Predicting outcomes for children with neuroblastoma using a multigene-expression signature: a retrospective SIOPEN/COG/GPOH study
Open accessAbstract
Background More accurate prognostic assessment of patients with neuroblastoma is required to better inform the choice of risk-related therapy. The aim of this study is to develop and validate a gene-expression signature to improve outcome prediction.Methods 59 genes were selected using an innovative data-mining strategy, and were profiled in the largest neuroblastoma patient series (n=579) to date using real-time quantitative PCR starting from only 20 ng of RNA. A multigene-expression signature was built using 30 training samples, tested on 313 test samples, and subsequently validated in a blind study on an independent set of 236 tumours.Findings The signature has a performance, sensitivity, and specificity of 85.4% (95% CI 77.7-93.2), 84.4% (66.5-94.1), and 86.5% (81.1-90.6), respectively, to predict patient outcome. Multivariate analysis indicates that the signature is a significant independent predictor of overall survival and progression-free survival after controlling for currently used risk factors: patients with high molecular risk have a higher risk of death from disease and higher risk of relapse or progression than patients with low molecular risk (odds ratio 19.32 [95% CI 6.50-57.43] and 3.96 [1.97-7.97] for overall survival and progression-free survival, respectively, both p<0.0001). Patients at an increased risk of an adverse outcome can also be identified in the current treatment groups, showing the potential of this signature for improved clinical management. These results were confirmed in the validation study, in which the signature was also independently statistically significant in a model adjusted for MYCN status, age, International Neuroblastoma Staging System stage, ploidy, International Neuroblastoma Pathology Classification grade of differentiation, and mitosis karyorrhexis index (odds ratios between 4.81 and 10.53 depending on the model for overall survival and 3.68 [95% CI 2.01-6.71] for progression-free survival).Interpretation The 59-gene expression signature is an accurate predictor of outcome in patients with neuroblastoma. The signature is an independent risk predictor, identifying patients with an increased risk of poor outcome in the current clinical-risk groups. The method and signature is suitable for routine laboratory testing, and should be evaluated in prospective studies.Funding The Belgian Foundation Against Cancer, the Children Cancer Fund Ghent, the Belgian Society of Paediatric Haematology and Oncology, the Belgian Kid's Fund and the Fondation Nuovo-Soldati (JV), the Fund for Scientific Research Flanders (KDP, JH), the Fund for Scientific Research Flanders, the Institute for the Promotion of Innovation by Science and Technology in Flanders, Strategisch basisonderzoek, the Fondation Fournier Majoie pour l'Innovation, the Instituto Carlos III, the Italian Neuroblastoma Foundation, the European Community under the FP6, and the Belgian programme of Interuniversity Poles of Attraction.
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Prediction of high-risk neuroblastoma patient outcome has remained challenging.
“However, while predictive models were highly accurate in risk assessment of current low- and intermediate-risk patients [18], the prediction of high-risk patient outcome has remained challenging [18–20].”
From Comparison of RNA-seq and microarray-based models for clinical endpoint prediction (2015) · cites this paper as [20]
The best performing models significantly discriminated patients with favorable and unfavorable outcome in the entire cohort and in the class labeled cohort.
“The models significantly discriminated patients with favorable and unfavorable outcome in the entire cohort and in the class labeled cohort (Additional file 1: Figure S9a-d, Table S3 and S4), which is consistent with previous observations made by us and others [16–18, 20].”
From Comparison of RNA-seq and microarray-based models for clinical endpoint prediction (2015) · cites this paper as [20]
Both gene expression-based models derived from RNA-seq and microarray analyses were capable of predicting patient outcome in the entire neuroblastoma cohort accurately.
“Both gene expression-based models derived from RNA-seq and microarray analyses were capable of predicting patient outcome in the entire neuroblastoma cohort accurately, thereby validating results from previous studies and underscoring their potential clinical utility for risk estimation in neuroblastoma [16–18, 20].”
