miRNA Expression profiling enables risk stratification in archived and fresh neuroblastoma tumor samples
- Author
- Katleen De Preter (UGent) , Pieter Mestdagh (UGent) , Joëlle Vermeulen (UGent) , Fjoralba Zeka (UGent) , Alene Naranjo, Isabella Bray, Victoria Castel, Caifu Chen, Elzbieta Drozynska, Angelika Eggert, Michael D Hogarty, Ewa Iżycka-Swieszewska, Wendy B London, Rosa Noguera, Marta Piqueras, Kenneth Bryan, Benjamin Schowe, Peter van Sluis, Jan J Molenaar, Alexander Schramm, Johannes H Schulte, Raymond L Stallings, Rogier Versteeg, Genevieve Laureys (UGent) , Nadine Van Roy (UGent) , Franki Speleman (UGent) and Jo Vandesompele (UGent)
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- Project
- Abstract
- Purpose: More accurate assessment of prognosis is important to further improve the choice of risk-related therapy in neuroblastoma (NB) patients. In this study, we aimed to establish and validate a prognostic miRNA signature for children with NB and tested it in both fresh frozen and archived formalin-fixed paraffin-embedded (FFPE) samples. Experimental Design: Four hundred-thirty human mature miRNAs were profiled in two patient subgroups with maximally divergent clinical courses. Univariate logistic regression analysis was used to select miRNAs correlating with NB patient survival. A 25-miRNA gene signature was built using 51 training samples, tested on 179 test samples, and validated on an independent set of 304 fresh frozen tumor samples and 75 archived FFPE samples. Results: The 25-miRNA signature significantly discriminates the test patients with respect to progression-free and overall survival (P < 0.0001), both in the overall population and in the cohort of high-risk patients. Multivariate analysis indicates that the miRNA signature is an independent predictor of patient survival after controlling for current risk factors. The results were confirmed in an external validation set. In contrast to a previously published mRNA classifier, the 25-miRNA signature was found to be predictive for patient survival in a set of 75 FFPE neuroblastoma samples. Conclusions: In this study, we present the largest NB miRNA expression study so far, including more than 500 NB patients. We established and validated a robust miRNA classifier, able to identify a cohort of high-risk NB patients at greater risk for adverse outcome using both fresh frozen and archived material.
- Keywords
- PREDICTION, GENE-EXPRESSION, RNA, CLASSIFICATION, AMPLIFICATION, PROGNOSIS, NETWORKS
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Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-2123688
- MLA
- De Preter, Katleen, et al. “MiRNA Expression Profiling Enables Risk Stratification in Archived and Fresh Neuroblastoma Tumor Samples.” CLINICAL CANCER RESEARCH, vol. 17, no. 24, 2011, pp. 7684–92, doi:10.1158/1078-0432.CCR-11-0610.
- APA
- De Preter, K., Mestdagh, P., Vermeulen, J., Zeka, F., Naranjo, A., Bray, I., … Vandesompele, J. (2011). miRNA Expression profiling enables risk stratification in archived and fresh neuroblastoma tumor samples. CLINICAL CANCER RESEARCH, 17(24), 7684–7692. https://doi.org/10.1158/1078-0432.CCR-11-0610
- Chicago author-date
- De Preter, Katleen, Pieter Mestdagh, Joëlle Vermeulen, Fjoralba Zeka, Alene Naranjo, Isabella Bray, Victoria Castel, et al. 2011. “MiRNA Expression Profiling Enables Risk Stratification in Archived and Fresh Neuroblastoma Tumor Samples.” CLINICAL CANCER RESEARCH 17 (24): 7684–92. https://doi.org/10.1158/1078-0432.CCR-11-0610.
