In this study, the circulating miRNome from diagnostic neuroblastoma serum was assessed for identification of noninvasive biomarkers with potential in monitoring metastatic disease. After determining the circulating neuroblastoma miRNome, 743 miRNAs were screened in 2 independent cohorts of 131 and 54 patients. Evaluation of serum miRNA variance in a model testing for tumor stage, MYCN status, age at diagnosis, and overall survival revealed tumor stage as the most significant factor impacting miRNA abundance in neuroblastoma serum. Differential abundance analysis between patients with metastatic and localized disease revealed 9 miRNAs strongly associated with metastatic stage 4 disease in both patient cohorts. Increasing levels of these miRNAs were also observed in serum from xenografted mice bearing human neuroblastoma tumors. Moreover, murine serum miRNA levels were strongly associated with tumor volume. These findings were validated in longitudinal serum samples from metastatic neuroblastoma patients, where the 9 miRNAs were associated with disease burden and treatment response.
Fjoralba Zeka, Anneleen Decock, Alan Van Goethem, Katrien Vanderheyden, Fleur Demuynck, Tim Lammens, Hetty H. Helsmoortel, Joëlle Vermeulen, Rosa Noguera, Ana P. Berbegall, Valérie Combaret, Gudrun Schleiermacher, Geneviève Laureys, Alexander Schramm, Johannes H. Schulte, Sven Rahmann, Julie Bienertová-Vašků, Pavel Mazánek, Marta Jeison, Shifra Ash, Michael D. Hogarty, Mirthala Moreno-Smith, Eveline Barbieri, Jason Shohet, Frank Berthold, Tom Van Maerken, Frank Speleman, Matthias Fischer, Katleen De Preter, Pieter Mestdagh, Jo Vandesompele
Usage data is cumulative from December 2022 through December 2023.
Usage | JCI | PMC |
---|---|---|
Text version | 570 | 76 |
40 | 36 | |
Figure | 70 | 3 |
Table | 17 | 0 |
Supplemental data | 41 | 0 |
Citation downloads | 7 | 0 |
Totals | 745 | 115 |
Total Views | 860 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.