From Comparison of RNA-seq and microarray-based models for clinical endpoint prediction (2015) · cites this paper as [20]
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 [20]
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Comparison of RNA-seq and microarray-based models for clinical endpoint prediction
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- Authors
- Vermeulen, J., De Preter, K., Naranjo, A., Vercruysse, L., Van Roy, N., Hellemans, J., Swerts, K., Bravo, S., Scaruffi, P., Tonini, G. P., De Bernardi, B., Noguera, R., Piqueras, M., Cañete, A., Castel, V., Janoueix-Lerosey, I., Delattre, O., Schleiermacher, G., Michon, J., Combaret, V., Fischer, M., Oberthuer, A., Ambros, P. F., Beiske, K., Bénard, J., Marques, B., Rubie, H., Kohler, J., Pötschger, U., Ladenstein, R., Hogarty, M. D., McGrady, P., London, W. B., Laureys, G., Speleman, F., & Vandesompele, J.
- Affiliations
- Ghent University Hospital (BE)
- University of Florida (US)
- Universitat de València (ES)
- Inserm (FR)
- Institut Curie (FR)
- Centre Léon Bérard (FR)
- University Hospital Cologne (DE)
- St. Anna Children's Cancer Research Institute (AT)
- Oslo University Hospital (NO)
- Centre National de la Recherche Scientifique (FR)
- National Institute of Health Dr. Ricardo Jorge (PT)
- Southampton General Hospital (GB)
- Children's Hospital of Philadelphia (US)
- Corresponding author
- Vandesompele, Jo
- ORCID
- Naranjo, Arlene
- Hellemans, Jan
- Scaruffi, Paola
- Tonini, Gian Paolo
- Noguera, Rosa
- Piqueras, Marta
- Cañete, Adela
- Castel, Victoria
- Delattre, Olivier
- Schleiermacher, Gudrun
- Michon, Jean
- Combaret, Valérie
- Fischer, Matthias
- Oberthuer, André
- Ambros, Peter F
- Beiske, Klaus
- Marques, Bárbara
- Pötschger, Ulrike
- Ladenstein, Ruth
- Hogarty, Michael D
- London, Wendy B
- Laureys, Geneviève
- Speleman, Frank
- Vandesompele, Jo
- Venue
- The Lancet Oncology
- Publisher
- Elsevier BV
- Published
- 2009-07
- Volume
- 10
- Issue
- 7
- Pages
- 663-671
- ISSN
- 1470-2045 (ISSN-L)
- PMC
- PMC3045079
- OpenAlex
- W2171873561
- Cited by
- 192
- References
- 29
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 9 · 2023: 10 · 2022: 2 · 2021: 9 · 2020: 6 · 2019: 8 · 2018: 9 · 2017: 12 · 2016: 6 · 2015: 8 · 2014: 12 · 2013: 15 · 2012: 26
- FWCI
- 17.07
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The Lancet Oncology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Ghent University Academic Bibliography (Ghent University) (submittedVersion)
- Funders
- Vlaamse regering
- Fondation contre le Cancer
- National Cancer Institute (U10CA098413, U24CA114766, U10CA098543)
- Topics
- Health Sciences › Medicine › Neurology › Neuroblastoma Research and Treatments
- Health Sciences › Medicine › Neurology › Neurofibromatosis and Schwannoma Cases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
- Keywords
- neuroblastoma, gene expression signatures, prognostic factors, outcome prediction, multi-gene signature, overall survival, progression-free survival, molecular risk stratification, MYCN, COG, childhood cancer, relapse risk, data mining, real-time quantitative PCR, risk-adapted treatment, ploidy, mitosis-karyorrhexis index
- MeSH terms
- Follow-Up Studies, Humans, Infant, Neuroblastoma, Prognosis, Sensitivity and Specificity, Biomarkers, Tumor, Reproducibility of Results, Multivariate Analysis, Logistic Models, Survival Analysis, Case-Control Studies, Gene Expression Profiling
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