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14h00 - 15h00 |
Rinaldo Schinazi, Department of Mathematics, University of Colorado
Stochastic models for carcinogenesis |
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15h00 - 15h30 | Pause café |
15h30 - 16h30 |
Benjamin Ribba, INRIA et UCBL - Ciblage Thérapeutique en Oncologie (EA3738)
Sylvie Mazoyer, UMR5201 |
16h30 - 17h00 | Discussion générale |
Rinaldo Schinazi, Department of Mathematics, University of Colorado
Stochastic models for carcinogenesis
We propose a simple stochastic model based on the two successive mutations hypothesis to compute cancer risks. Assume that only stem cells are susceptible to the first mutation and that there is a total of D stem cell divisions over the life time of the tissue with a first mutation probability mu_1 per division. Our model predicts that cancer risk will be low if m=mu_1D is low even in the case of very advantageous mutations. Moreover, if mu_1D is low the mutation probability of the second mutation is practically irrelevant to the cancer risk. These results are in contrast with existing models but in agreement with a conjecture of Cairns. In the case where m is large our model predicts that the cancer risk depends crucially on whether the first mutation is advantageous or not. A disadvantageous or neutral mutation makes the risk of cancer drop dramatically.
Benjamin Ribba, INRIA et UCBL - Ciblage Thérapeutique en Oncologie (EA3738)
A mathematical model of tumor growth and its use in optimizing the delivery of anti-angiogenesis drugs in combination with chemotherapy
Sylvie Mazoyer, UMR5201
Mutations in the BRCA1 and BRCA2 breast cancer susceptibility genes
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