Spatial Multiomic Profiling Identifies Metabolic and Inflammatory Signatures Driving Recurrence in Adjuvant-Treated NSCLC

While there have been therapeutic advancements in treatments for non-small cell lung cancer (NSCLC), we have a limited understanding of how the tumour composition and spatial heterogeneity influences clinical outcomes. Here, we performed a multiomic analysis of 61 NSCLC patients treated with adjuvant chemotherapy and curative resection, integrating spatial transcriptomics, spatial proteomics, and deep learning to profile the tumour microenvironment (TME). We identified spatial-metabolic alterations associated with disease recurrence in and between cells in the TME, involving glutamine import, glycolytic, and lipid oxidation pathways. Based on protein expression, we found spatially distinct regions linked to tumour recurrence, implicating specific roles for tumour associated macrophages, metabolic pathways, and major histocompatibility complex (MHC) proteins. Moreover, transcriptomic analysis revealed histology-specific gene expression changes and metabolic and inflammation pathway associations with tumour recurrence. This comprehensive multiomic analysis highlights the complex immunological and metabolic dynamics characteristic of disease recurrence in adjuvant chemotherapy treated NSCLC.