Predicting outcomes for children with neuroblastoma using a multigene-expression signature: a retrospective SIOPEN/COG/GPOH study - PubMed (original) (raw)

doi: 10.1016/S1470-2045(09)70154-8. Epub 2009 Jun 8.

Katleen De Preter, Arlene Naranjo, Liesbeth Vercruysse, Nadine Van Roy, Jan Hellemans, Katrien Swerts, Sophie Bravo, Paola Scaruffi, Gian Paolo Tonini, Bruno De Bernardi, Rosa Noguera, Marta Piqueras, Adela Cañete, Victoria Castel, Isabelle Janoueix-Lerosey, Olivier Delattre, Gudrun Schleiermacher, Jean Michon, Valérie Combaret, Matthias Fischer, André Oberthuer, Peter F Ambros, Klaus Beiske, Jean Bénard, Bárbara Marques, Hervé Rubie, Janice Kohler, Ulrike Pötschger, Ruth Ladenstein, Michael D Hogarty, Patrick McGrady, Wendy B London, Geneviève Laureys, Frank Speleman, Jo Vandesompele

Affiliations

Predicting outcomes for children with neuroblastoma using a multigene-expression signature: a retrospective SIOPEN/COG/GPOH study

Joëlle Vermeulen et al. Lancet Oncol. 2009 Jul.

Abstract

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.

PubMed Disclaimer

Conflict of interest statement

Conflict of interest

The authors declare no conflict of interest.

Figures

Figure 1

Figure 1

Kaplan-Meier and log-rank analysis for progression-free (a) and overall (b) survival of the entire SIOPEN/GPOH cohort * missing relapse date for one HR case LR: low molecular risk HR: high molecular risk PFS: progression-free survival OS: overall survival (Legend: number of patients in predicted subgroups, between brackets: number of patients with event)

Figure 2

Figure 2

Kaplan-Meier and log-rank analysis for progression-free (a) and overall (b) survival of the stratified SIOPEN cohort according to currently used risk factors * missing relapse date for one HR case LR: low molecular risk HR: high molecular risk PFS: progression-free survival OS: overall survival (Legend: number of patients in predicted subgroups, between brackets: number of patients with event) Missing MYCN status for 1 HR case

Figure 3

Figure 3

Kaplan-Meier and log-rank analysis for progression-free (a) and overall (b) survival of the stratified SIOPEN cohort according to treatment group * missing relapse date for one HR case LR: low molecular risk HR: high molecular risk PFS: progression-free survival OS: overall survival (Legend: number of patients in predicted subgroups, between brackets: number of patients with event)

Comment in

Similar articles

Cited by

References

    1. Maris JM, Hogarty MD, Bagatell R, Cohn SL. Neuroblastoma. Lancet. 2007;369:2106–2120. - PubMed
    1. van 't Veer LJ, Dai H, van de Vijver MJ, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature. 2002;415:530–536. - PubMed
    1. Liu R, Wang X, Chen GY, et al. The prognostic role of a gene signature from tumorigenic breast-cancer cells. N Engl J Med. 2007;356:217–226. - PubMed
    1. Wang Y, Klijn JG, Zhang Y, et al. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet. 2005;365:671–679. - PubMed
    1. Chen HY, Yu SL, Chen CH, et al. A five-gene signature and clinical outcome in non-small-cell lung cancer. N Engl J Med. 2007;356:11–20. - PubMed

Publication types

MeSH terms

Substances

Grants and funding

LinkOut - more resources