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Series GSE241468 Query DataSets for GSE241468
Status Public on Aug 14, 2024
Title Context-aware single-cell multiomics approach identifies cell-type specific lung cancer susceptibility genes
Organism Homo sapiens
Experiment type Expression profiling by high throughput sequencing
Genome binding/occupancy profiling by high throughput sequencing
Summary 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.
 
Contributor(s) Long E, Yin J, Kim EY, Choi J, Li B
Citation(s) 39266564
Submission date Aug 22, 2023
Last update date Oct 03, 2024
Contact name Jiyeon Choi
Organization name NCI
Street address 9615 Medical Center Drive, Rm 3116
City Rockville
State/province Maryland
ZIP/Postal code 20850
Country USA
 
Platforms (1)
GPL24676 Illumina NovaSeq 6000 (Homo sapiens)
Samples (32)
GSM7729446 Male, smoker, GEX, subject1
GSM7729447 Male, smoker, GEX, subject2
GSM7729448 Male, smoker, GEX, subject3
Relations
BioProject PRJNA1008237

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE241468_RAW.tar 72.1 Gb (http)(custom) TAR (of H5, TBI, TSV)
GSE241468_fragments_info.xlsx 12.7 Kb (ftp)(http) XLSX
GSE241468_sc-multiome-SeuratObj.rds.gz 9.9 Gb (ftp)(http) RDS
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file
Processed data are available on Series record

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