In Vivo Imaging-Based Mathematical Modeling Techniques That Enhance the Understanding of Oncogene Addiction in relation to Tumor Growth

Table 1

Model parameters and values governing the response to oncogene inactivation.

Parameter	Estimated value (day^−1)	Description
𝐾𝑁_prolif	0.1	Transition coefficient from the “MYC off” state to proliferating
𝐾diff	0.02	Transition coefficient between “MYC off” state and differentiation state
𝐾𝑁_apop	2	Transition coefficient between “MYC off” and apoptosis state
𝐾senesc	0.001	Transition coefficient between “MYC off” state and Oncogene inactivation induced senescence state
𝐾relapse	0/3 × 10^−8	Transition coefficient between “MYC off” state and escaped state (immunocompetent/immunodeficient)
𝐾wake	0.1	Transition coefficient between differentiated state and “MYC on” state
𝐾𝐸_prolif	0.5	Transition coefficient from the escaped state to proliferating
𝐾𝑀_apop	0.05	Transition coefficient between “MYC on” and apoptosis state
𝐾𝑀_prolif	0.5	Transition coefficient from the “MYC on” state to proliferating
𝐾𝐸_apop	0.01	Transition coefficient between escaped state and apoptosis state
𝐾𝐷_apop	0.05/0.002/0.01	Transition coefficient between differentiated state and apoptosis state (tumor dependent: lymphoma, osteosarcoma, and hepatocellular carcinoma)
𝐾Inactivation	0/2	Transition from “MYC on” to “MYC off” (depending on if MYC is on/off)
𝐾Activation	2/0	Transition from “MYC off” to “MYC on” (depending on if MYC is on/off)