A mechanistic approach to neuroblastoma prognosis and risk

A mechanistic approach to neuroblastoma prognosis and risk
 

A new study reveals key molecular indicators that could help doctors select the best form of treatment for patients with neuroblastoma - the most common type of cancer in infants. The new study, which involved a genomic analysis of over 400 neuroblastomas, suggests that tumors with telomere maintenance mechanisms and certain genetic alterations are at higher-risk and may need to be treated more aggressively than tumors without these features.

Neuroblastoma is a pediatric tumor that arises from early nerve cells of the sympathetic nervous system. Some neuroblastomas are fatal despite treatment, others respond well to it, and still others undergo spontaneous regression without any treatment whatsoever.

A molecular classification scheme that predicts the likely clinical course of the disease at the time of diagnosis could help oncologists select the best treatment for each patient. Previous research had suggested a link between clinical outcome and the presence or absence of mutations in genes known to influence the maintenance of telomeres (DNA sequences capping the ends of chromosomes).

Researchers sequenced over 400 pre-treatment neuroblastomas and identified molecular features that correlate with distinct clinical outcomes. Authors found that patients whose tumors lacked telomere maintenance mechanisms had an excellent prognosis, whereas the prognosis of patients whose tumors harbored telomere maintenance mechanisms was substantially worse. Survival rates were lowest for neuroblastoma patients whose tumors harbored telomere maintenance mechanisms in combination with RAS and/or p53 pathway mutations.

Spontaneous tumor regression occurred both in the presence and absence of these mutations in patients with telomere maintenance–negative tumors. On the basis of these data, authors propose a mechanistic classification of neuroblastoma that may benefit the clinical management of patients..

http://science.sciencemag.org/content/362/6419/1165

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