Context-aware single-cell multiomics approach identifies cell-type specific lung cancer susceptibility genes

Genome-wide association studies (GWAS) identified over fifty genomic loci associated with lung cancer risk. However, the genetic mechanisms and target genes underlying these loci are largely unknown, as most risk-associated-variants might regulate gene expression in a context-specific manner. Here, we generated a barcode-shared multiome (transcriptome and chromatin accessibility map) of 117,911 human lung cells from ever- and never-smokers to profile context-specific gene regulation. We observed that most of differentially expressed genes based on smoking status (smoking-responsive genes) were cell-type specific, and inter-cellular communication strength for Major Histocompatibility Complex-I and -II pathways were inverted between ever- and never-smokers. Accessible chromatin peak detection identified candidate cis-regulatory elements (cCREs) from each lung cell type, and 37% of them were cell-type specific. Colocalization of lung cancer candidate causal variants (CCVs) with these cCREs prioritized the variants for 68% of the GWAS loci, a subset of which was also supported by transcription factor footprinting. cCRE colocalization and single-cell based trait relevance score nominated epithelial and immune cells as the main cell groups contributing to lung cancer susceptibility. Notably, cCREs of rare epithelial cell types, including AT2-proliferating (0.13%) and basal cells (1.8%), overlapped with CCVs from multiple GWAS loci. A multi-level cCRE-gene linking system identified candidate susceptibility genes from 57% of lung cancer loci, including smoking-responsive genes. Our multiome dataset identified lung cancer susceptibility genes that were not detected in previous tissue- or cell-line-based approaches and further revealed the cell types and contexts where the susceptibility genes are functional, including the interplay of epithelial and immune cell types even in a single locus.