New Model for Predicting Neuroblastoma Outcomes Incorporates Early Developmental Signals
Neuroblastoma, a rare childhood cancer of the sympathetic nervous system, is particularly deadly because it is difficult to detect and thus generally advanced before treatment begins. Scientists know that neuroblastoma develops from embryonic neural crest cells that fail to properly migrate or differentiate, but the details about exactly what causes these cells to go astray have been unclear.
Motivated by a desire to better understand the molecular circuitry underlying neuroblastoma and limitations of current methods for predicting disease progression and outcome, researchers from the Kulesa Lab at the Stowers Institute for Medical Research and collaborators at the University of Michigan and Oxford University set out to construct a logic-based model incorporating information about developmental signaling pathways implicated in the disease. They sought to test whether their model could predict disease outcomes more effectively than the current predictive methods, which are based on gene expression information from human patient samples but do not provide much insight about how these molecules interact to participate in disease progression.
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14th International Conference on Neurology, Neuroscience and Neuromuscular Disorders
June 17-18, 2019; Tokyo
CARS 2019 Computer Assisted Radiology and Surgery
June 18-21, 2019; Rennes, France
18th Meeting of WSSFN
June 24-27, 2019; New York
International Summer School Transnasal Endoscopic Surgery: From Sinuses to Skull Base
June 24-28, 2019; Brescia, Italy
The Society of University Neurosurgeons Annual Meeting
June 26-30, 2019; Dubrovnik, Croatia