Work

Construction and validation of a disulfidptosis-related risk assessment model for prediction of prognosis, immune microenvironment, drug therapy, and microbiota in patients with low-grade glioma

Year: 2025

Type: article

Abstract: BACKGROUND: Disulfidptosis has been recently identified as a mode of programmed cell death, which is becoming a promising target for tumor treatment. However, its biological mechanism in low-grade glioma (LGG) has not yet been thoroughly investigated. Due to the molecular heterogeneity of LGG, it is essential to develop an accurate classification system to predict prognosis and therapeutic response of LGG patients based on distinct molecular characteristics. METHODS AND RESULTS: A prognostic gene signature was constructed based on differentially expressed genes between disulfidptosis-related genes-specified subtypes, which was verified to have superior prognostic performance. According to it, high-risk patients with poor prognosis were more enriched with immune cells, including CD4 + , CD8 + , and regulatory T cells. Through drug sensitivity analysis, several drugs exhibited significant correlation with risk score, and molecular docking illustrated that both dactolisib and linsitinib were capable of binding tightly with most signature genes, making them potential candidates for targeted therapeutic approaches of LGG. Additionally, this model was also found to be significantly associated with tumor mutation burden, stemness index, treatment response, and microbiota features. CONCLUSION: Thus, this model can stratify LGG patients with distinct gene expression features, immune landscape, genomic instability, and microbiota features. By stratifying patients with risk score, this risk model may improve the accuracy of prognostic prediction for LGG patients, which might provide new insights into the molecular targeted therapy for individual treatment in a risk score-specific manner.

Source: International Journal of Surgery

DOI: 10.1097/js9.0000000000003921