Dataset Information

The TERT promoter mutation status and MGMT promoter methylation status, combined with dichotomized MRI-derived and clinical features, predict adult primary glioblastoma survival.

ABSTRACT:

Purpose

This study aimed to integrate the TERT promoter mutation status, MGMT promoter methylation status, MRI-derived features, and clinical features into a survival analysis model to better understand adult primary glioblastoma prognosis-related markers.

Method

A total of 304 adult glioblastoma samples collected after surgical resection were selected for retrospective analysis, and Sanger sequencing was performed to detect IDH and TERT promoter mutations. The methylation of the MGMT promoter was analyzed by pyrosequencing, and MRI-derived and clinical features were dichotomized into easily acquired variables. Random survival forest analysis, Kaplan-Meier analysis, Cox proportional hazard regression, and LASSO regression were performed for the survival analysis, and ROC analysis and Pearson's chi-squared test were employed for the correlation analysis.

Results

Wild-type IDH was present in 89.8% of the adult glioblastoma samples, and TERT promoter mutations and MGMT promoter methylation were observed in 66.42% and 38.49% of all adult primary glioblastomas, respectively. Age and MGMT promoter methylation were identified as independent prognostic biomarkers, and the TERT promoter mutation status and MGMT promoter methylation status, when combined with other tumor-related factors, generated several different survival subgroups. None of the factors investigated in this study predicted the MGMT promoter status, and MRI-detected necrosis was positively associated with TERT promoter mutations.

Conclusion

MGMT promoter methylation and TERT promoter mutations, combined with MRI-derived and clinical features, revealed different survival subgroups with distinct responses to current treatments, and this information increases the ability to predict the survival of adult primary glioblastoma patients. MRI-detected necrosis often indicates the presence of TERT promoter mutations.

SUBMITTER: Shu C

PROVIDER: S-EPMC6089138 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Publications

The TERT promoter mutation status and MGMT promoter methylation status, combined with dichotomized MRI-derived and clinical features, predict adult primary glioblastoma survival.

Shu Chang C Wang Qiong Q Yan Xiaoling X Wang Jinhuan J

Cancer medicine 20180709 8

<h4>Purpose</h4>This study aimed to integrate the TERT promoter mutation status, MGMT promoter methylation status, MRI-derived features, and clinical features into a survival analysis model to better understand adult primary glioblastoma prognosis-related markers.<h4>Method</h4>A total of 304 adult glioblastoma samples collected after surgical resection were selected for retrospective analysis, and Sanger sequencing was performed to detect IDH and TERT promoter mutations. The methylation of the ...[more]

PMID: 29984907

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Project description:BackgroundThe clinical relevance of promoter mutations and single nucleotide polymorphism rs2853669 of telomerase reverse transcriptase (TERT) and telomere length in patients with isocitrate dehydrogenase (IDH) wild-type glioblastoma (GBM) patients remains unclear. Moreover, some studies speculated that TERT promoter status might influence the prognostic role of O6-methylguanine DNA methyltransferase (MGMT) promoter methylation in newly diagnosed GBM. We carried out a large study to investigate their clinical impact and their interaction in newly diagnosed GBM patients.Patients and methodsWe included 273 newly diagnosed IDH wild-type GBM patients who started treatment at Veneto Institute of Oncology IOV - IRCCS (Padua, Italy) from December 2016 to January 2020. TERT promoter mutations (-124 C>T and -146 C>T) and SNP rs2853669 (-245 T>C), relative telomere length (RTL) and MGMT methylation status were retrospectively assessed in this prospective cohort of patients.ResultsMedian overall survival (OS) of 273 newly diagnosed IDH wild-type GBM patients was 15 months. TERT promoter was mutated in 80.2% of patients, and most had the rs2853669 single nucleotide polymorphism as T/T genotype (46.2%). Median RTL was 1.57 (interquartile range 1.13-2.32). MGMT promoter was methylated in 53.4% of cases. At multivariable analysis, RTL and TERT promoter mutations were not associated with OS or progression-free survival (PFS). Notably, patients C carrier of rs2853669 (C/C+C/T genotypes) showed a better PFS compared with those with the T/T genotype (hazard ratio 0.69, P = 0.007). In terms of OS and PFS, all interactions between MGMT, TERT and RTL and between TERT and rs2853669 genotype were not statistically significant.ConclusionsOur findings suggest the presence of the C variant allele at the rs2853669 of the TERT promoter as an attractive independent prognostic biomarker of disease progression in IDH wild-type GBM patients. RTL and TERT promoter mutational status were not correlated to survival regardless of MGMT methylation status.

