Preoperative inflammation markers and IDH mutation status predict glioblastoma patient survival.
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ABSTRACT:
SUBMITTER: Wang PF
PROVIDER: S-EPMC5564834 | biostudies-other | 2017 Jul
REPOSITORIES: biostudies-other
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Project description:Glioma is the most common primary brain tumor with various genetic alterations; among which, IDH mutation is the most common mutation and plays an important role in glioma early development, especially in lower grade glioma (LGG, WHO II-III). Previous studies have found that IDH mutation is tightly associated with extensive methylation across whole genome in glioma. To further investigate the role of IDH, we obtained methylation data of 777 samples from CGGA (Chinese Glioma Genome Atlas) and TCGA (The Cancer Genome Atlas) with IDH mutation status available. A package compiled under R language called Tspair was used as the main analytic tool to find potential probes that were significantly affected by IDH mutation. As a result, we found one pair of probes, cg06940792 and cg26025891, which was capable of predicting IDH mutation status precisely. The hypermethylated probe was cg06940792, designed in the promoter region of MEGF10, while the hypomethylated probe was cg26025891, designed in the promoter region of PSTPIP1. Survival analysis proved that hypermethylation or low expression of MEGF10 indicated a favorable prognosis in 983 glioma samples. Moreover, gene ontology analysis demonstrated that MEGF10 was associated with cell migration, cell proliferation, and regulation of apoptosis in glioma. All findings above can be validated in three other independent cohorts. In a word, our results suggested that methylation level and mRNA expression of MEGF10 in glioma were not only correlated with IDH mutation but also associated with clinical outcome of patients, providing potential guide for future dissection of IDH role in glioma.
| S-EPMC5985127 | biostudies-literature
Project description:BackgroundsMutations in the isocitrate dehydrogenase (IDH)1 gene are favourable prognostic factors in newly diagnosed diffuse gliomas, whereas it remains controversial in the recurrent glioblastoma setting.MethodsA total of 171 patients with newly diagnosed glioblastoma, either 'primary' glioblastoma or 'secondary' glioblastoma, treated at Kyorin University Hospital or Japanese Red Cross Medical Center from 2000 to 2015 were included. Patients with confirmed IDH1 status and O6-methylguanine-DNA methyltransferase promoter methylation status were retrospectively analysed for overall survival from the initial diagnosis (n = 147) and after the first progression (n = 122).ResultsIDH1 mutation but not IDH2 was noted in 19 of 147 patients with glioblastoma (12.9%). In patients with 'primary' glioblastoma (n = 136), median overall survival after the first progression was 13.5 and 10.5 months for mutant IDH1 and wild-type IDH1 glioblastoma, respectively (P = 0.747). Multivariate analysis revealed O6-methylguanine-DNA methyltransferase promoter methylation, and Karnofsky Performance status 60 or higher, were independent prognostic factors for better overall survival after the first progression. When 'primary' glioblastoma and 'secondary' glioblastoma were combined, median overall survival from the first progression was not significantly different between the mutant IDH1 group (10.1 months) and wild-type IDH1 group (10.5 months) (P = 0.559), whereas median overall survival from the initial diagnosis was significantly different (47.5 months vs.18.3 months, respectively; P = 0.035).ConclusionsThese results suggest that IDH1 mutation may not be a prognostic factor for survival at the first progression of patients with 'primary' glioblastoma and pretreated 'secondary' glioblastoma, and further warrant investigation in prospective studies.
| S-EPMC7767982 | biostudies-literature
Project description:PurposeThis 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.MethodA 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.ResultsWild-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.ConclusionMGMT 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.
