Transcriptomic Analysis Identifies Acrolein Exposure-Related Pathways and Constructs a Prognostic Model in Oral Squamous Cell Carcinoma

TL;DR

This study explores how acrolein exposure affects oral cancer by identifying key genes and building a model to predict patient outcomes.

Contribution

The study introduces a novel prognostic model for oral squamous cell carcinoma based on acrolein-related genes.

Findings

Four key genes (PLK1, AURKA, CTLA4, PPARG) were identified as significant for the prognostic model.

The model showed strong predictive performance with AUC values of 0.72 at 1 year and 0.75 at 5 years.

High-risk patients correlated with a 'cold' immune microenvironment, indicating acrolein's role in immune modulation.

Abstract

Acrolein, a highly reactive environmental toxicant widely present in urban air and tobacco smoke, has been implicated in the development of multiple malignancies. In oral tissues, chronic acrolein exposure induces oxidative stress, inflammation, and genetic mutations, all of which are closely linked to the development of oral squamous cell carcinoma (OSCC). Although accumulating evidence indicates a strong association between acrolein exposure and OSCC, its prognostic significance remains poorly understood. In this study, we analyzed transcriptome data to identify differentially expressed genes (DEGs) between tumor and adjacent normal tissues, and screened acrolein-related candidates by intersecting DEGs with previously identified acrolein-associated gene sets. Functional alterations of these genes were assessed using Gene Set Variation Analysis (GSVA), and a protein–protein interaction (PPI) network was constructed to identify key regulatory genes. A prognostic model was developed using Support Vector Machine–Recursive Feature Elimination (SVM-RFE) combined with LASSO-Cox regression and validated in an independent external cohort. Among the acrolein-related DEGs, four key genes (PLK1, AURKA, CTLA4, and PPARG) were ultimately selected for model construction. Kaplan–Meier analysis showed significantly worse overall survival in the high-risk group (p < 0.0001). Receiver operating characteristic (ROC) curve analysis further confirmed the strong predictive performance of the model, with area under the curve (AUC) values of 0.72 at 1 year, 0.72 at 3 years, and 0.75 at 5 years. Furthermore, the high risk score was significantly correlated with a ‘cold’ immune microenviroment, suggesting that acrolein-related genes may modulate the tumor immune microenvironment. Collectively, these findings highlight the role of acrolein in OSCC progression, suggesting the importance of reducing acrolein exposure for cancer prevention and public health, and call for increased attention to the relationship between environmental toxicants and disease initiation, providing a scientific basis for public health interventions and cancer prevention strategies.

Figures