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

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.