- Chicago author-date (all authors)
- De Preter, Katleen, Pieter Mestdagh, Joëlle Vermeulen, Fjoralba Zeka, Alene Naranjo, Isabella Bray, Victoria Castel, Caifu Chen, Elzbieta Drozynska, Angelika Eggert, Michael D Hogarty, Ewa Iżycka-Swieszewska, Wendy B London, Rosa Noguera, Marta Piqueras, Kenneth Bryan, Benjamin Schowe, Peter van Sluis, Jan J Molenaar, Alexander Schramm, Johannes H Schulte, Raymond L Stallings, Rogier Versteeg, Genevieve Laureys, Nadine Van Roy, Franki Speleman, and Jo Vandesompele. 2011. “MiRNA Expression Profiling Enables Risk Stratification in Archived and Fresh Neuroblastoma Tumor Samples.” CLINICAL CANCER RESEARCH 17 (24): 7684–7692. doi:10.1158/1078-0432.CCR-11-0610.
- Vancouver
- 1.De Preter K, Mestdagh P, Vermeulen J, Zeka F, Naranjo A, Bray I, et al. miRNA Expression profiling enables risk stratification in archived and fresh neuroblastoma tumor samples. CLINICAL CANCER RESEARCH. 2011;17(24):7684–92.
- IEEE
- [1]K. De Preter et al., “miRNA Expression profiling enables risk stratification in archived and fresh neuroblastoma tumor samples,” CLINICAL CANCER RESEARCH, vol. 17, no. 24, pp. 7684–7692, 2011.
@article{2123688,
abstract = {{Purpose: More accurate assessment of prognosis is important to further improve the choice of risk-related therapy in neuroblastoma (NB) patients. In this study, we aimed to establish and validate a prognostic miRNA signature for children with NB and tested it in both fresh frozen and archived formalin-fixed paraffin-embedded (FFPE) samples.
Experimental Design: Four hundred-thirty human mature miRNAs were profiled in two patient subgroups with maximally divergent clinical courses. Univariate logistic regression analysis was used to select miRNAs correlating with NB patient survival. A 25-miRNA gene signature was built using 51 training samples, tested on 179 test samples, and validated on an independent set of 304 fresh frozen tumor samples and 75 archived FFPE samples.
Results: The 25-miRNA signature significantly discriminates the test patients with respect to progression-free and overall survival (P < 0.0001), both in the overall population and in the cohort of high-risk patients. Multivariate analysis indicates that the miRNA signature is an independent predictor of patient survival after controlling for current risk factors. The results were confirmed in an external validation set. In contrast to a previously published mRNA classifier, the 25-miRNA signature was found to be predictive for patient survival in a set of 75 FFPE neuroblastoma samples.
Conclusions: In this study, we present the largest NB miRNA expression study so far, including more than 500 NB patients. We established and validated a robust miRNA classifier, able to identify a cohort of high-risk NB patients at greater risk for adverse outcome using both fresh frozen and archived material.}},
author = {{De Preter, Katleen and Mestdagh, Pieter and Vermeulen, Joëlle and Zeka, Fjoralba and Naranjo, Alene and Bray, Isabella and Castel, Victoria and Chen, Caifu and Drozynska, Elzbieta and Eggert, Angelika and Hogarty, Michael D and Iżycka-Swieszewska, Ewa and London, Wendy B and Noguera, Rosa and Piqueras, Marta and Bryan, Kenneth and Schowe, Benjamin and van Sluis, Peter and Molenaar, Jan J and Schramm, Alexander and Schulte, Johannes H and Stallings, Raymond L and Versteeg, Rogier and Laureys, Genevieve and Van Roy, Nadine and Speleman, Franki and Vandesompele, Jo}},
issn = {{1078-0432}},
journal = {{CLINICAL CANCER RESEARCH}},
keywords = {{PREDICTION,GENE-EXPRESSION,RNA,CLASSIFICATION,AMPLIFICATION,PROGNOSIS,NETWORKS}},
language = {{eng}},
number = {{24}},
pages = {{7684--7692}},
title = {{miRNA Expression profiling enables risk stratification in archived and fresh neuroblastoma tumor samples}},
url = {{http://doi.org/10.1158/1078-0432.CCR-11-0610}},
volume = {{17}},
year = {{2011}},
}
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