Computing Cancer

Last week's Cell has a paper using simulations to estimate the influence of the local microenvironment on the development of invasiveness in cancers. Their model includes both discrete elements (cells, which have a number of associated discrete states) and continuous variables, and is therefore referred to as a Hybrid Discrete-Continuum, or HDC, model. Properties associated with a cell include both internal activities, such as metabolism, and external ones, such as oxygen tension (which, the authors point out, could be any diffusible nutrient), secretion of extracellular matrix degrading enzymes, and the concentration of extracellular matrix.

With any model, the fun part are the predictions they make -- particularly the unorthodox ones. Predictions enable verification or invalidation. For the Cell paper, they do make quite an interesting prediction:

The HCC model predicts that invasive tumor properties are reversible under appropriate microenvironment conditions and suggests that differentiating therapy aimed at cancer-microenvironment interactions may be more useful than making the microenvironment harsher (e.g. by chemotherapy or antiangiogenic therapy).

Experimentally testing such predictions is decidedly non-trivial, but at least now the challenge has been posed. This prediction has clear implications for choosing therapeutic strategies, particularly in picking combinations of oncology drugs -- and few cancer patients are on only a single anti-tumor agent.

This paper is also part of Cell's experiment in electronic feedback -- readers can submit comments on the paper. The opportunity to be the first commenter still appears available -- is there anyone reading this brave enough to go for it?