Nature Communications (Sep 2024)

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

  • Erping Long,
  • Jinhu Yin,
  • Ju Hye Shin,
  • Yuyan Li,
  • Bolun Li,
  • Alexander Kane,
  • Harsh Patel,
  • Xinti Sun,
  • Cong Wang,
  • Thong Luong,
  • Jun Xia,
  • Younghun Han,
  • Jinyoung Byun,
  • Tongwu Zhang,
  • Wei Zhao,
  • Maria Teresa Landi,
  • Nathaniel Rothman,
  • Qing Lan,
  • Yoon Soo Chang,
  • Fulong Yu,
  • Christopher I. Amos,
  • Jianxin Shi,
  • Jin Gu Lee,
  • Eun Young Kim,
  • Jiyeon Choi

DOI
https://doi.org/10.1038/s41467-024-52356-9
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 16

Abstract

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Abstract Genome-wide association studies (GWAS) identified over fifty loci associated with lung cancer risk. However, underlying mechanisms and target genes are largely unknown, as most risk-associated variants might regulate gene expression in a context-specific manner. Here, we generate a barcode-shared transcriptome and chromatin accessibility map of 117,911 human lung cells from age/sex-matched ever- and never-smokers to profile context-specific gene regulation. Identified candidate cis-regulatory elements (cCREs) are largely cell type-specific, with 37% detected in one cell type. Colocalization of lung cancer candidate causal variants (CCVs) with these cCREs combined with transcription factor footprinting prioritize the variants for 68% of the GWAS loci. CCV-colocalization and trait relevance score indicate that epithelial and immune cell categories, including rare cell types, contribute to lung cancer susceptibility the most. A multi-level cCRE-gene linking system identifies candidate susceptibility genes from 57% of the loci, where most loci display cell-category-specific target genes, suggesting context-specific susceptibility gene function.