| Name |
Hye-Won Kang |
| Country |
USA |
| Email |
hwkang@umbc.edu |
| Co-Author(s) |
Melissa Crawford, Muller Fabbri, Gerard Nuovo, Michela Garofalo, S. Patrick Nana-Sinkam, Avner Friedman |
| Submit Time |
2013-12-05 21:45:18 |
Session |
Special Session 62: Mathematical models of cell migration, tumor growth and cancer dynamics
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| Contents |
| Lung cancer is the leading cause of cancer-related deaths. Lack of early detection and the limited options for targeted therapies are the main factors to contribute to these statistics. MicroRNAs represent a class of non-coding RNAs that regulate genes and may serve as both diagnostic and prognostic biomarkers in lung cancer. Based on the experimental data, two microRNAs, miR-9 and let-7, are dysregulated in non-small cell lung cancer (NSCLC) and this feature may be helpful to identify lung cancer. In this talk, I will suggest a key signaling pathway involving two microRNAs and introduce a mathematical model using a system of differential equations. Simulations of the model demonstrate that EGFR and Ras mutations in NSCLC result in miR-9 upregulation and let-7 suppression. By putting random perturbation on microRNAs using stochastic differential equations, I can conclude that the signaling pathway is somewhat robust against random input into miR-9 and more strongly robust against random input into let-7. |
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