Beschreibung:
The role of homologous recombination deficiency (HRD) in lower grade glioma (LGG) has notbeen elucidated, and accurate prognostic prediction is also important for the treatment andmanagement of LGG. The aim of this study was to construct an HRD-based risk model and toexplore the immunological and molecular characteristics of this risk model. The HRD scorethreshold = 10 was determined from 506 LGG samples in The Cancer Genome Atlas cohortusing the best cut-off value, and patients with highHRDscores had worse overall survival. A totalof 251 HRD-related genes were identified by analyzing differentially expressed genes, 182 ofwhich were associated with survival. A risk score model based on HRD-related genes wasconstructed using univariate Cox regression, least absolute shrinkage and selection operatorregression, and stepwise regression, and patients were divided into high- and low-risk groupsusing the median risk score. High-risk patients had significantly worse overall survival than lowriskpatients. The risk model had excellent predictive performance for overall survival in LGG andwas found to be an independent risk factor. The prognostic value of the riskmodel was validatedusing an independent cohort. In addition, the risk score was associated with tumor mutationburden and immune cell infiltration in LGG. High-risk patients had higher HRD scores and “hot”tumor immune microenvironment, which could benefit from poly-ADP-ribose polymeraseinhibitors and immune checkpoint inhibitors. Overall, this big data study determined thethreshold of HRD score in LGG, identified HRD-related genes, developed a risk modelbased on HRD-related genes, and determined the molecular and immunologicalcharacteristics of the risk model. This provides potential new targets for future targetedtherapies and facilitates the development of individualized immunotherapy to improve prognosis.