Dataset Information

DGKI methylation status modulates the prognostic value of MGMT in glioblastoma patients treated with combined radio-chemotherapy with temozolomide.

ABSTRACT:

Background

Consistently reported prognostic factors for glioblastoma (GBM) are age, extent of surgery, performance status, IDH1 mutational status, and MGMT promoter methylation status. We aimed to integrate biological and clinical prognostic factors into a nomogram intended to predict the survival time of an individual GBM patient treated with a standard regimen. In a previous study we showed that the methylation status of the DGKI promoter identified patients with MGMT-methylated tumors that responded poorly to the standard regimen. We further evaluated the potential prognostic value of DGKI methylation status.

Methods

399 patients with newly diagnosed GBM and treated with a standard regimen were retrospectively included in this study. Survival modelling was performed on two patient populations: intention-to-treat population of all included patients (population 1) and MGMT-methylated patients (population 2). Cox proportional hazard models were fitted to identify the main prognostic factors. A nomogram was developed for population 1. The prognostic value of DGKI promoter methylation status was evaluated on population 1 and population 2.

Results

The nomogram-based stratification of the cohort identified two risk groups (high/low) with significantly different median survival. We validated the prognostic value of DGKI methylation status for MGMT-methylated patients. We also demonstrated that the DGKI methylation status identified 22% of poorly responding patients in the low-risk group defined by the nomogram.

Conclusions

Our results improve the conventional MGMT stratification of GBM patients receiving standard treatment. These results could help the interpretation of published or ongoing clinical trial outcomes and refine patient recruitment in the future.

SUBMITTER: Etcheverry A

PROVIDER: S-EPMC4169423 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Publications

DGKI methylation status modulates the prognostic value of MGMT in glioblastoma patients treated with combined radio-chemotherapy with temozolomide.

Etcheverry Amandine A Aubry Marc M Idbaih Ahmed A Vauleon Elodie E Marie Yannick Y Menei Philippe P Boniface Rachel R Figarella-Branger Dominique D Karayan-Tapon Lucie L Quillien Veronique V Sanson Marc M de Tayrac Marie M Delattre Jean-Yves JY Mosser Jean J

PloS one 20140918 9

<h4>Background</h4>Consistently reported prognostic factors for glioblastoma (GBM) are age, extent of surgery, performance status, IDH1 mutational status, and MGMT promoter methylation status. We aimed to integrate biological and clinical prognostic factors into a nomogram intended to predict the survival time of an individual GBM patient treated with a standard regimen. In a previous study we showed that the methylation status of the DGKI promoter identified patients with MGMT-methylated tumors ...[more]

PMID: 25233099

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Project description:BackgroundGlioblastoma is an aggressive form of brain cancer. Approximately five in 100 people with glioblastoma survive for five years past diagnosis. Glioblastomas that have a particular modification to their DNA (called methylation) in a particular region (the O6-methylguanine-DNA methyltransferase (MGMT) promoter) respond better to treatment with chemotherapy using a drug called temozolomide.ObjectivesTo determine which method for assessing MGMT methylation status best predicts overall survival in people diagnosed with glioblastoma who are treated with temozolomide.Search methodsWe searched MEDLINE, Embase, BIOSIS, Web of Science Conference Proceedings Citation Index to December 2018, and examined reference lists. For economic evaluation studies, we additionally searched NHS Economic Evaluation Database (EED) up to December 2014.Selection criteriaEligible studies were longitudinal (cohort) studies of adults with diagnosed glioblastoma treated with temozolomide with/without radiotherapy/surgery. Studies had to have related MGMT status in tumour tissue (assessed by one or more method) with overall survival and presented results as hazard ratios or with sufficient information (e.g. Kaplan-Meier curves) for us to estimate hazard ratios. We focused mainly on studies comparing two or more methods, and listed brief details of articles that examined a single method of measuring MGMT promoter methylation. We also sought economic evaluations conducted alongside trials, modelling studies and cost analysis.Data collection and analysisTwo review authors independently undertook all steps of the identification and data extraction process for multiple-method studies. We assessed risk of bias and applicability using our own modified and extended version of the QUality In Prognosis Studies (QUIPS) tool. We compared different techniques, exact promoter regions (5'-cytosine-phosphate-guanine-3' (CpG) sites) and thresholds for interpretation within studies by examining hazard ratios. We performed meta-analyses for comparisons of the three most commonly examined methods (immunohistochemistry (IHC), methylation-specific polymerase chain reaction (MSP) and pyrosequencing (PSQ)), with ratios of hazard ratios (RHR), using an imputed value of the correlation between results based on the same individuals.Main resultsWe included 32 independent cohorts involving 3474 people that compared two or more methods. We found evidence that MSP (CpG sites 76 to 80 and 84 to 87) is more prognostic than IHC for MGMT protein at varying thresholds (RHR 1.31, 95% confidence interval (CI) 1.01 to 1.71). We also found evidence that PSQ is more prognostic than IHC for MGMT protein at various thresholds (RHR 1.36, 95% CI 1.01 to 1.84). The data suggest that PSQ (mainly at CpG sites 74 to 78, using various thresholds) is slightly more prognostic than MSP at sites 76 to 80 and 84 to 87 (RHR 1.14, 95% CI 0.87 to 1.48). Many variants of PSQ have been compared, although we did not see any strong and consistent messages from the results. Targeting multiple CpG sites is likely to be more prognostic than targeting just one. In addition, we identified and summarised 190 articles describing a single method for measuring MGMT promoter methylation status.Authors' conclusionsPSQ and MSP appear more prognostic for overall survival than IHC. Strong evidence is not available to draw conclusions with confidence about the best CpG sites or thresholds for quantitative methods. MSP has been studied mainly for CpG sites 76 to 80 and 84 to 87 and PSQ at CpG sites ranging from 72 to 95. A threshold of 9% for CpG sites 74 to 78 performed better than higher thresholds of 28% or 29% in two of three good-quality studies making such comparisons.

