It has been a consensus in cancer research that cancer is a disease caused primarily by genomic alterations, especially somatic mutations. However, the mechanism of mutation-induced oncogenesis is not fully understood. Here, we used the mitochondrial apoptotic pathway as a case study and performed a systematic analysis of integrating pathway dynamics with protein interaction kinetics to quantitatively investigate the causal molecular mechanism of mutation-induced oncogenesis. A mathematical model of the regulatory network was constructed to establish the functional role of dynamic bifurcation in the apoptotic process. The oncogenic mutation enrichment of each of the protein functional domains involved was found strongly correlated with the parameter sensitivity of the bifurcation point. We further dissected the causal mechanism underlying this correlation by evaluating the mutational influence on protein interaction kinetics using molecular dynamics simulation. We analyzed 29 matched mutant-wild-type and 16 matched SNP-wild-type protein systems. We found that the binding kinetics changes reflected by the changes of free energy changes induced by protein interaction mutations, which induce variations in the sensitive parameters of the bifurcation point, were a major cause of apoptosis pathway dysfunction, and mutations involved in sensitive interaction domains show high oncogenic potential. Our analysis provided a molecular basis for connecting protein mutations, protein interaction kinetics, network dynamics properties, and physiological function of a regulatory network. These insights provide a framework for coupling mutation genotype to tumorigenesis phenotype and help elucidate the logic of cancer initiation.mutation-induced oncogenesis | dynamic bifurcation | parameter sensitivity analysis | mutation enrichment | protein interaction kinetics H igh-throughput whole-genome sequencing (1) and massively parallel technologies (2) have enabled cancer researchers to understand that cancer is a disease caused primarily by genomic alterations, especially somatic cell mutations (3, 4). This stimulated extensive research endeavors to identify the landscape of cancer-related mutations. In the last decade, studies of different tumor types using cancer genomic and pathology analysis indicate that oncogenic mutations are concentrated primarily in a few core regulatory pathways that govern cell phenotypic behaviors (5-8). These results led to the idea that "genetic aberrations alter normal cellular regulation and then drive tumor development" (9, 10). Therefore, mutation-induced oncogenesis should be explored from a network and system perspective.A systematic interpretation of oncogenesis can be achieved in part by analyzing interactions among mutated genes and performing functional annotation of cancer-related proteins in functional pathways. A more quantitative approach is network modeling using ordinary differential equations (ODEs) and mathematical simulations. This well-established method has been successfully used to ...