Exploring Potential Associations between Benzo[a]pyrene, Nicotine Exposure, and Lung Cancer: Molecular Insights, Prognostic Biomarkers, and Immune Cell Infiltration.

Abstract

Benzo[a]pyrene (BaP) and nicotine exposure have been implicated in lung cancer development. This study aims to elucidate the molecular mechanisms and potential biomarkers associated with this exposure in lung cancer patients. We integrated gene expression data from The Cancer Genome Atlas lung cancer cohort and the Comparative Toxicogenomics Database to identify differentially expressed genes (DEGs) associated with BaP and nicotine exposure. Enrichment analyses, survival analyses, and immune cell infiltration analyses were conducted to interpret the biological significance of these DEGs. A risk score model and a nomogram were constructed for a prognostic evaluation. We identified 163 DEGs related to BaP and nicotine exposure in lung cancer. Enrichment analysis revealed significant biological processes and pathways, including "IL-17 signaling", "cellular senescence", and "p53 signaling". From the DEGs, 34 prognostic genes were identified, with CLDN5, DNASE1L3, and GPR37 being independent prognostic factors. A risk score model based on these genes showed significant prognostic value, with high-risk patients exhibiting poorer survival outcomes. Additionally, a nomogram based on these risk scores demonstrated good predictive accuracy and clinical utility. Kaplan-Meier analyses confirmed that high expression of CLDN5 and GPR37 correlated with poor survival, while high DNASE1L3 expression indicated better survival. Single-gene enrichment analyses linked these genes to immune responses, cell adhesion, and DNA methylation. Immune cell infiltration analysis revealed significant correlations between the expression of these genes and the infiltration of various immune cell types. Our findings highlight the significant role of CLDN5, DNASE1L3, and GPR37 in lung cancer associated with BaP and nicotine exposure. The constructed risk score model and nomogram provide valuable tools for prognostication, and the identified genes offer potential targets for therapeutic intervention. Understanding the influence of toxic exposure on the tumor-immune microenvironment can guide future research and treatment strategies.