摘要

Cancer research over the past decades has revealed a number of molecular, biochemical, and cellular events that reflect progressive transformation of normal human cells into their malignant derivatives. These findings help to better understand the complexity of human tumorigenesis. In our study, molecular information is organized to chart a comprehensive map of the signaling network for human cancer. It includes transcriptional and translational regulation and diverse feedback-control loops. It is demonstrated that applying this signaling network map allows predicting the effect of targeted therapy before it can be applied into practice to reduce clinical trial risks. Hence, the proposed map with prognosticating potential effect might become part of drug discovery programs for targeted therapy. Applied in individual patient care it helps to reduce the current reliance of cancer treatment on chemotherapies with low therapeutic indices. This study also demonstrates that continuing elucidation of tumorigenesis will not only need heterotypic organ culture systems in vitro and increasingly refined animal models in vivo, but also computationally calculable virtual cell models in silico.