Authors: Elena Conroy, Future Science Group
A new computation model developed in the laboratory of Salvatore Torquato at Princeton University (NJ, USA) may help advance our understanding of the conditions surrounding tumor dormancy and the switch to a malignant state. Recently published in PLOS ONE, the cellular automaton (CA) model is able to simulate various scenarios of tumor growth leading to tumor suppression, proliferation or dormancy.
In pancreatic cancer, tumor dormancy can last up to 25 years before the disease becomes aggressively malignant, a phenomenon that is yet to be understood.
“The power of the model is that it lets people test medically realistic scenarios,” explained Torquato. “In future collaborations, these scenarios could be engineered in laboratory experiments and the observed outcomes could be used to calibrate the model.”
The computational model allows exploration of a variety of scenarios. For each scenario, a set of rules is imposed on virtual cell populations. These rules, which were derived from a previous CA model, include interactions that dictate cell division such as neighboring cell death or immune system suppression. The new CA model rules induce natural ’competition’ between the tumor and tumor-suppression factors in the microenvironment.
“We were very surprised to observe this phenomenon where the tumor all of a sudden began to rapidly divide,” commented Duyu Chen (Princeton University), lead author of the article. “This was the first time that the emergent switch behavior, which has been observed clinically, occurred spontaneously in a model”.
The study evaluated a number of different factors that could affect tumor cell growth, including phenotypic changes, mechanical properties and strength of suppression factors. One of the CA model’s findings was the likely suppression of tumors in harsh environments characterized by high density and high pressure.
Torquato’s team predicted that if the number of actively dividing cells within the proliferative rim of the tumor reached a critical, yet low level, the dormant tumor had a high probability to resume rapid growth.
These findings could shed light on the fundamental understanding of cancer dormancy and provide insight into early cancer treatment.
Sources: Chen D, Jiao Y, Torquato, S. A Cellular Automaton Model for Tumor Dormancy: Emergence of a Proliferative Switch Duyu. PLOS ONE, 9(10): e109934 doi:10.1371/journal.pone.0109934 (2014); Princeton University press release