Population analysis uncovers genetic variation implications for lung cancer risk in smokers, suggesting a role for immunogenetics and environmental factors.
Description (Wilson* et al Science 2024 & unpublished work ) Cancer risk is modulated by a complex network of inherited mutations, DNA replication errors, and environmental exposures. Yet, the impact of genetic variation in the immunosurveillance of nascent and established malignancies remains uncertain. Using population-scale data from the UK Biobank and FinnGen, we uncover a striking association between HLA allelic-associated peptidome diversity and reduced lung cancer risk in smokers. Fine-mapping reveals that amino acid heterozygosity in the HLA-II peptide-binding groove significantly contributes to this protective effect. Single-cell analyses further demonstrate that smoking induces proinflammatory lung macrophages and HLA-II+ epithelial cells, emphasizing a dynamic immune-environment interaction. Furthermore, we identify widespread loss of HLA-II heterozygosity (LOH) in lung cancer, favoring alleles with expanded neopeptide repertoires, alongside distinct LOH patterns for HLA-I and HLA-II across cancer types. Building on these insights, we introduce a novel biophysically informed embedding space, developed with state-of-the-art large language models, to represent HLA allelic similarity as a continuous variable. This framework enables precise quantification of risk across diverse cancers. Together, our findings position genetic variation in immunosurveillance as a pivotal determinant of cancer risk, offering new avenues for predictive modeling and therapeutic innovation. Funding Sources US NIH grant R01 CA283469 Alexander and Alexandrine Sinsheimer Foundation Topic Categories Tumor Immunology: Checkpoints, Prevention, and Treatment (TIPT)
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