An integrative spatial multi-omic workflow for unified analysis of tumor tissue

Combining molecular profiling with imaging techniques has advanced the field of spatial biology, offering new insights into complex biological processes. Focusing on diffuse IDH-mutated low-grade glioma, this study presents a workflow for Spatial Multi-omics Integration, SMINT, specifically combining spatial transcriptomics and spatial metabolomics. Our workflow incorporates both existing and custom-developed computational tools to enable cell segmentation and registration of spatial coordinates from both modalities to a common coordinate framework. During our investigation of cell segmentation strategies, we found that nuclei-only segmentation, while containing only 40% of segmented cell transcripts, enables accurate cell type annotation, but does not account for multinucleated cells. Our integrative workflow including cell-morphology segmentation identified distinct cellular neighborhoods at the infiltrating edge of gliomas, which were enriched in multinucleated and oligodendrocyte-lineage tumor cells, that may drive tumor invasion into the normal cortical layers of the brain.