Integrating multi-omics data reveals neuroblastoma subtypes in the tumor microenvironment

Abstract

Neuroblastoma (NB) is a severe pediatric tumor originating from the developing sympathetic nervous system, characterized by diverse clinical outcomes, including spontaneous regression and aggressive metastasis. This variability suggests the existence of different NB subtypes, necessitating accurate classification for effective targeted treatment. In this study, we employed the similarity network fusion (SNF) algorithm and identified three NB subtypes, including mesenchymal-like (MES), MYCN-like (MYCN), and neurogenic-like (Neurogenic). The MES subtype exhibited the highest activation of immune-related pathways. The MYCN subtype demonstrated the worst prognosis, with enrichment in cell growth and proliferation pathways. Conversely, the Neurogenic subtype showed the best prognosis, with enrichment in sympathetic nervous system development processes. Through single-cell RNA sequencing (scRNA-seq) analysis, we examined the tumor microenvironments of these distinct NB subtypes, revealing divergent differentiation trajectories for adrenergic cells within the MYCN and Neurogenic subtypes. We also identified a significant presence of naïve T cells in the MES subtype, as well as mesenchymal cell subtypes associated with the unique plasticity observed in both the MES and MYCN subtypes. Drug sensitivity prediction analysis suggested that the MES subtype may respond favorably to MEK inhibitors, while the MYCN subtype may be susceptible to Bcl-2 inhibitors. Our integrative multi-omics approach enabled precise stratification of NB into biologically distinct subtypes, potentially facilitating the development of subtype-specific therapeutic strategies for improved patient management and survival outcomes.