Exploring Potential Associations between Benzo[a]pyrene, Nicotine Exposure, and Lung Cancer: Molecular Insights, Prognostic Biomarkers, and Immune Cell Infiltration.
Study Goal
The researchers aimed to elucidate the molecular mechanisms and potential biomarkers associated with nicotine and BaP exposure in lung cancer patients.
Results Summary
The study identified 163 differentially expressed genes related to nicotine and BaP exposure, with CLDN5, DNASE1L3, and GPR37 being independent prognostic factors. High-risk patients showed poorer survival outcomes, and the genes were linked to immune responses, cell adhesion, and DNA methylation.
Population
Lung cancer patients with exposure to nicotine and BaP.
Effective Dosage
Not available
Duration
Not specified
Interactions
None mentioned
| Intervention | Direction | Endpoint | Population | Dosage | Impact | Claim # |
|---|---|---|---|---|---|---|
Benzo[a]pyrene (BaP) and nicotine exposure | increase | lung cancer development | - | - | have been implicated in | #1 |
Benzo[a]pyrene (BaP) and nicotine exposure | increase | 163 differentially expressed genes (DEGs) | lung cancer patients | - | associated with | #2 |
Benzo[a]pyrene (BaP) and nicotine exposure | increase | IL-17 signaling pathway | - | - | revealed significant | #3 |
Benzo[a]pyrene (BaP) and nicotine exposure | increase | cellular senescence pathway | - | - | revealed significant | #4 |
Benzo[a]pyrene (BaP) and nicotine exposure | increase | p53 signaling pathway | - | - | revealed significant | #5 |
Benzo[a]pyrene (BaP) and nicotine exposure | increase | 34 prognostic genes | - | - | identified | #6 |
CLDN5, DNASE1L3, and GPR37 | neutral | prognosis | - | - | being independent prognostic factors | #7 |
risk score model based on CLDN5, DNASE1L3, and GPR37 | increase | prognostic value | - | - | showed significant prognostic value | #8 |
high-risk patients | decrease | survival outcomes | high-risk patients | - | exhibiting poorer | #9 |
nomogram based on risk scores | increase | predictive accuracy and clinical utility | - | - | demonstrated good predictive accuracy and clinical utility | #10 |
high expression of CLDN5 | decrease | survival | - | - | correlated with poor | #11 |
high expression of GPR37 | decrease | survival | - | - | correlated with poor | #12 |
high DNASE1L3 expression | increase | survival | - | - | indicated better | #13 |
CLDN5, DNASE1L3, and GPR37 | increase | immune responses | - | - | linked to | #14 |
CLDN5, DNASE1L3, and GPR37 | increase | cell adhesion | - | - | linked to | #15 |
CLDN5, DNASE1L3, and GPR37 | increase | DNA methylation | - | - | linked to | #16 |
expression of CLDN5, DNASE1L3, and GPR37 | increase | infiltration of various immune cell types | - | - | revealed significant correlations with | #17 |
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.