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. Overall design: Tumor-distant normal lung tissues from smokers and never-smokers were dissociated into single-cell suspension and analyzed using 10X Genomics multiome kit to perform single-nuclear RNAseq and single-nuclear ATACseq from the same single cell. A total of 16 samples (8 from smokers and 8 from never-smokers) were analyzed. The main goal of the study was to perform peak-gene linkage in normal lung tissues to identify cell-type-specific cis-regulatory elements and their target gene. Smoking effect on differential gene expression of lung cells were also assessed. Please note that each processed data h5 file was generated from both GEX and ATAC samples, and is linked to the corresponding GEX sample records. UPDATES [Jan-24-2025] The GSE241468_sc-multiome-SeuratObj.rds file was removed because it had errors. [Feb-21-2025] The errors in the GSE241468_sc-multiome-SeuratObj.rds were corrected. The revised file is GSE241468_share_seur.rds.