Neuroblastoma (NB), the most prevalent extracranial solid tumour among children, is characterised by a high rate of metastasis.

The pathogenesis of NB with bone or bone marrow metastasis (NB-BBM) and its complex immune microenvironment remain poorly understood, posing challenges for effective risk prediction for BBM and limiting therapeutic strategies.

This research, published in the Genes & Diseases journal by a team from The Children's Hospital of Chongqing Medical University, highlights key genomic and single-cell transcriptomic alterations in NB-BBM, underscoring the significance of predictive pathology for NB-BBM and its role in understanding tumour onset, progression, and heterogeneity.

The researchers used a Swin-Transformer deep learning model to analyse 142 paraffin-embedded hematoxylin-eosin-stained tumour section images to predict NB-BBM occurrence, achieving a classification accuracy exceeding 85%.

In parallel, single-cell transcriptomics identified a tumour cell subpopulation (NB3) and two tumour-associated macrophage (TAM) subpopulations (SPP1⁺ TAMs and IGHM⁺ TAMs) closely associated with BBM progression.

Interestingly, findings reveal that oxidative phosphorylation (OXPHOS) also plays a crucial role in BBM development.

Additionally, this study highlighted transketolase (TKT) as a crucial metabolic molecule linked to BBM.

The researchers showed that the TKT gene was strongly associated with the clinical features of NB patients, especially in the BBM group.

Functional experiments validated TKT’s involvement in malignant behaviour, while pathway enrichment analysis showed correlations between high TKT expression and cell cycle activity.

Moreover, expression analysis of immune checkpoint genes CD274, LAG3, and TIGIT revealed their significant upregulation in NB-BBM, suggesting potential targets for antibody-based immunotherapies.

Furthermore, immunohistochemical validation demonstrated a pronounced expression of PD-L1 in NB-BBM, indicating its potential as a biomarker.

Although this research provides a predictive model for NB-BBM risk assessment, it has certain limitations, including the need for multicenter validation of the predictive model and prospective studies to confirm clinical utility.

Despite these challenges, this study offers a pathodiagnostic prediction for the risk of NB-BBM, enhances other imaging diagnoses, and elucidates the cellular heterogeneity of initial, progressive, and distant metastatic sites in NB.

Source: Compuscript Ltd