Age-dependent differences in neuroblastoma microenvironment: integrative analysis of human and mouse single-cell RNA sequencing data
This research investigates the molecular basis of age-dependent outcome disparities in neuroblastoma, the most common extracranial solid tumor in children, where patients under 18 months show dramatically better survival rates than older children. We developed CellMentor, a novel supervised non-negative matrix factorization method that leverages labeled reference datasets to learn biologically meaningful latent spaces for single-cell RNA sequencing analysis. Using both mouse models and human patient data, we discovered age-specific differences in the tumor microenvironment, particularly in neutrophil populations that may contribute to better outcomes in younger patients. This work provides new computational tools and biological insights that could inform age-tailored therapeutic approaches for pediatric neuroblastoma.