Project description:BackgroundOur previous studies have indicated that miR-198 reduces cellular methylguanine DNA methyltransferase (MGMT) levels to enhance temozolomide sensitivity. Transforming growth factor beta 1 (TGF-β1) switches off miR-198 expression by repressing K-homology splicing regulatory protein (KSRP) expression in epidermal keratinocytes. However, the underlying role of TGF-β1 in temozolomide resistance has remained unknown.MethodsThe distribution of KSRP was detected by western blotting and immunofluorescence. Microarray analysis was used to compare the levels of long noncoding RNAs (lncRNAs) between TGF-β1-treated and untreated cells. RNA immunoprecipitation was performed to verify the relationship between RNAs and KSRP. Flow cytometry and orthotopic and subcutaneous xenograft tumor models were used to determine the function of TGF-β1 in temozolomide resistance.ResultsOverexpression of TGF-β1 contributed to temozolomide resistance in MGMT promoter hypomethylated glioblastoma cells in vitro and in vivo. TGF-β1 treatment reduced cellular MGMT levels through suppressing the expression of miR-198. However, TGF-β1 upregulation did not affect KSRP expression in glioma cells. We identified and characterized 2 lncRNAs (H19 and HOXD-AS2) that were upregulated by TGF-β1 through Smad signaling. H19 and HOXD-AS2 exhibited competitive binding to KSRP and prevented KSRP from binding to primary miR-198, thus decreasing miR-198 expression. HOXD-AS2 or H19 upregulation strongly promoted temozolomide resistance and MGMT expression. Moreover, KSRP depletion abrogated the effects of TGF-β1 and lncRNAs on miR-198 and MGMT. Finally, we found that patients with low levels of TGF-β1 or lncRNA expression benefited from temozolomide therapy.ConclusionsOur results reveal an underlying mechanism by which TGF-β1 confers temozolomide resistance. Furthermore, our findings suggest that a novel combination of temozolomide with a TGF-β inhibitor may serve as an effective therapy for glioblastomas.

Project description:Background: Glioblastoma (GBM) prognosis remains extremely poor despite standard treatment that includes temozolomide (TMZ) chemotherapy. To discover new GBM drug targets and biomarkers, genes signatures associated with survival and TMZ resistance in GBM patients treated with TMZ were identified. Methods: GBM cases in The Cancer Genome Atlas who received TMZ (n = 221) were stratified into subgroups that differed by median overall survival (mOS) using network-based stratification to cluster patients whose somatic mutations affected genes in similar modules of a gene interaction network. Gene signatures formed from differentially mutated genes in the subgroup with the longest mOS were used to confirm their association with survival and TMZ resistance in independent datasets. Somatic mutations in these genes also were assessed for an association with OS in an independent group of 37 GBM cases. Results: Among the four subgroups identified, subgroup four (n = 71 subjects) exhibited the longest mOS at 18.3 months (95% confidence interval: 16.2, 34.1; p = 0.0324). Subsets of the 86 genes that were differentially mutated in this subgroup formed 20-gene and 8-gene signatures that predicted OS in two independent datasets (Spearman's rho of 0.64 and 0.58 between actual and predicted OS; p < 0.001). Patients with mutations in five of the 86 genes had longer OS in a small, independent sample of 37 GBM cases, but this association did not reach statistical significance (p = 0.07). Thirty-one of the 86 genes formed signatures that distinguished TMZ-resistant GBM samples from controls in three independent datasets (area under the curve ≥ 0.75). The prognostic and TMZ-resistance signatures had eight genes in common (ANG, BACH1, CDKN2C, HMGA1, IFI16, PADI4, SDF4, and TP53INP1). The latter three genes have not been associated with GBM previously. Conclusion: PADI4, SDF4, and TP53INP1 are novel therapy and biomarker candidates for GBM. Further investigation of their oncologic functions may provide new insight into GBM treatment resistance mechanisms.

Dataset Information

DGKI methylation status modulates the prognostic value of MGMT in glioblastoma patients treated with combined radio-chemotherapy with temozolomide.

Background

Methods

Results

Conclusions

Publications

DGKI methylation status modulates the prognostic value of MGMT in glioblastoma patients treated with combined radio-chemotherapy with temozolomide.

Similar Datasets

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