科研之友
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摘要
-BACKGROUND: The efficacy of treatment of glioblas-toma multiforme (GBM) is limited. The effect of DNA damage repair is an important factor.-METHODS: Expression data were downloaded from The Cancer Genome Atlas (training dataset) and the Gene Expression Omnibus (validation dataset) databases. Uni-variate Cox regression analysis and the least absolute shrinkage and selection operator were used to construct a DNA damage response (DDR) gene signature. Receiver operating characteristic curve analysis and Kaplan-Meier curve analysis were used to estimate the prognostic value of the risk signature. Moreover, consensus clustering analysis was used to investigate the potential subtypes of GBM according to DDR expression.-RESULTS: We constructed a 3-DDRerelated gene signature through the survival analysis. The Kaplan-Meier curve analysis suggested that patients in the low-risk group have significantly better survival outcomes compared with the high-risk group in the training and external validation datasets. The results from the receiver operating characteristic curve analysis indicated that the risk model has high prognostic value in the training and external validation datasets. Moreover, 3 stable molecular subtypes were identified and validated in the Gene Expression Omnibus and The Cancer Genome Atlas data-bases according to the expression of the DNA repair gene. The microenvironment and immunity of GBM were further investigated and showed that cluster 2 had higher immu-n ity and a higher immune score compared with clusters 1 and 3.-CONCLUSIONS: The DNA damage repair-related gene signature was an independent and powerful prognostic biomarker in GBM. Knowledge of the GBM subtypes could have important implications in the subclassification of GBM.
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单位1; 哈尔滨医科大学
