Geospatial immune variability illuminates differential evolution of lung adenocarcinoma

Remarkable progress in molecular analyses has improved our understanding of the evolution of cancer cells towards immune escape(1–5). However, the spatial configurations of immune and stromal cells, which may shed light on the evolution of immune escape across tumor geographical locations, remain unaddressed. We integrated multi-region exome and RNA-seq data with spatial histology mapped by deep learning in 100 non-small cell lung cancer (NSCLC) patients from the TRAcking Cancer Evolution through Therapy (Rx) (TRACERx) cohort(6). Cancer subclones derived from immune cold regions were more closely related in mutation space, diversifying more recently than subclones from immune hot regions. In TRACERx and in an independent multi-sample cohort of 970 lung adenocarcinoma (LUAD) patients, the number of immune cold regions significantly correlated with risk of relapse, independently of tumor size, stage and number of samples per patient. In LUAD, but not lung squamous cell carcinoma (LUSC), geometrical irregularity and complexity of the cancer-stromal cell interface significantly increased in tumor regions without disruption of antigen presentation. Decreased lymphocyte accumulation in adjacent stroma was observed in tumors with low clonal neoantigen burden. Collectively, immune geospatial variability elucidates tumor ecological constraints that may shape the emergence of immune evading subclones and aggressive clinical phenotypes.