Lunit and Labcorp announced a collaborative initiative to accelerate innovation in digital pathology (DP) and artificial intelligence (AI) for oncology research and clinical care. The collaboration aims to leverage Labcorp's extensive clinical and pathology expertise alongside Lunit's cutting-edge AI algorithms to transform how tumor microen environments are analyzed and interpreted. By combining high-resolution whole-slide imaging with AI-powered spatial profiling, the collaboration seeks to generate new insights that can enhance biomarker discovery and guide precision immuno-oncology strategies.
The first outcome of the collaboration was showcased at two leading scientific conferences: Society for Immunotherapy of Cancer (SITC): Study demonstrated how AI-based spatial profiling and machine learning can identify immune-active subtypes of non-small cell lung cancer (NSCLC) tumors with the MET exon 14 skipping mutation, which are associated with improved immunotherapy outcomes. Using Lunit SCOPE IO®?, researchers analyzed more than 370 pathology slides to characterize immune phenotypes across different types of MET alterations, including exon 14 skipping, amplification, or no mutation (wildtype). Immune gene expression analysis further validated the AI-defined immune phenotypes and revealed key immune response pathways driving the inflamed phenotype, underscoring the predictive power of AI-based spatial profiling in MET-mutated NSCLC.
Association for Molecular Pathology (AMP): Study highlighted distinct tumor-immune microen environments linked to different MET alterations in NSCLC, revealing immune-desert phenotypes in MET-amplified tumors, andflamed phenotypes in those with MET exon 14 skipping tumors. Labcorp and Lunit plan to further broaden their collaboration by applying digital pathology AI to additional cancer types and genomic correlations.
