An integrated proteomic approach to identifying circulating biomarkers in high-risk neuroblastoma and their potential in relapse monitoring

Proteomics Clin Appl. 2011 Oct;5(9-10):532-41. doi: 10.1002/prca.201000089. Epub 2011 Sep 7.


Purpose: Despite intensive treatment regimens, overall survival for high-risk neuroblastoma (HRNB) is still poor. This is in part due to an inability to cure the disease once a patient has reached clinical relapse. Identifying plasma biomarkers of active disease may provide a way of relapse monitoring in HRNB.

Experimental design: In this study, we developed an integrated proteomic approach to identify plasma biomarkers for HRNB.

Results: We identified seven candidate biomarkers (SAA, APOA1, IL-6, EGF, MDC, sCD40L and Eotaxin) for HRNB. These biomarkers were then used to create a multivariate classifier of HRNB, which showed a specificity of 90% (95% confidence interval (CI), 73%, 98%), and a sensitivity of 81% (95%CI, 54%, 96%) for classifying HRNB in a training set. When evaluated on independent test samples, the classifier exhibited 86% accuracy (95% CI, 42%, 100%) of identifying diagnostic samples, and 86% accuracy (95% CI, 70%, 100%) of detecting post-diagnosis longitudinal samples that having active disease.

Conclusion and clinical relevance: Further validation of these biomarkers may improve patients' outcomes by developing a simple blood test for the detection of relapse prior to the development of clinically evident disease. Understanding the role of these biomarkers in immune surveillance of neuroblastoma may also provide a new direction of therapeutic strategies.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adolescent
  • Biomarkers / blood*
  • Child
  • Child, Preschool
  • Cytokines / metabolism
  • Female
  • Humans
  • Infant
  • Longitudinal Studies
  • Male
  • Neoplasm Staging
  • Neuroblastoma / diagnosis*
  • Neuroblastoma / metabolism
  • Neuroblastoma / prevention & control
  • Proteomics / methods*
  • Recurrence
  • Risk Factors
  • Sensitivity and Specificity
  • Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization


  • Biomarkers
  • Cytokines