns for each chromosome revealed region-wide expression bias within HCC, reflecting chromosomal aberrations in cell lines. These results not only identified unrecognized subtypes of HCC, but also provided potential molecular markers for each subtype that can be useful for diagnostic and/or therapeutic purposes.
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