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.
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