Predicting the incidence of cancer: Does natural selection pick holographic networks?

Director's Seminar Series Maintenance of function in many tissues in adult animals requires controlled somatic stem cell replication. The vast majority of these replication events are uneventful, as there are multiple levels of quality control: DNA damage repair mechanisms, paracrine signaling and the extracellular matrix, the immune system, and likely others that have not been uncovered. Our work has modeled tissue development and homeostasis processes in a variety of tissues: adipose tissue, beta cells in the islets of Langerhans, the development of the overall endocrine pancreas, and liver regeneration after partial hepatectomy. We will discuss levels at which tissue homeostasis can be modeled with large-scale data collection, and some general theoretical features of networks that dynamically can maintain homeostasis. Turning then to the other end of the spectrum of cell replication, cancer, where cells have evaded quality control, we will survey models of cancer incidence, and propose a new dynamic model that predicts population cancer incidence for all types of sporadic cancers with few parameters. This model reveals a startling simplicity in the sum total effect of the multiple levels of cellular replication quality control in all cancer types. We attempt to understand the relative contributions of different repair mechanisms by modeling skin cancer incidence in Xeroderma Pigmentosum subjects. Air date: 3/11/2016 12:00:00 PM
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