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Abstract This study explores migrasomes' role in neuroblastoma, a common malignant tumor in children, and their potential impact on tumor formation. We analyzed neuroblastoma RNA-seq datasets from public databases, including GSE62564, GSE181559, target, and fwr144. Through data normalization and unsupervised classification using migrasome-specific molecular markers, Differentially Expressed Genes were identified, followed by functional enrichment analysis. Our novel migrasome-associated machine learning model, MigScore, was developed using ten algorithms and 101 combinations, validated on two single-cell datasets. This enabled immune infiltration assessment and drug compatibility prediction, highlighting the utility of MS275, a histone deacetylase inhibitor. Results showed a significant inverse relationship between MigScore and favorable clinical outcomes, elucidating the link between migrasome pathways and tumor immunogenicity. These findings suggest that migrasomes are crucial in neuroblastoma prognosis, leading to the possibility of personalized treatment strategies and improved outcomes.

BackgroundNeuroblastoma (NB), characterized by its marked heterogeneity, is the most common extracranial solid tumor in children. The status and functionality of mitochondria are crucial in regulating NB cell behavior. While the significance of mitochondria-related genes (MRGs) in NB is still missing in key knowledge.Materials and methodsThis study leverages consensus clustering and machine learning algorithms to construct and validate an MRGs-related signature in NB. Single-cell data analysis and experimental validation were employed to characterize the pivotal role of FEN1 within NB cells.ResultsMRGs facilitated the classification of NB patients into 2 distinct clusters with considerable differences. The constructed MRGs-related signature and its quantitative indicators, mtScore and mtRisk, effectively characterize the MRGs-related patient clusters. Notably, the MRGs-related signature outperformed MYCN in predicting NB patient prognosis and was adept at representing the tumor microenvironment (TME), tumor cell stemness, and sensitivity to the chemotherapeutic agents Cisplatin, Topotecan, and Irinotecan. FEN1, identified as the most contributory gene within the MRGs-related signature, was found to play a crucial role in the communication between NB cells and the TME, and in the developmental trajectory of NB cells. Experimental validations confirmed FEN1’s significant influence on NB cell proliferation, apoptosis, cell cycle, and invasiveness.ConclusionThe MRGs-related signature developed in this study offers a novel predictive tool for assessing NB patient prognosis, immune infiltration, stemness, and chemotherapeutic sensitivity. Our findings unveil the critical function of FEN1 in NB, suggesting its potential as a therapeutic target.