Project description:Temozolomide (TMZ) is an important first-line treatment for glioblastoma (GBM), but there are limitations to TMZ response in terms of durability and dependence on the promoter methylation status of the DNA repair gene O6-methylguanine DNA methyltransferase (MGMT). MGMT-promoter-hypermethylated (MGMT-M) GBMs are more sensitive to TMZ than MGMT-promoter-hypomethylated (MGMT-UM) GBMs. Moreover, TMZ resistance is inevitable even in TMZ-sensitive MGMT-M GBMs. Hence, epigenetic reprogramming strategies are desperately needed in order to enhance TMZ response in both MGMT-M and MGMT-UM GBMs. In this study, we present novel evidence that the epigenetic reactivation of Tumor Suppressor Candidate 3 (TUSC3) can reprogram sensitivity of GBM stem cells (GSCs) to TMZ irrespective of MGMT promoter methylation status. Interrogation of TCGA patient GBM datasets confirmed TUSC3 promoter regulation of TUSC3 expression and also revealed a strong positive correlation between TUSC3 expression and GBM patient survival. Using a combination of loss-of-function, gain-of-function and rescue studies, we demonstrate that TUSC3 reactivation is associated with enhanced TMZ response in both MGMT-M and MGMT-UM GSCs. Further, we provide novel evidence that the demethylating agent 5-Azacitidine (5-Aza) reactivates TUSC3 expression in MGMT-M GSCs, whereas the combination of 5-Aza and MGMT inhibitor Lomeguatrib is necessary for TUSC3 reactivation in MGMT-UM GSCs. Lastly, we propose a pharmacological epigenetic reactivation strategy involving TUSC3 that leads to significantly prolonged survival in MGMT-M and MGMT-UM orthotopic GSCs models. Collectively, our findings provide a framework and rationale to further explore TUSC3-mediated epigenetic reprogramming strategies that could enhance TMZ sensitivity and outcomes in GBM. Mechanistic and translational evidence gained from such studies could contribute towards optimal design of impactful trials for MGMT-UM GBMs that currently do not have good treatment options.

Project description:The methylation of the O6-methylguanine-DNA methyltransferase (MGMT) promoter is a molecular marker associated with a better response to chemotherapy in patients with glioblastoma (GB). Standard pre-operative magnetic resonance imaging (MRI) analysis is not adequate to detect MGMT promoter methylation. This study aims to evaluate whether the radiomic features extracted from multiple tumor subregions using multiparametric MRI can predict MGMT promoter methylation status in GB patients. This retrospective single-institution study included a cohort of 277 GB patients whose 3D post-contrast T1-weighted images and 3D fluid-attenuated inversion recovery (FLAIR) images were acquired using two MRI scanners. Three separate regions of interest (ROIs) showing tumor enhancement, necrosis, and FLAIR hyperintensities were manually segmented for each patient. Two machine learning algorithms (support vector machine (SVM) and random forest) were built for MGMT promoter methylation prediction from a training cohort (196 patients) and tested on a separate validation cohort (81 patients), based on a set of automatically selected radiomic features, with and without demographic variables (i.e., patients' age and sex). In the training set, SVM based on the selected radiomic features of the three separate ROIs achieved the best performances, with an average of 83.0% (standard deviation: 5.7%) for accuracy and 0.894 (0.056) for the area under the curve (AUC) computed through cross-validation. In the test set, all classification performances dropped: the best was obtained by SVM based on the selected features extracted from the whole tumor lesion constructed by merging the three ROIs, with 64.2% (95% confidence interval: 52.8-74.6%) accuracy and 0.572 (0.439-0.705) for AUC. The performances did not change when the patients' age and sex were included with the radiomic features into the models. Our study confirms the presence of a subtle association between imaging characteristics and MGMT promoter methylation status. However, further verification of the strength of this association is needed, as the low diagnostic performance obtained in this validation cohort is not sufficiently robust to allow clinically meaningful predictions.

Dataset Information

The TERT promoter mutation status and MGMT promoter methylation status, combined with dichotomized MRI-derived and clinical features, predict adult primary glioblastoma survival.

Purpose

Method

Results

Conclusion

Publications

The TERT promoter mutation status and MGMT promoter methylation status, combined with dichotomized MRI-derived and clinical features, predict adult primary glioblastoma survival.

Similar Datasets

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