Genetic heterogeneity and clonal evolution have been shown to play a role in progression of neuroblastoma. Recent data from other malignancies suggest that genetic heterogeneity might reflect not only evidence of competing clones, but also cooperating clonal events. This workshop will focus on neuroblastoma genetic heterogeneity, seeking to explore how recent and emerging technologies such as single cell studies and surrogate samples including circulating tumor DNA (ctDNA) and disseminated/circulating tumor cells (DTC/CTC) and can contribute to the understanding of the role of genetic heterogeneity and clonal evolution in tumor progression. While highlighting technical issues, challenges and pitfalls, the important questions of how these findings can be harnessed for clinical management of neuroblastoma patients will be further discussed.
Risk stratification approaches that rely on robust clinical and biological prognostic factors have been used to predict outcome and tailor therapies for neuroblastoma patients for more than two decades. Current classification systems utilize clinical, histologic, and genetic factors to identify patients with low, intermediate, or high risk neuroblastoma. Recent advances have resulted in improved patient outcomes; however, long-term survival for high-risk patients remains < 50%. Furthermore, current prognostic factors do not predict which high-risk (HR) neuroblastoma patients will fail to achieve remission with current era therapies. There are many efforts aimed at prospectively identifying the subset of HR patients at highest risk of death, or “ultra-high risk (UHR) patients, “ for whom novel therapies may be indicated early on in the course of the disease. Currently there is no uniform definition for UHR and to date, no clinical or genetic determinant(s) reliably identify UHR patients. In this workshop we will highlight recent advances in the discovery of germline and somatic genomic alterations that may predict poor outcome or failure to respond to therapy in the setting of high-risk disease. The potential roles for gene expression signatures and detection of minimal residual disease will also be discussed. Following these presentations there will be a panel discussion to consider how to incorporate these novel prognostic factors into upfront clinical trials and how we may use genomic markers and minimum residual disease status together with current prognostic factors to further refine the next generation of risk classification systems.