Abstract
DNA damage repair (DDR) related genes are associated with the development, progression, aggressiveness, and heterogeneity of low-grade gliomas (LGG). However, the precise role of DDR in LGG prognosis and molecular subtypes remains to be elucidated. We analyzed 477 and 594 LGG samples from the Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) to develop a prognostic model using the random forest algorithm and Cox regression. Independent prognostic factors were incorporated into a nomogram, and its performance was assessed using receiver operating characteristic and calibration curves. We also used Connectivity Map analysis to identify potential small molecule drugs targeting DDR. Molecular subtypes based on DDR were identified by consensus cluster analysis, and the clinical characteristics, mutation landscape, immune tumor microenvironment, and drug sensitivity of patients with different subtypes in the TCGA and CGGA datasets were further compared. The Boruta algorithm was used to select features from the differentially expressed genes between clusters to generate DDR scores. Results were further validated in the Glioma Longitudinal AnalySiS consortium dataset. Statistical analysis and tests were implemented using R software version 4.0.2. We developed a prognostic model containing six DDR-related genes, which served as a potential independent prognostic indicator in LGG across three datasets. The area under the curve (AUC) values for 1-, 3-, and 5-year survival in the TCGA dataset were 0.901, 0.832, and 0.771, respectively. The nomogram demonstrated high accuracy in predicting 1-, 3-, and 5-year survival, with AUC values greater than 0.8. Additionally, we identified and validated two molecular subtypes based on DDR genes. These subtypes exhibited significant differences in somatic mutations, clinical prognosis, and immune cell infiltration. One subtype showed higher immune and stromal scores, worse prognosis, and increased sensitivity to common chemotherapeutic agents. Finally, we established a DDR score which served as another promising prognostic predictor for LGG. The prognostic model and molecular subtypes based on DDR genes can help in more detailed classification and provide insights for personalized management of LGG and clinical drug development.
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