Phillip Manno is a medical oncologist/hematologist with the Nevada Cancer Institute in Nevada. “My clinical interests include lung and head & neck cancer. My NKS interests are motivated towards its application to fields of cellular signal transduction and carcinogenesis.”
Project: Carcinogenesis in Substitution Systems
In carcinogenesis, we know that normal tissue follows growth patterns that are balanced by organized interactive patterns between cells ultimately leading to apoptosis (programmed cell death). Growth is considered exponential. When a clonal perturbation occurs in a normal cell, a cluster of sequential mutations over time can lead to genomic instability and the development of a malignant phenotype with growth autonomy and evasion of apoptosis. The accumulation of this monoclonal population leads to the invasive destruction of neighboring cells. I would submit that as simple rules lead to complexity in a computational universe, the same may be true for patterns of cancer in nature.
We know that a feature described in simple 1D substitution systems is that the number of elements can change when some elements are replaced by a block of new elements. This is in contrast to cellular automata, mobile automata, or Turing machines, in which the number and organization of cells remain the same. Intuitively, this may provide a useful methodology for our search. We will therefore look at the behavior of sequential substitution systems with rules dependent on the cell itself and its neighbors as this may yield sufficient complexity analogous to the behavior seen in cancer. We will also consider a 2D substitution searching for the qualities of division and networking possibly revealing patterns seen in signal transduction pathways and cellular organization.