Several diseases manifest metabolic anomalies in their progressions. Abnormal production or degradation of metabolites could damage the cell and eventually lead to disease pathogenesis. If we focus on genes associated with metabolic regulation, rather than metabolic changes, we can identify the cause of metabolic diseases and also prognostic genetic markers. Especially, a disease showing metabolic anomalies, colorectal cancer has been intensively investigated in this study. Abnormally produced bile acids could lead to the pathogenesis of colorectal cancer, but gene-level clues of bile acid anomalies to colorectal cancer have been incomplete. We suggested proteins of a new role to regulate metabolism, instead of metabolic sensors and metabolic enzymes, as bridge proteins, which link between metabolic sensors and metabolic enzymes. Based on our novel networkbased approach, such as a bridgeness metric, we could identify bridge proteins from a reference network, i.e., bridge network, that we generated and their significant prognostic ability in colorectal cancers. Unlike previous approach to identify prognostic genes, such as hypothesis-driven experimental approach and computational association studies, we could identify prognostic genes with their mechanistic relevance and prognostic abilities simultaneously. Therefore, we identified prognostic genes from bridge proteins that are related to bile acid anomalies and give novel insights to understand and cope with metabolic diseases.