New Model for Predicting Neuroblastoma Outcomes Incorporates Early Developmental Signals
Neuroblastoma, the most deadly cancer for infants and children younger than two years of age, is difficult to diagnose and treat. To improve the chances for survival, scientists have been searching for ways to better understand the cellular mechanics of what causes neuroblastoma and how it progresses.
Using published research on molecular signals important in development and also implicated in neuroblastoma, researchers from the Kulesa Lab and collaborators created a logic-based model that predicted the favorable or unfavorable outcomes of very young neuroblastoma patients with greater accuracy than current methods of predicting outcomes. This work demonstrates the ability of such models to predict disease outcomes and offer a better understanding of molecular network interactions in disease.
This study was published in the July 2018 issue of Biophysical Chemistry.