Fig. 7: Validation of the prognostic four-gene signature for overall survival in the CGGA-LGG, TCGA-GBM and CGGA-GBM datasets. | Cell Death & Disease

Fig. 7: Validation of the prognostic four-gene signature for overall survival in the CGGA-LGG, TCGA-GBM and CGGA-GBM datasets.

From: DC vaccines loaded with glioma cells killed by photodynamic therapy induce Th17 anti-tumor immunity and provide a four-gene signature for glioma prognosis

Fig. 7: Validation of the prognostic four-gene signature for overall survival in the CGGA-LGG, TCGA-GBM and CGGA-GBM datasets.

A–E Characteristics of the four-gene prognostic signature in the validation CGGA-LGG dataset. A The low- and high-risk scores for each CGGA-LGG patient. B The time to death of patients (black, DEAD) and time until last follow-up of live patients (orange, ALIVE) from the CGGA-LGG dataset. C Heatmap of gene expression profiles of the four prognostic genes in the CGGA-LGG dataset. D Kaplan–Meier survival analysis of high-risk versus low-risk groups in the CGGA-LGG dataset. E Time-dependent receiver operating characteristic curve analysis of the four-gene predictive model in the CGGA-LGG dataset. F–J Characteristics of the four-gene prognostic signature in the validation CGGA-GBM dataset. F The low- and high-risk scores of each CGGA-GBM patient. G The time to death of dead patients (black, DEAD) and time until last follow-up of live patients (orange, ALIVE) from the CGGA-GBM dataset. H Heatmap of gene expression profiles of the four prognostic genes in the CGGA-GBM dataset. I Kaplan–Meier survival analysis of high-risk versus low-risk groups in the CGGA-GBM dataset. J Time-dependent receiver operating characteristic curve analysis of the four-gene predictive model in the CGGA-GBM dataset.

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