RESUMEN
The dependence on the overexpression of a single oncogene constitutes an exploitable weakness for molecular targeted therapy. These drugs can produce dramatic tumor regression by targeting the driving oncogene, but relapse often follows. Understanding the complex interactions of the tumor's multifaceted response to oncogene inactivation is key to tumor regression. It has become clear that a collection of cellular responses lead to regression and that immune-mediated steps are vital to preventing relapse. Our integrative mathematical model includes a variety of cellular response mechanisms of tumors to oncogene inactivation. It allows for correct predictions of the time course of events following oncogene inactivation and their impact on tumor burden. A number of aspects of our mathematical model have proven to be necessary for recapitulating our experimental results. These include a number of heterogeneous tumor cell states since cells following different cellular programs have vastly different fates. Stochastic transitions between these states are necessary to capture the effect of escape from oncogene addiction (i.e., resistance). Finally, delay differential equations were used to accurately model the tumor growth kinetics that we have observed. We use this to model oncogene addiction in MYC-induced lymphoma, osteosarcoma, and hepatocellular carcinoma.
Asunto(s)
Carcinoma Hepatocelular/inmunología , Neoplasias Hepáticas/inmunología , Linfoma/inmunología , Neoplasias/patología , Oncogenes/genética , Osteosarcoma/inmunología , Apoptosis , Linfocitos T CD4-Positivos/citología , Carcinoma Hepatocelular/metabolismo , Senescencia Celular , Biología Computacional/métodos , Simulación por Computador , Humanos , Neoplasias Hepáticas/metabolismo , Linfoma/metabolismo , Modelos Biológicos , Neoplasias/metabolismo , Osteosarcoma/metabolismo , Proteínas Proto-Oncogénicas c-myc/metabolismo , Recurrencia , Procesos EstocásticosRESUMEN
Understanding the complex dynamics between the tumor cells and the host immune system will be key to improved therapeutic strategies against cancer. We propose an ODE-based mathematical model of both the tumor and immune system and how they respond to inactivation of the driving oncogene. Our model supports experimental results showing that cellular senescence of tumor cells is dependent on CD4+ T helper cells, leading to relapse of tumors in immunocompromised hosts.