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The immune system has highly sophisticated to defend the foreign invaders such as bacteria and viruses. In this system, Tumor necrosis factor-a(TNF-a) is one of the key molecules to help kill the cancer or tumors, however, at the certain time point, TNF-a switch to encourage them to the differentiation or proliferation for growing tumors. After TNF-a is discovered, it takes around 30 years and much information about TNF-a such as intracellular signaling process, gene expression following to cellular network and its phenomena are being restored through wet-bench activities and advanced high throughput technologies. But comprehensive mechanism of its dynamic cellular processes and their control such as switching mechanism are still poorly understood. Recent high-throughput dataset on TNF-a stimulation shows three dynamical patterns (groups) arising from 180 up-regulated genes in murine embryonic fibroblasts (MEF). These groups were delineated based on the shape of their temporal activation profiles. In group 1, the time of peak activation is early (~0.5h) and decays rapidly. In groups 2 and 3, the peak activation is delayed (~2h and ~12h, respectively) and the decay is very slow. These results were interpreted to arise due to the rate of instability of mRNA determined by the number of AU-rich element in the 3'untranslated region (UTR). Recently our group also developed simple rules using the law of the conservation to shed light on the various signaling dynamics. Using this approach, we found that the 3 temporal patterns of gene expressions can be reproduced using the law of conservation and mass-action equations. Next, in addition to the instability of mRNA, we show groups 1 and 2 genes are mainly activated by primary signaling with transcription factors AP-1 and NF-kB with different kinetics and group 3 genes are induced by secondary signaling such as autocrine stimulations of IL-1 and IL-6. Here, we compared our model simulation with dynamical experimental data and suggested the dynamical patterns of gene expression in complex networks can be represented by simple physical rules.
Yamada D., Hayashi K., Piras V., Tomita M., Tsuchiya M., Selvarajoo K. (2010) "Signaling Flux Redistribution concept can switch survival to apoptosis in cancer cells" q-bio conference, New Mexico, USA
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