EXPLORING THE RELATIONSHIP BETWEEN M6A RNA METHYLATION REGULATORS, TUMOR MUTATION BURDEN, AND ESOPHAGEAL CANCER: IMPLICATIONS FOR ATHLETE HEALTH

Abstract

Objective: This study aims to develop a prognostic model for esophageal cancer (ESCA) utilizing m6A RNA methylation status and tumor mutational burden (TMB), examining their implications for athlete health, especially considering the increased risk factors associated with high-performance sports. Methods: We utilized transcriptomic and clinical profiles from ESCA patients in the TCGA database. Patients were stratified into high-TMB and low-TMB groups based on m6A RNA methylation regulator expression and TMB scores. We employed gene set enrichment analysis (GSEA) to identify pathways significantly enriched across the groups. The dataset was then split into training and test sets to develop and validate an m6A score signature model. Patients were further divided into high- and low-risk categories based on median m6A risk scores, forming H-TMB-H-risk and L-TMB-L-risk groups for deeper analysis. Results: GSEA revealed distinct immune cell enrichment between clusters. Six m6A regulatory genes (LRPPRC, FMR1, HNRNPA2B1, IGF2BP2, YTHDF2, and ALKBH5) were utilized to establish a prognostic signature. This model, validated using a test dataset, effectively segregated patients into risk-specific groups correlated with overall survival (OS), immune cell infiltration, tumor immune dysfunction and exclusion (TIDE), and microsatellite instability (MSI) scores. Notably, the combined m6A and TMB score model provided significant prognostic insights and predicted responses to immunotherapy. Conclusion: Our findings indicate that the integrated model of m6A and TMB scores offers a robust prognostic tool for ESCA, with potential applications in predicting immunotherapy outcomes. For athletes, particularly those who might be predisposed to health risks due to their intense physical regimes, such a model can be instrumental in early detection and personalized management of ESCA, enhancing both treatment outcomes and quality of life. This research underscores the importance of molecular profiling in advancing personalized medicine in sports health management.