Browsing by Author "Pérez-García, Víctor M."

Brain metastases (BMs) are cancer cells that spread to the brain from primary tumors in other organs. Up to 35% of adult cancer patients develop BMs. The treatment of BM patients who have well-controlled extracranial disease and a small number of lesions consists of localized doses of radiation (stereotactic radio surgery (SRS)). Estimating prognosis among BM patients may allow treatments to be chosen that balance durability of intracranial tumor control with quality of life and the side effects of treatment. No mathematical model-based quantitative biomarkers have been determined for estimating prognosis. As a first step toward that goal, we describe a mathematical model of growth and response of brain metastasis to stereotactic radio surgery. The mathematical model incorporates some biological mechanisms involved in BM growth and response to SRS and allows the observed dynamics to be accurately described.

Most physical and other natural systems are complex entities composed of a large number of interacting individual elements. It is a surprising fact that they often obey the so-called scaling laws relating an observable quantity with a measure of the size of the system. Here we describe the discovery of universal superlinear metabolic scaling laws in human cancers. This dependence underpins increasing tumour aggressiveness, due to evolutionary dynamics, which leads to an explosive growth as the disease progresses. We validated this dynamic using longitudinal volumetric data of different histologies from large cohorts of cancer patients. To explain our observations we put forward increasingly-complex biologically-inspired mathematical models that captured the key processes governing tumor growth. Our models predicted that the emergence of superlinear allometric scaling laws is an inherently three-dimensional phenomenon. Moreover, the scaling laws thereby identified allowed us to define a set of metabolic metrics with prognostic value, thus providing added clinical utility to the base findings.