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DC vaccines loaded with glioma killed by photodynamic therapy induce Th17 anti-tumor immunity and provide a 4-gene signature for glioma prognosis

ABSTRACT: DC vaccines loaded with glioma killed by photodynamic therapy induce Th17 anti-tumor immunity and provide a 4-gene signature for glioma prognosis

PROVIDER: PRJNA902288 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR22309916_1.fastq.gz	Fastqsanger.gz
	SRR22309916_2.fastq.gz	Fastqsanger.gz
	SRR22309917_1.fastq.gz	Fastqsanger.gz
	SRR22309917_2.fastq.gz	Fastqsanger.gz
	SRR22309918_1.fastq.gz	Fastqsanger.gz

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Project description:Gliomas are the most frequent type of primary tumor of the central nervous system in adults with significant morbidity and mortality. Despite the development of novel, complex, multidisciplinary, and targeted therapies, glioma therapy has not progressed much over the last decades. Therefore, there is an urgent need to develop novel patient-adjusted immunotherapies that actively stimulate antitumor T cells generating long-term memory and thus resulting in significant clinical benefits. This work aimed to investigate the efficacy and molecular mechanism of dendritic cell (DC) vaccines loaded with glioma cells undergoing immunogenic cell death (ICD) induced by photosens based photodynamic therapy (PS-PDT) and to identify reliable prognostic genes’ signatures for predicting patients’ overall survival (OS). The analysis of the transcriptional program of the ICD-based DC vaccine led to the identification of robust induction of Th17 signature when used as a vaccine, these DCs demonstrate retinoic acid receptor-related orphan receptor-γt dependent efficacy in orthotopic mouse model. Moreover, by comparative analysis of transcriptome program of the ICD-based DC vaccine with transcriptome data from the TCGA-low grade glioma (LGG) dataset the four-gene signature (CFH, GALNT3, SMC4, VAV3) associated with OS of glioma patients have been identified. This model has been validated on OS of CGGA-LGG, TCGA-glioblastoma multiforme (GBM) and CGGA-GBM datasets to determine whether it has a similar prognostic value. For this the sensitivity and specificity of the prognostic model for predicting the OS were evaluated by calculating the area under curve (AUC) of the time-dependent receiver operating characteristic (ROC) curve. The values of AUC for TCGA-LGG, CGGA-LGG, TCGA-GBM and CGGA-GBM were, respectively, 0.75, 0.73, 0.9 and 0.69 for predicting 5-year survival rates. These data open attractive prospects for improving glioma therapy by employing ICD and PS-PDT-based DC vaccines to induce Th17 immunity and to use this prognostic model to predict the OS of glioma patients.

Project description:Gliomas, the most frequent type of primary tumor of the central nervous system in adults, results in significant morbidity and mortality. Despite the development of novel, complex, multidisciplinary, and targeted therapies, glioma therapy has not progressed much over the last decades. Therefore, there is an urgent need to develop novel patient-adjusted immunotherapies that actively stimulate antitumor T cells, generate long-term memory, and result in significant clinical benefits. This work aimed to investigate the efficacy and molecular mechanism of dendritic cell (DC) vaccines loaded with glioma cells undergoing immunogenic cell death (ICD) induced by photosens-based photodynamic therapy (PS-PDT) and to identify reliable prognostic gene signatures for predicting the overall survival of patients. Analysis of the transcriptional program of the ICD-based DC vaccine led to the identification of robust induction of Th17 signature when used as a vaccine. These DCs demonstrate retinoic acid receptor-related orphan receptor-γt dependent efficacy in an orthotopic mouse model. Moreover, comparative analysis of the transcriptome program of the ICD-based DC vaccine with transcriptome data from the TCGA-LGG dataset identified a four-gene signature (CFH, GALNT3, SMC4, VAV3) associated with overall survival of glioma patients. This model was validated on overall survival of CGGA-LGG, TCGA-GBM, and CGGA-GBM datasets to determine whether it has a similar prognostic value. To that end, the sensitivity and specificity of the prognostic model for predicting overall survival were evaluated by calculating the area under the curve of the time-dependent receiver operating characteristic curve. The values of area under the curve for TCGA-LGG, CGGA-LGG, TCGA-GBM, and CGGA-GBM for predicting five-year survival rates were, respectively, 0.75, 0.73, 0.9, and 0.69. These data open attractive prospects for improving glioma therapy by employing ICD and PS-PDT-based DC vaccines to induce Th17 immunity and to use this prognostic model to predict the overall survival of glioma patients.

Dataset Information

DC vaccines loaded with glioma killed by photodynamic therapy induce Th17 anti-tumor immunity and provide a 4-gene signature for glioma prognosis

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