First published July 1 2016
A Boolean network model for invasive thyroid carcinoma
Jess Espinal-Enriquez, Ral Alejandro Meja-Pedroza, and Enrique Hernndez-Lemus
Thyroid cancer is a common endocrine system neoplasm characterized by being extremely heterogeneous and of unexplained incidence (idiopathic). Some subtypes of thyroid cancer are more aggressive than others and for this reason treatment needs to be differential. Nonetheless, due to its inherent variability, prognosis based on pathology and/or bio-chemical profiling often fails leading to a delay in proper therapeutics that increases significantly the associated mortality. The most aggressive thyroid tumors are characterized by an increase in the destruction of extracellular matrix, this is done by the matrix metalloproteinases (MMPs). The regulation of MMPs is finely tuned by several molecules, but the dynamical mechanisms which control this pathway are still unknown. Here, based on detailed molecular interaction information coming from functional tests and gene expression experiments, we develop a boolean model of the matrix metalloproteinases pathway in thyroid cancer. By observing steady state conditions perturbing the network by simulating a specific drug, we find that TNFA could be a major target of this pathway. The approach performed here could allow to understand the finely regulated process to maintain extracellular matrix homeostasis.