Spatially resolved multi-omics highlights cell-specific metabolic remodeling and interactions in gastric cancer

The spatial signature of metabolic remodeling in tumours remains to be explored. Here, the integration of mass spectrometry imaging-based spatial metabolomics and lipidomics with microarray-based spatial transcriptomics allows the visualisation of metabolic heterogeneity in gastric cancer. Mapping tumor metabolic remodeling and their spatial crosstalk with surrounding non-tumor cells can fundamentally improve our understanding of tumor biology, facilitates the designing of advanced therapeutic strategies. Here, we present an integration of mass spectrometry imaging-based spatial metabolomics and lipidomics with microarray-based spatial transcriptomics to hierarchically visualize the intratumor metabolic heterogeneity and cell metabolic interactions in same gastric cancer sample. Tumor-associated metabolic reprogramming is imaged at metabolic-transcriptional levels, and maker metabolites, lipids, genes are connected in metabolic pathways and colocalized in the heterogeneous cancer tissues. Integrated data from spatial multi-omics approaches coherently identify cell types and distributions within the complex tumor microenvironment, and an immune cell-dominated tumor-normal interface region where tumor cells contact adjacent tissues are characterized with distinct transcriptional signatures and significant immunometabolic alterations. Our approach for mapping tissue molecular architecture provides highly integrated picture of intratumor heterogeneity, and transform the understanding of cancer metabolism at systemic level.

Automated summary

This study explores the spatial signature of metabolic remodeling in gastric cancer by integrating mass spectrometry imaging-based spatial metabolomics and lipidomics with microarray-based spatial transcriptomics, allowing for the visualization of metabolic heterogeneity. Mapping tumor metabolic remodeling and its interaction with non-tumor cells improves our understanding of tumor biology and helps in designing advanced therapeutic strategies.