Abstract
Despite receiving comprehensive treatment, the prognosis for low-grade gliomas (LGGs) patients varies considerably. Recent studies have focused extensively on ferroptosis, across a range of tumor types. Nevertheless, methodologies to evaluate the efficacy of radiotherapy for LGGs, from the perspective of ferroptosis-related genes (FRGs), remain strikingly rare. In this study, we conducted a retrospective study on the transcriptional profiles of LGG patients from the public databases and a local cohort. An FRG model was developed and validated, exhibits heightened robustness when contrasted with the traditional ssGSEA model. Patients demonstrating higher FRG scores were identified as a high-risk group, displaying a worse prognosis. By incorporating the FRG score alongside other prognosis-associated clinical indicators, we formulated an enhanced nomogram to achieve a higher level of prediction performance. Additionally, among LGG patients receiving radiotherapy, a poorer prognosis was observed in the high-risk group. Further investigation revealed that samples from the high-risk group generally exhibit a TME in an immuno-suppressive state. Collectively, we developed an FRG model and a robust nomogram for LGG prognostication. This study suggests that a high FRG score, indicative of an immunosuppressive TME, could potentially lead to a less favorable prognosis for certain LGG patients receiving radiotherapy.
Overview
- The study aims to investigate the prognosis of low-grade gliomas (LGGs) patients and the role of ferroptosis-related genes (FRGs) in this process. The study uses a retrospective approach, combining data from public databases and a local cohort. An FRG model is developed and validated, and patients with higher FRG scores are identified as a high-risk group with a worse prognosis. The study also develops an enhanced nomogram to improve prediction performance. The study investigates the impact of radiotherapy on LGG patients and finds that a poorer prognosis is observed in the high-risk group, which is associated with an immunosuppressive tumor microenvironment (TME).
- Comparative Analysis & Findings
Comparative Analysis & Findings
- The study compares the outcomes observed under different experimental conditions or interventions, specifically the FRG model and the traditional ssGSEA model. The FRG model exhibits heightened robustness and is more effective in predicting prognosis. The study also compares the outcomes of LGG patients receiving radiotherapy and finds that a poorer prognosis is observed in the high-risk group, which is associated with an immunosuppressive TME. The study identifies a significant difference in the prognosis of LGG patients based on the FRG score and the TME status. The study also finds that the FRG model and the nomogram are more effective in predicting prognosis than traditional clinical indicators alone. The study suggests that a high FRG score and an immunosuppressive TME could potentially lead to a less favorable prognosis for certain LGG patients receiving radiotherapy.
Implications and Future Directions