Validation of a prognostic multi‐gene signature in high‐risk neuroblastoma using the high throughput digital NanoString nCounter™ system
Open accessAbstract
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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The best performing models were able to predict outcome of high-risk patients with a similar precision as previously published multigene signatures, and independently from current prognostic markers.
“In addition, we found that the best performing models were able to predict outcome of high-risk patients with a similar precision as previously published multigene signatures [18, 20, 33], and independently from current prognostic markers.”
From Comparison of RNA-seq and microarray-based models for clinical endpoint prediction (2015) · cites this paper as [33]
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Comparison of RNA-seq and microarray-based models for clinical endpoint prediction
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- Authors
- Stricker, T. P., Morales La Madrid, A., Chlenski, A., Guerrero, L., Salwen, H. R., Gosiengfiao, Y., Perlman, E. J., Furman, W., Bahrami, A., Shohet, J. M., Zage, P. E., Hicks, M. J., Shimada, H., Suganuma, R., Park, J. R., So, S., London, W. B., Pytel, P., Maclean, K. H., & Cohn, S. L.
- Affiliations
- Vanderbilt University (US)
- University of Chicago (US)
- Northwestern University (US)
- St. Jude Children's Research Hospital (US)
- Baylor College of Medicine (US)
- Children's Hospital Los Angeles (US)
- Seattle Children's Hospital (US)
- Boston Children's Hospital (US)
- Nanostring Technologies (United States) (US)
- Corresponding author
- Cohn, Susan L.
- ORCID
- Venue
- Molecular Oncology
- Publisher
- Wiley
- Published
- 2014-01-31
- Volume
- 8
- Issue
- 3
- Pages
- 669-678
- ISSN
- 1574-7891 (ISSN-L)
- 1878-0261
- PMC
- PMC4004665
- OpenAlex
- W2013276712
- Cited by
- 36
- References
- 32
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 1 · 2020: 3 · 2019: 2 · 2018: 5 · 2017: 3 · 2016: 8 · 2015: 11 · 2014: 1
- FWCI
- 5.00
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Molecular Oncology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- Conquer Cancer Foundation (AML)
- St. Baldrick's Foundation (AML)
- Children's Neuroblastoma Cancer Foundation (SLC)
- Neuroblastoma Children's Cancer Society (SLC)
- Elise Anderson Foundation (SLC)
- The National Cancer Institute
- Topics
- Health Sciences › Medicine › Neurology › Neuroblastoma Research and Treatments
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
- Keywords
- high-risk neuroblastoma, NanoString nCounter, digital gene expression profiling, formalin-fixed paraffin-embedded tissue, overall survival, event-free survival, MYCN, tumor ploidy, prognostic risk classification
- MeSH terms
- Humans, Infant, Neuroblastoma, Prognosis, Cohort Studies, Cluster Analysis, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling
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