INTRODUCTION: Lung cancer (LC) has the highest cancer-related mortality rate. Even though genome-wide association studies (GWAS) have identified numerous loci linked to LC risk, the underlying causal genes and biological processes are still mostly unknown. METHODS: The LC GWAS summary data comprised 29,863 cases and 55,586 controls of European ancestry. The weight file and related files of plasma protein, multi-tissue, and single-cell were obtained from Zhang's study, Mancuso lab, and Thompson's study, respectively. We conducted transcriptome association studies (TWAS) employing functional Summary-based Imputation (FUSION) from two levels, which were multiple tissues and single cell. We conducted proteome-wide association studies (PWAS) from plasma protein. Conditional and joint (COJO) analysis and multi-marker analysis of genomic annotation (MAGMA) analysis were used to further screen the PWAS/TWAS results. Summary-data-based Mendelian randomization (SMR) and colocalization analysis were utilized to explain the causal association between variables and results. RESULTS: A total of 13, 251, and 16 genes were calculated from the three dimensions, which were plasma protein, multiple tissues, and single cell, respectively. RNASET2 and IREB2 were obtained through intersecting these three sets of genes. COJO analysis and MAGMA analysis were replicated the two genes successfully. Then, RNASET2 was replicated in both eQTL-SMR and mQTL-SMR and following colocalization analysis. CONCLUSION: In summary, we conducted a multi-omic studies, which integrated three levels to investigate the novel targets for LC. Through a series of verifications, RNASET2 was identified as the key gene for LC in the current research.