AIM: To investigate the relationship of changes in expression of marker genes in functional categories or molecular networks comprising one functional category or multiple categories in progression of hepatic fibrosis in hepatitis C (HCV) patients. METHODS: Marker genes were initially identified using DNA microarray data from a rat liver fibrosis model. The expression level of each fibrosis associated marker gene was analyzed using reverse transcription-polymerase chain reaction (RT-PCR) in clinical biopsy specimens from HCV-positive patients (n = 61). Analysis of changes in expression patterns and interactions of marker genes in functional categories was used to assess the biological mechanism of fibrosis. RESULTS: The profile data showed several biological changes associated with progression of hepatic fibrosis. Clustered genes in functional categories showed sequential changes in expression. Several sets of clustered genes, including those related to the extracellular matrix (ECM), inflammation, lipid metabolism, steroid metabolism, and some transcription factors important for hepatic biology showed expression changes in the immediate early phase (F1/F2) of fibrosis. Genes associated with aromatic amino acid (AA) metabolism, sulfur-containing AA metabolism and insulin/ Wnt signaling showed expression changes in the middle phase (F2/F3), and some genes related to glucose metabolism showed altered expression in the late phase of fibrosis (F3/F4). Therefore, molecular networks showing serial changes in gene expression are present in liver fibrosis progression in hepatitis C patients. CONCLUSION: Analysis of gene expression profiles from a perspective of functional categories or molecular networks provides an understanding of disease and suggests new diagnostic methods. Selected marker genes have potential utility for biological identification of advanced fibrosis. A: To investigate the relationship of changes in expression of marker genes in functional categories or molecular networks one one category or multiple categories in progression of hepatic fibrosis in hepatitis C (HCV) patients. Methods: Marker genes were initially identified using DNA microarray data from a rat liver fibrosis model. The expression level of each fibrosis associated marker gene was analyzed using reverse transcription-polymerase chain reaction (RT-PCR) in clinical biopsy specimens from HCV-positive patients (n = 61). Analysis of changes in expression patterns and interactions of marker genes in functional categories was used to assess the biological mechanism of fibrosis. RESULTS: The profile data showed several biological changes associated with progression of hepatic fibrosis. Clustered genes in functional categories showed sequential changes in expression. Several sets of clustered genes, including those related to the extracellular matrix (ECM), inflammation, lipid metabolism, and some transcription factors important for hepatic biology showed expression changes in the immediate early phase (F1 / F2) of fibrosis. Genes associated with aromatic amino acids (AA) metabolism, sulfur-containing AA metabolism and insulin / Wnt signaling showed expression changes in the middle phase (F2 / F3), and some genes related to glucose metabolism showed altered expression in the late phase of fibrosis (F3 / F4). Therefore, molecular networks showing serial changes in gene expression are present in liver fibrosis progression in hepatitis C patients. CONCLUSION: Analysis of gene expression profiles from a perspective of functional categories or molecular networks provides an understanding of disease and suggests new diagnostic methods. Selected marker genes have potential utility for biological identification of advanced fibrosis.