Abstract
Cancer is known to occur due to the genetic alternations of proto-oncogenes or tumor suppressor genes to alter a series of downstream signal transduction pathway in the molecular level or loss function in inhibiting the tumor occurrence. Therefore, inspecting the interactive behaviors of proteins in cancer cells and comparing them with those in normal cells will help us understand more about how a normal cell transforms to a cancer cell. In this study, we develop a nonlinear stochastic model to interpret the dynamic interactions among proteins and protein complexes in cancer cells based on the expression profiles of the cancer cell lines (HeLa) to depict a protein-protein interaction network of cancer cells. Furthermore, we provide a systematic method for construction and comparison of protein-protein interactions between normal and cancer cells. By choosing the target proteins of the protein-protein interaction network known to play important roles in proto-oncogenes and tumor suppressor genes such as Fos protein, Rb1 protein, Tp53 protein, etc. via our method, differential interactions between normal and cancer cells could be shown. These differences will provide a clue to the formations of tumors, and then we find some literature evidences to validate these results. Finally, protein-protein interaction networks of the MAPK signal transduction pathways between normal and cancer cells are also depicted via the proposed method. The proposed method is useful for enhancement and comparison of protein-protein interactions between normal and cancer cells, and may be helpful in the drug design in the future.