Developing a prognostic stratification model based on glutathione metabolism in thyroid cancer and validating RRM2's tumor-promoting role.

Introduction: Glutathione (GSH), the most abundant antioxidant in cells, acts as free radical scavenger and detoxifying agent. Elevation of GSH metabolism protects tumor from damage of oxidant and even promotes tumor progression. However, the clinical value of GSH metabolism in thyroid cancer (THCA) remained largely unknown. Methods: The expression and prognostic value of GSH metabolism-related enzymes were first investigated using a large The Cancer Genome Atlas (TCGA) cohort of 510 THCA patients. To expand the prognostic application, a risk stratification model based on these enzymes was developed using the LASSO Cox regression algorithm. Patients were categorized into high- and low-risk groups based on the median risk score, and the model's predictive performance for disease-freesurvival (DFS) was validated. Further correlation analysis, pan-cancer analysis (using TCGA and GTEx data), and detailed analysis across pathological types and TNM stages were performed to identify and characterize key molecules, such as RRM2. Finally, the biological role of Results: The majority of GSH metabolism-related enzymes were significantly upregulated in THCA tumor tissues and their expression was negatively associated with DFS. The LASSO Cox model stratified patients into high-risk and low-risk groups with significantly different DFS. High-risk status was also positively correlated with increased infiltration of naïve B cells, activated memory CD4+ T cells, helper T cells and regulatory T cells. Discussion: GSH metabolism-related enzymes are upregulated in THCA and associate with a worse prognosis and an immune landscape suggestive of antigenic stimulation coupled with immunosuppression.