Dataset Information

Combined Therapy Sensitivity Index Based on a 13-Gene Signature Predicts Prognosis for IDH Wild-type and MGMT Promoter Unmethylated Glioblastoma Patients.

ABSTRACT: Glioblastoma (GBM) is one of the lethal tumors with poor prognosis. However, prognostic prediction approaches need to be further explored. Therefore, we developed an evaluation system that could be used for prognostic prediction of GBM patients. Published mRNA expression datasets from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and Chinese Glioma Genome Atlas (CGGA) were analyzed. Quantitative Realtime-PCR of signature genes and molecular aberrations of 178 Xiangya GBM patients were used for confirmation. Gene set enrichment analysis (GSEA) was performed for functional annotation. As a result, we established a 13-gene signature which named Combined Therapy Sensitivity Index (CTSI). Based on a cutoff point, we divided patients into high-risk group and low-risk group. Based on Kaplan-Meier analysis and multivariate Cox regression analysis, we found that patients in the high-risk group had a shorter overall survival time than patients in the low-risk group (p<0.001 in TCGA and CGGA datasets, p=0.047 in GSE4271 dataset, p=0.008 in Xiangya GBM cohort, HR: 1.65-3.42). By comparing the status of IDH mutation, TERT promoter mutation (TERTp-mut) and MGMT promoter methylation, CTSI was predictable in IDH wild-type (IDH-wt)/MGMT promoter unmethylated (MGMTp-unmeth) patients (p=0.037 in IDH-wt/TERTp-mut/MGMTp-unmeth subgroup, HR: 1.98; p=0.032 in IDH-wt/TERTp-wt/MGMTp-unmeth subgroup, HR: 2.09). Based on GESA, the Gene Ontology (GO) gene sets were enriched differently between CTSI high-risk and low-risk groups. Our results showed CTSI risk score can predict the prognosis of IDH-wt/MGMTp-unmeth GBM patients. Based on CTSI, combined with the status of IDH mutation, TERT promoter mutation and MGMT promoter methylation, a stepwise prognosis evaluation system which can provide precise prognosis prediction for GBM patients was established.

SUBMITTER: Ye N

PROVIDER: S-EPMC6775685 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Combined Therapy Sensitivity Index Based on a 13-Gene Signature Predicts Prognosis for IDH Wild-type and MGMT Promoter Unmethylated Glioblastoma Patients.

Ye Ningrong N Jiang Nian N Feng Chengyuan C Wang Feiyifan F Zhang Hanwen H Bai Harrusin Xiao HX Yang Li L Su Yandong Y Huang Chunhai C Wanggou Siyi S Li Xuejun X

Journal of Cancer 20190829 22

Glioblastoma (GBM) is one of the lethal tumors with poor prognosis. However, prognostic prediction approaches need to be further explored. Therefore, we developed an evaluation system that could be used for prognostic prediction of GBM patients. Published mRNA expression datasets from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and Chinese Glioma Genome Atlas (CGGA) were analyzed. Quantitative Realtime-PCR of signature genes and molecular aberrations of 178 Xiangya GBM patients ...[more]

PMID: 31632497

Similar Datasets

Project description:BackgroundThe potential benefit of risk stratification using a 4-miRNA signature in combination with MGMT promoter methylation in IDH1/2 wild-type glioblastoma patients was assessed.MethodsPrimary tumors from 102 patients with comparable treatment from the LMU Munich (n = 37), the University Hospital Düsseldorf (n = 33), and The Cancer Genome Atlas (n = 32) were included. Risk groups were built using expressions of hsa-let-7a-5p, hsa-let-7b-5p, hsa-miR-615-5p, and hsa-miR-125a-5p to assess prognostic performance in overall survival (OS). MGMT promoter methylation and age were considered as cofactors. Integrated miRNA, DNA methylome, and transcriptome analysis were used to explore the functional impact of signature miRNAs.ResultsThe 4-miRNA signature defined high-risk (n = 46, median OS: 15.8 months) and low-risk patients (n = 56, median OS: 20.7 months; univariable Cox proportional hazard analysis: hazard ratio [HR]: 1.8, 95% confidence interval [CI]: 1.14-2.83, P = .01). The multivariable Cox proportional hazard model including the 4-miRNA signature (P = .161), MGMT promoter methylation (P < .001), and age (P = .034) significantly predicted OS (Log-rank P < .0001). Likewise to clinical routine, analysis was performed for younger (≤60 years, n = 50, median OS: 20.2 months) and older patients (>60 years, n = 52, median OS: 15.8) separately. In younger patients, the 4-miRNA signature had prognostic value (HR: 1.92, 95% CI: 0.93-3.93, P = .076). Particularly, younger, MGMT methylated, 4-miRNA signature low-risk patients (n = 18, median OS: 37.4 months) showed significantly improved survival, compared to other younger patients (n = 32, OS 18.5 months; HR: 0.33, 95% CI: 0.15-0.71, P = .003). Integrated data analysis revealed 4-miRNA signature-associated genes and pathways.ConclusionThe prognostic 4-miRNA signature in combination with MGMT promoter methylation improved risk stratification with the potential for therapeutic substratification, especially of younger patients.

Project description:Glioblastoma (GBM) is the most malignant glioma, with a median overall survival (OS) of 14-16 months. Temozolomide (TMZ) is the first-line chemotherapy drug for glioma, but whether TMZ should be withheld from patients with GBMs that lack O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation is still under debate. DNA methylation profiling holds great promise for further stratifying the responses of MGMT promoter unmethylated GBMs to TMZ. In this study, we studied 147 TMZ-treated MGMT promoter unmethylated GBM, whose methylation information was obtained from the HumanMethylation27 (HM-27K) BeadChips (n = 107) and the HumanMethylation450 (HM-450K) BeadChips (n = 40) for training and validation, respectively. In the training set, we performed univariate Cox regression and identified that 3,565 CpGs were significantly associated with the OS of the TMZ-treated MGMT promoter unmethylated GBMs. Functional analysis indicated that the genes corresponding to these CpGs were enriched in the biological processes or pathways of mitochondrial translation, cell cycle, and DNA repair. Based on these CpGs, we developed a 31-CpGs methylation signature utilizing the least absolute shrinkage and selection operator (LASSO) Cox regression algorithm. In both training and validation datasets, the signature identified the TMZ-sensitive GBMs in the MGMT promoter unmethylated GBMs, and only the patients in the low-risk group appear to benefit from the TMZ treatment. Furthermore, these identified TMZ-sensitive MGMT promoter unmethylated GBMs have a similar OS when compared with the MGMT promoter methylated GBMs after TMZ treatment in both two datasets. Multivariate Cox regression demonstrated the independent prognostic value of the signature in TMZ-treated MGMT promoter unmethylated GBMs. Moreover, we also noticed that the hallmark of epithelial-mesenchymal transition, ECM related biological processes and pathways were highly enriched in the MGMT unmethylated GBMs with the high-risk score, indicating that enhanced ECM activities could be involved in the TMZ-resistance of GBM. In conclusion, our findings promote our understanding of the roles of DNA methylation in MGMT umethylated GBMs and offer a very promising TMZ-sensitivity predictive signature for these GBMs that could be tested prospectively.

Dataset Information

Combined Therapy Sensitivity Index Based on a 13-Gene Signature Predicts Prognosis for IDH Wild-type and MGMT Promoter Unmethylated Glioblastoma Patients.

Publications

Combined Therapy Sensitivity Index Based on a 13-Gene Signature Predicts Prognosis for IDH Wild-type and MGMT Promoter Unmethylated Glioblastoma Patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets