Integrating Lung Tissue-based Transcriptome-Wide Association Study with Single-cell RNA-sequencing Uncovers...

Area of Science:

• Genetics
• Oncology
• Bioinformatics

Background:

• Genome-wide association studies (GWASs) have identified numerous lung cancer loci, but causal genes remain largely unknown.
• Identifying these genes is crucial for understanding lung cancer development and for therapeutic advancements.

Purpose of the Study:

• To conduct a lung tissue-specific transcriptome-wide association study (TWAS) to identify novel lung cancer risk genes.
• To explore the biological mechanisms and potential therapeutic targets associated with these genes.

Main Methods:

• Constructed gene expression prediction models using normal lung tissue data (Vanderbilt Thoracic Biorepository and GTEx).
• Applied these models to a large lung cancer GWAS meta-analysis (55,174 cases, 1,294,174 controls).
• Performed smoking-conditional analysis, cell-type-specific colocalization, Mendelian randomization, and in vitro functional validation.

Main Results:

• Identified 109 unique lung cancer risk genes, with 71 being novel discoveries and 13 in novel loci.
• Discovered 52 genes unrelated to smoking behavior and identified cell-type-specific colocalization for seven genes.
• Found 17 genes targeted by 58 drugs and validated three genes through in vitro experiments.

Conclusions:

• This TWAS identified novel candidate risk genes for lung cancer and its subtypes.
• The findings provide insights into lung cancer biology, including smoking-independent pathways and cell-type specificities.
• The study highlights potential causal genes with translational utility for drug development and therapeutic strategies.