Nucleai has announced its contribution to a collaborative international study published in Nature Communications exploring how the spatial organization and metabolic characteristics of tumor cells are associated with response and resistance to immunotherapy in non-small cell lung cancer (NSCLC). Led by researchers at The University of Queensland and Yale School of Medicine, the study applied multiplex immunofluorescence (mIF) and computational approaches to analyze tumor tissue at single-cell resolution. Nucleai’s AI-powered mIF analysis pipeline enabled the accurate identification and classification of tumor and immune cell populations, revealing distinct spatial and metabolic patterns linked to immunotherapy outcomes. By transforming complex imaging data into structured insights, the platform provided a reproducible foundation for examining how cellular positioning and glucose use predict patient benefit, further advancing the discovery of predictive spatial biomarkers in precision oncology.
