Mathematical Modeling Applied to Cancer Progression

ALEJANDRA C VENTURA; JACQUES-A. SEPULCHRE; MEI WU; ZHIFEN WU; JORGE R TREDICCE; SOFIA D MERAJVER

Columbus, USA

Workshop; 2007 Workshop for Young Researchers in Mathematical Biology; 2007

Mathematical Biosciences Institute

Rho family members are small GTPases that are known to regulate malignant transformation and motility of cancer cells. RhoC GTPase was found to be preferentially over-expressed in inflammatory breast cancer, which is a highly aggressive form of locally advanced breast cancer that carries a guarded prognosis due to its propensity to disseminate via the dermal lymphatics and metastasize to distant organs. It is well known that RhoC, like other GTP-binding proteins, undergoes a cycle between an active (GTP-bound) state and an inactive (GDP-bound) state, and that its switch-on/off activity is tightly regulated by activators (guanine nucleotide exchange factors, GEFs) and inactivators (GTPase-activating proteins, GAPs). We have developed a dual mathematical-experimental approach to understand this cycle and its deregulation in cancer cells in comparison with normal tissues. Using a deterministic description based on ordinary differential equations we are correlating the dynamic responses of RhoC and its regulators proteins under stimulation, with experimental data. A major impact of this work is to quantitatively predict the effects of drugs targeted against RhoC in cancer.  The most damaging change during cancer progression is the growth of metastases. The protein RhoC GTPase was found to be crucial in that process in different cancers, particularly, in a highly aggressive form of breast cancer. RhoC is a molecular switch cycling between inactive (GDP-bound) and active (GTP-bound) states, tightly regulated by several regulatory proteins. We have developed a dual mathematical-experimental approach to understand this cycle and its deregulation in breast cancer cells in comparison with normal ones. A major impact of this work is to quantitatively predict the effects of drugs targeted against RhoC in cancer.