The network pathophysiology of tumorigenesis: a systems biology approach I
Summary of the proposed research
Characteristics of malign tumor cells are the abilities to (i) disregard or misinterpret signals of the host that tell them to adjust their behavior to the requirements of the latter and (ii) survive conditions that results from their extraordinary behavior. The former ability can stem from excessive or inappropriate autocrine activation or up-regulation of membrane-bound receptor proteins (chemokine receptors, receptor tyrosine kinases), which promotes inadvertent cell proliferation and migration, resulting in tumor progression and metastasis. The latter include sustained activation of metabolic routes that reduce the cell’s dependence on oxygen, such as the Warburg effect. In this project we will combine expertise on oncogenic signaling networks (Smit, FEW) and differential network-based drug design (Westerhoff, FALW), physiology and regulation of metabolism (Teusink, 0.8FALW/0.2FEW) and bioanalytic chemistry (Irth, FEW).
The aim is to elucidate how receptor mediated signaling networks and metabolic processes are linked and linked differently in cancer, and how this may lead to a new, dual-pronged systems-biology based approach to target finding. We will make use of cancer model systems (Smit), integrating both global (genetic, proteomic) and mechanism-based approaches focusing on signaling and metabolic pathways. Analytical techniques will be developed and optimized to measure intracellular and extracellular metabolites, intracellular and transcellular fluxes (Irth/Westerhoff), and phosphorylation status of proteins in these cancer cells (Irth/Teusink), as well as enzyme activities and their adaptation (Westerhoff). These as well as proteomic and microarray data will serve as input for both global (genome-scale) and more detailed (kinetic) metabolic network modelling and regulation analysis, pinpointing the sites and mechanism of alteration. We will make a first-generation mathematical model of
- the differences between normal and the tumor cells studied and
- how receptor mediated signaling networks affect metabolic processes. This model will then be used for the first calculation of which targets might be best in terms of differential network-based drug target design, targeting metabolism and signaling, simultaneously.
