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Fig. 5 | Cancer Cell International

Fig. 5

From: Cell senescence-associated genes predict the malignant characteristics of glioblastoma

Fig. 5

Constructing risk score models. A Weighted gene co-expression network analysis (WGCNA) based on gene expression data identified gene modules with highly synergistic changes. B The heatmap of module-trait relationships. (C) Univariate Cox regression analysis of 228 genes relevant to GBM prognosis. D The least absolute shrinkage and selection operator (LASSO) method of cell senescence-associated genes. E The multivariate Cox regression analysis ultimately found 11 gene sets associated with prognosis to construct risk score. (F) Kaplan–Meier curves of the train set (P < 0.001, log-rank test) and test set (P = 0.0053, log-rank test). G Time-dependent receiver operating characteristics (ROC) of trainset and test set. H Correlations between survival status and risk score and gene expression status and risk score

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