It remains unclear which cellular properties underlie a tumor's dependence on a single oncogenic signaling pathway. Tran and colleagues sought to elucidate the general underlying mechanisms of oncogene addiction with the ultimate goal of developing a strategy to quickly determine whether oncogene-targeted treatment will be effective. First, using a mouse model of Kras-addicted lung cancer, they combined immunohistochemistry of several prosurvival and prodeath effector molecules at multiple time points before and after Kras inactivation with the proliferative and apoptotic indices to generate an ordinary differential equation model of aggregate survival and death signals over time. This model fit serial imaging data and showed that the response of oncogene-addicted tumors could be explained almost entirely by a sharp attenuation of the survival signal and a more gradual decline in the death signal. The authors also used this model to successfully predict the effects of particular prosurvival (Stat, Akt) and prodeath...
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1 November 2011
Research Watch|
November 16 2011
Mathematical Modeling Can Identify Oncogene-Addicted Tumors Available to Purchase
Online ISSN: 2159-8290
Print ISSN: 2159-8274
©2011 American Association for Cancer Research.
2011
Cancer Discov (2011) 1 (6): 463.
Citation
Mathematical Modeling Can Identify Oncogene-Addicted Tumors. Cancer Discov 1 November 2011; 1 (6): 463. https://doi.org/10.1158/2159-8290.CD-RW102011OL-06
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