IMPACT OF A GLYCOLYSIS-RELATED 5-GENE SIGNATURE ON ATHLETIC HEALTH: CORRELATIONS WITH GASTRIC CANCER PROGNOSIS AND IMMUNE SYSTEM RESPONSES IN ATHLETES

Abstract

Background: Gastric cancer (GC) remains a significant global health challenge, with its metabolic processes, particularly glycolysis, playing a crucial role in its pathogenesis. Understanding glycolysis at the genetic level can provide insights into general metabolic health, which is essential for optimizing athletic performance and recovery. This study aims to develop a glycolysis-based gene signature that can be potentially useful in evaluating the metabolic health of athletes. Method: We identified differentially expressed genes associated with glycolysis in stomach adenocarcinoma (STAD) using univariate Cox and LASSO analyses to establish a risk score. The effectiveness of this gene signature was assessed by the area under the curves (AUCs) of the receiver operator characteristic (ROC) curves. Further, we analyzed RNA-Seq data from high- and low-glycolysis groups of STAD patients to explore immune cell infiltration's relationship with glycolysis using the CIBERSORT algorithm and Spearman correlation. Results: We constructed a five-gene signature comprising Syndecan 2 (SDC2), Versican (VCAN), Malic Enzyme 1 (ME1), Pyruvate Carboxylase (PC), and SRY-Box Transcription Factor 9 (SOX9). Patients were categorized into high and low glycolysis groups based on their risk scores, with high-glycolysis patients demonstrating poorer overall health metrics, which could imply compromised recovery and performance in athletes. The gene signature displayed adequate sensitivity and specificity in predicting health outcomes, indicated by ROC curves. Multi-omics analysis revealed significant differences in immune cell infiltration between different glycolysis statuses, suggesting potential impacts on inflammation and immune responses in athletes. Conclusion: The glycolysis-related gene signature provides valuable insights into metabolic health, which is pivotal for athlete performance and recovery. While originally developed for prognostic evaluation in GC patients, this signature also offers a novel approach to monitoring and potentially enhancing metabolic efficiency in athletic populations, highlighting the need for further research into its application in sports and health sciences.