Neuroblastoma, a Paradigm for Big Data Science in Pediatric Oncology.

ABSTRACT: Pediatric cancers rarely exhibit recurrent mutational events when compared to most adult cancers. This poses a challenge in understanding how cancers initiate, progress, and metastasize in early childhood. Also, due to limited detected driver mutations, it is difficult to benchmark key genes for drug development. In this review, we use neuroblastoma, a pediatric solid tumor of neural crest origin, as a paradigm for exploring "big data" applications in pediatric oncology. Computational strategies derived from big data science-network- and machine learning-based modeling and drug repositioning-hold the promise of shedding new light on the molecular mechanisms driving neuroblastoma pathogenesis and identifying potential therapeutics to combat this devastating disease. These strategies integra

SUBMITTER: Salazar BM 

PROVIDER: S-EPMC5297672 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature