GSE172184
Remodeled single-cell landscape in the metastatic bone marrow in human neuroblastoma unraveled by multi-omics and deep multiplex imaging
Single-cell assessment of bone marrow metastases is essential to decipher the entire spectrum of tumor heterogeneity in solid cancers with bone marrow involvement. We used multi-epitope-ligand cartography (MELC) to spatially profile 20 biomarkers in 35,000 disseminated tumor cells (DTCs), hematopoietic and mesenchymal cells from eight neuroblastoma bone marrow metastases. We developed DeepFLEX, a single-cell image analysis pipeline for MELC data that combines deep learning-based cell and nucleus segmentation and overcomes frequent challenges of multiplex imaging methods. Comparisons of cell type proportions between samples indicated that microenvironmental changes in the bone marrow are associated with tumor cell infiltration and therapy response. Hierarchical clustering of DTCs revealed multiple phenotypes with highly diverse expression of markers such as FAIM2, which we propose as a complementary marker to capture DTC heterogeneity in neuroblastoma. This single-cell atlas is an important step towards a deeper understanding of DTCs and their interactions with the bone marrow niche. Overall design: mRNA of 38 samples was sequenced and analysed. Some of the RNA-Seq Samples are also available in GEO Series GSE94035.