A Risk Model Developed Based on Homologous Recombination Deficiency Predicts Overall Survival in Patients With Lower Grade Glioma - Peng, Hao; Wang, Yibiao; Wang, Pengcheng; Huang, Chuixue; Liu, Zhaohui; Wu, Changwu (Frontiers in Genetics, 2022)
The role of homologous recombination deficiency (HRD) in lower grade glioma (LGG) has not been elucidated, and accurate prognostic prediction is also important for the treatment and management of LGG. This study aimed to determine the threshold of HRD score of LGG, identify HRD-related genes and construct a risk model. The HRD score threshold = 10 was determined from 506 LGG samples in The Cancer Genome Atlas (TCGA) cohort using the best cut-off value, and patients with high HRD scores had worse OS. A total of 251 HRD-related genes were identified by analyzing differentially expressed genes, 182 of which were associated with survival. A risk score model based on HRD-related genes was constructed using univariate Cox regression, LASSO regression, and stepwise regression, and patients were divided into high- and low-risk groups using the median risk score. High-risk patients had significantly worse OS than low-risk patients. The risk model had excellent predictive performance for OS in LGG and was found to be an independent risk factor. The prognostic value of the risk model was validated using an independent cohort. In addition, the risk score was associated with tumor mutation burden and immune cell infiltration in LGG. High-risk patients had higher HRD scores and “hot” tumor microenvironment, which could benefit from poly-ADP-ribose polymerase inhibitors and immune checkpoint inhibitors. Overall, this big data study determined the threshold of HRD score in LGG, identified HRD-related genes, developed a risk model based on HRD-related genes, and determined the molecular and immunological characteristics of the risk model. This provides potential new targets for future targeted therapies and facilitates the development of individualized immunotherapy to improve prognosis.