Validation of a prognostic multi-gene signature in high-risk neuroblastoma using the high throughput digital NanoString nCounter™ system.
Mol Oncol
; 8(3): 669-78, 2014 May.
Article
em En
| MEDLINE
| ID: mdl-24560446
ABSTRACT
Microarray-based molecular signatures have not been widely integrated into neuroblastoma diagnostic classification systems due to the complexities of the assay and requirement for high-quality RNA. New digital technologies that accurately quantify gene expression using RNA isolated from formalin-fixed paraffin embedded (FFPE) tissues are now available. In this study, we describe the first use of a high-throughput digital system to assay the expression of genes in an "ultra-high risk" microarray classifier in FFPE high-risk neuroblastoma tumors. Customized probes corresponding to the 42 genes in a published multi-gene neuroblastoma signature were hybridized to RNA isolated from 107 FFPE high-risk neuroblastoma samples using the NanoString nCounter™ Analysis System. For classification of each patient, the Pearson's correlation coefficient was calculated between the standardized nCounter™ data and the molecular signature from the microarray data. We demonstrate that the nCounter™ 42-gene panel sub-stratified the high-risk cohort into two subsets with statistically significantly different overall survival (p = 0.0027) and event-free survival (p = 0.028). In contrast, none of the established prognostic risk markers (age, stage, tumor histology, MYCN status, and ploidy) were significantly associated with survival. We conclude that the nCounter™ System can reproducibly quantify expression levels of signature genes in FFPE tumor samples. Validation of this microarray signature in our high-risk patient cohort using a completely different technology emphasizes the prognostic relevance of this classifier. Prospective studies testing the prognostic value of molecular signatures in high-risk neuroblastoma patients using FFPE tumor samples and the nCounter™ System are warranted.
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MEDLINE
Assunto principal:
Análise de Sequência com Séries de Oligonucleotídeos
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Neuroblastoma
Idioma:
En
Ano de publicação:
2014
Tipo de documento:
Article