Description
To support their unrestricted growth, cancer cells require a permanent supply of glucose that can be obtained from cancer-mediated reprogramming of glucose/insulin metabolism in their host. The pathological mechanisms by which cancer cells exert their negative influence on host glucose/insulin metabolism remain poorly understood. Research by cancer biologists indicates that in breast cancer (and likely many others), the cancer cells secrete extracellular vesicles (EVs) that inhibit insulin production by the β-cells in the pancreas. Healthy insulin-dependent cells, such as skeletal muscle, fat cells and hepatic cells thereby have reduced ability to absorb glucose from the blood. Experimental work is currently underway in the laboratory of our collaborator at the University of California San Diego that will elucidate the mechanisms by which breast cancer secreted EVs suppress insulin production and induce insulin resistance. Mathematical modeling and simulation will help to better understand the outcome of these experiments and, in addition, help to formulate new hypotheses and design new experiments. In the long run, breast cancer patients will profit from novel therapeutic strategies and the possibility of treatment of metabolic co-morbidities.
Tasks and Responsibilities
The first task is to survey the literature for mathematical models of glucose-insulin-glucagon metabolism in healthy individuals and diabetes patients. In a healthy individual, the glucose regulatory system in the pancreas maintains the body’s blood glucose concentration between 70 and 120 mg/dl. Factors influencing the system are inputs from eating, additional use of internal glucose stores and different glucose needs during the circadian cycle. Special attention will be paid to ordinary differential equation (ODE) models that are flexible and which can accommodate additional compartments and interactions with cancerous organs. Another task is to check for sound parameter choices. In the second step, the student will assist in building compartmental ODE models. ODE models have the advantage that they are easily simulated numerically using for example Python or julia. Additional variables will be the tumor's glucose consumption, the secreted EVs in the bloodstream and their action on the insulin production in the pancreas. Two scenariosare planned to be simulated, namely a previously healthy individual and a diabetes patient with breast cancer. A central question will be how the existing metabolic disease influences the outcome of the cancer treatment.