Open AccessGlobal genomic and RNA profiles for novel risk stratification of neuroblastoma
Author(s) -
Ohira Miki,
Nakagawara Akira
Publication year - 2010
Publication title -
cancer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.035
H-Index - 141
eISSN - 1349-7006
pISSN - 1347-9032
DOI - 10.1111/j.1349-7006.2010.01681.x
Subject(s) - neuroblastoma , biology , microrna , dna methylation , gene , disease , bioinformatics , microarray , genetic predisposition , phenotype , cancer research , genetics , computational biology , medicine , gene expression , cell culture
Neuroblastoma is one of the most common solid tumors in children. Its clinical behavior ranges widely from spontaneous regression to life‐threatening aggressive growth. The molecular etiology of neuroblastoma is still enigmatic and the overall cure rate of advanced disease is still very poor. Recent microarray‐based technology provided us with important information such as comprehensive genomic alterations and gene expression profiles to help us understand the molecular characteristics of each tumor in detail. Several retrospective studies have revealed that these signatures are strongly correlated with patient prognoses and led to the construction of new risk stratification systems, some of which are considered for evaluation in upcoming clinical studies in a prospective way. Large‐scale analyses using a variety of genetic tools also discovered a major familial neuroblastoma predisposition gene ALK, as well as new candidate susceptibility genes at 6q22 and 2q35 for sporadic neuroblastoma. Of note, ALK is mutated in 6–9% of sporadic cases, and is either amplified or constitutively activated through mutations mainly within the kinase domain, promoting the possibility of new therapeutic strategies using ALK inhibitors. Additional candidates for outcome predictors such as the methylation phenotype of tumor DNA and expression profiles of microRNA have also been proposed. Such variety of information will help us understand the heterogeneity of neuroblastoma biology and further, the combined use of these signatures will be beneficial in predicting prognosis with high accuracy, as well as choosing a suitable therapy for the individual patient. ( Cancer Sci 2010; 101: 2295–2301)