Molecular mechanisms and clinical insights of benzo[a]pyrene-related lung adenocarcinoma: New discoveries in multi-scale approaches

While the carcinogenicity of Benzo[a]pyrene (BaP) in lung adenocarcinoma (LUAD) is well-documented, the molecular mechanisms underlying BaP-driven tumorigenesis remain not fully clear. We first identified BaP-related prognostic genes for LUAD by analyzing online data and constructed prognostic models. Then diagnostic genes were screened from the aforementioned genes, and machine learning algorithms were employed to develop diagnostic models. Subsequently, single-cell and spatial transcriptomics were applied to characterize the cellular and spatial distribution of target genes, along with their gene co-localization. Molecular docking and dynamics were conducted to assess the binding affinities and stability between BaP and target proteins. In addition, we conducted some other analyses such as the correlation analysis between the expression of target genes (as well as the key genes of some pathways) and the patients' smoking status. During the construction of prognostic and diagnostic models, we identified five genes (SOD1, HK2, ACSS1, ANGPTL4, and CTBP2) that serve as core targets for BaP in the occurrence and progression of LUAD. Single-cell RNA sequencing and spatial transcriptomic analysis further validated these targets, and explained possible pathways how BaP causes LUAD, such as immunity and metabolism together with other analyses. Molecular docking and dynamics collectively revealed strong binding affinities and dynamic interactions between BaP and these targets, while the correlation analysis has also shown good results. Drug enrichment analysis highlighted tiopronin as promising therapeutic candidate for BaP-exposed populations. This study bridges BaP carcinogenesis and LUAD pathogenesis, offering translational insights for risk assessment, early diagnosis, and targeted therapy of BaP-related LUAD.