Deciphering the metabolic landscape of MYCN non-amplified neuroblastoma through integrated multiomics

Despite its clinical importance, the metabolic landscape of MYCN nonamplified neuroblastoma (MYCN-NA NB) remains poorly defined. In this study, we performed integrated metabolic characterization of 22 NB samples by combining single-cell RNA sequencing (scRNA-seq) with proteomics and metabolomics. This was followed by multi-omics integration, two-way orthogonal partial least squares analysis, and biomarker selection using a random forest classifier. The scRNA-seq analysis of NB tumors revealed that, compared to the MYCN-amplified (MYCN-A) group, the MYCN-NA group exhibited higher proportions of T cells, monocytes, and neurons, while lipid metabolism pathways were specifically enriched. Proteomics identified 821 differentially expressed proteins [27 upregulated and 794 downregulated in the high-risk (HR) NB group], and functional analysis indicated that these proteins were primarily involved in biological processes such as the tricarboxylic acid cycle (TCA) and lipid metabolism. Metabolomics further detected 15 significantly altered metabolites associated with pathways such as linoleic acid metabolism. Integrated multiomics analysis identified key molecules, including RPL9 and POLR2G, with potentially critical roles in HR NB. Multi-omics correlation and network analyses revealed significant interactions between key proteins (RPL9 and POLR2G) and metabolites (D-ribose and 9-oxoODE). The biomarker combination determined by random forest and bidirectional orthogonal partial least squares modeling underscored the central role of oxidative lipid metabolism remodeling in high-risk disease progression. This study systematically elucidated the crucial role of lipid metabolic reprogramming in the pathogenesis of HR MYCN-NA NB. These findings provide critical insight for uncovering the mechanisms underlying NB progression and for identifying potential therapeutic targets.