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

• Published in: Nature communications Vol. 14; no. 1; p. 2692
• Main Authors: Sun, Chenglong, Wang, Anqiang, Zhou, Yanhe, Chen, Panpan, Wang, Xiangyi, Huang, Jianpeng, Gao, Jiamin, Wang, Xiao, Shu, Liebo, Lu, Jiawei, Dai, Wentao, Bu, Zhaode, Ji, Jiafu, He, Jiuming
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 10.05.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 140/58; 45/91; 631/45/320; 631/67/2327; 639/638/11/296; Cancer; DNA microarrays; Gastric cancer; Gene Expression Profiling; Heterogeneity; Humanities and Social Sciences; Humans; Immune system; Lipid metabolism; Lipids; Mapping; Mass Spectrometry; Mass spectroscopy; Medical imaging; Metabolic pathways; Metabolism; Metabolites; Metabolomics; Metabolomics - methods; Molecular structure; multidisciplinary; Multiomics; Science; Science (multidisciplinary); Scientific imaging; Stomach Neoplasms - genetics; Transcriptomics; Tumor cells; Tumor Microenvironment; Tumors
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-023-38360-5

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. 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.