Revised risk estimation and treatment stratification of low- and intermediate-risk neuroblastoma patients by integrating clinical and molecular prognostic markers

André Oberthuer, Dilafruz Juraeva, Barbara Hero, Ruth Volland, Carolina Sterz, Rene Schmidt, Andreas Faldum, Yvonne Kahlert, Anne Engesser, Shahab Asgharzadeh, Robert Seeger, Miki Ohira, Akira Nakagawara, Paola Scaruffi, Gian Paolo Tonini, Isabelle Janoueix-Lerosey, Olivier Delattre, Gudrun Schleiermacher, Jo Vandesompele, Frank SpelemanRosa Noguera, Marta Piqueras, Jean Bénard, Alexander Valent, Smadar Avigad, Isaac Yaniv, Richard G. Grundy, Monika Ortmann, Chunxuan Shao, Manfred Schwab, Roland Eils, Thorsten Simon, Jessica Theissen, Frank Berthold, Frank Westermann, Benedikt Brors, Matthias Fischer*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: To optimize neuroblastoma treatment stratification, we aimed at developing a novel risk estimation system by integrating gene expression-based classification and established prognostic markers. Experimental Design: Gene expression profiles were generated from 709 neuroblastoma specimens using customized 4 x 44 K microarrays. Classification models were built using 75 tumors with contrasting courses of disease. Validation was performed in an independent test set (n = 634) by Kaplan-Meier estimates and Cox regression analyses. Results: The best-performing classifier predicted patient outcome with an accuracy of 0.95 (sensitivity, 0.93; specificity, 0.97) in the validation cohort. The highest potential clinical value of this predictor was observed for current low-risk patients [5-year event-free survival (EFS), 0.84 ± 0.02 vs. 0.29 ± 0.10; 5-year overall survival (OS), 0.99 ± 0.01 vs. 0.76 ± 0.11; both P < 0.001] and intermediate-risk patients (5-year EFS, 0.88 ± 0.06 vs. 0.41 ± 0.10; 5-year OS, 1.0 vs. 0.70 ± 0.09; both P < 0.001). Inmultivariate Cox regression models for low-risk/intermediate-risk patients, the classifier outperformed risk assessment of the current German trial NB2004 [EFS: hazard ratio (HR), 5.07; 95% confidence interval (CI), 3.20-8.02; OS: HR, 25.54; 95% CI, 8.40-77.66; both P < 0.001]. On the basis of these findings, we propose to integrate the classifier into a revised risk stratification system for low-risk/intermediate-risk patients. According to this system, we identified novel subgroups with poor outcome (5-year EFS, 0.19 ± 0.08; 5-year OS, 0.59 ± 0.1), for whomwe propose intensified treatment, and with beneficial outcome (5-year EFS, 0.87 ± 0.05; 5-year OS, 1.0), who may benefit from treatment de-escalation. Conclusions: Combination of gene expression-based classification and established prognostic markers improves risk estimation of patients with low-risk/intermediate-risk neuroblastoma. We propose to implement our revised treatment stratification system in a prospective clinical trial.

Original languageEnglish
Pages (from-to)1904-1915
Number of pages12
JournalClinical Cancer Research
Volume21
Issue number8
DOIs
StatePublished - 15 Apr 2015

Funding

FundersFunder number
Bundesministerium für Bildung und Forschung01GS0896, 01GS0895
Japan Society for the Promotion of Science26461603, 24249061

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