| S-EPMC6089138 | biostudies-literature
Project description:BackgroundGlioma prognosis depends on isocitrate dehydrogenase (IDH) mutation status. We aimed to predict the IDH status of gliomas from preoperative MR images using a fully automated hybrid approach with convolutional neural networks (CNNs) and radiomics.MethodsWe reviewed 1166 preoperative MR images of gliomas (grades II-IV) from Severance Hospital (n = 856), Seoul National University Hospital (SNUH; n = 107), and The Cancer Imaging Archive (TCIA; n = 203). The Severance set was subdivided into the development (n = 727) and internal test (n = 129) sets. Based on T1 postcontrast, T2, and fluid-attenuated inversion recovery images, a fully automated model was developed that comprised a CNN for tumor segmentation (Model 1) and CNN-based classifier for IDH status prediction (Model 2) that uses a hybrid approach based on 2D tumor images and radiomic features from 3D tumor shape and loci guided by Model 1. The trained model was tested on internal (a subset of the Severance set) and external (SNUH and TCIA) test sets.ResultsThe CNN for tumor segmentation (Model 1) achieved a dice coefficient of 0.86-0.92 across datasets. Our hybrid model achieved accuracies of 93.8%, 87.9%, and 78.8%, with areas under the receiver operating characteristic curves of 0.96, 0.94, and 0.86 and areas under the precision-recall curves of 0.88, 0.82, and 0.81 in the internal test, SNUH, and TCIA sets, respectively.ConclusionsOur fully automated hybrid model demonstrated the potential to be a highly reproducible and generalizable tool across different datasets for the noninvasive prediction of the IDH status of gliomas.
| S-EPMC7906063 | biostudies-literature
Project description:The evaluation of the isocitrate dehydrogenase (IDH) mutation status in the glioma decision-making process has diagnostic, prognostic and therapeutic implications. The aim of this study was to evaluate whether conventional magnetic resonance imaging (MRI) and apparent diffusion coefficient (ADC) can noninvasively predict the most common IDH mutational status (R132H) in GIII-astrocytomas and the overall survival (OS). Hence, twenty-two patients (9-F, 13-M) with a histological diagnosis of GIII-astrocytoma and evaluation of IDH-mutation status (12-wild type, 10-mutant) were retrospectively evaluated. Imaging studies were reviewed for the morphological feature and mean ADC values (ADCm). Statistics included a Fisher's exact test, Student's t-test, Spearman's Test and receiver operating characteristic analysis. A p ? 0.05 value was considered statistically significant for all the tests. A younger age and a frontal location were more likely related to mutational status. IDH-wild type (Wt) exhibited a slight enhancement (p = 0.039). The ADCm values in IDH-mutant (Mut) patients were higher than those of IDH-Wt patients (p < 0.0004). The value of ADC ? 0.99 × 10-3 mm2/s emerged as a "cut-off" to differentiate the mutation state. In the overall group, a positive relationship between the ADCm values and OS was detected (p = 0.003; r = 0.62). Adding quantitative measures of ADC values to conventional MR imaging could be used routinely as a noninvasive marker of specific molecular patterns.
| S-EPMC7236014 | biostudies-literature
Project description:BackgroundRing enhancement on magnetic resonance imaging (MRI) is an important characteristic of GBM. Though patients suffering from glioblastoma multiforme (GBM) with BRAF mutation (MUT BRAF) in V600E benefit from BRAF-targeted inhibitors, the relationship between ring enhancement and MUT BRAF remains elusive. The purpose of this study was to investigate the relationship between BRAF mutation status and the appearance of ring enhancement so as to guide preoperative targeted therapy for MUT BRAF GBM.MethodsPatient's population, clinical data and characteristic ring enhancement appearances on MRI were compared between GBM with MUT BRAF and GBM with WT BRAF. A receiver operating characteristic (ROC) curve analysis was performed to evaluate the differential diagnostic significance. A nomogram was developed to predict the mutation status of BRAF. Moreover, all the variables were re-analyzed between epithelioid GBM (E-GBM) with or without MUT BRAF.ResultsCompared to GBM with WT BRAF, GBM with MUT BRAF had specific ring enhancement appearances with multiple rings, multiple located lobes, regular shape of ring, uniform thickness of ring and smaller diameter of ring. Area under the curve (AUC) of all the variables' combination was 0.929. The nomogram was developed and validated. The re-analyzed results between E-GBM with or without MUT BRAF were similar to these above. AUC of the combination of quantity of ring, quantity of located lobe and shape of ring was 0.962.ConclusionThe characteristic ring enhancement appearances of GBM may play an important role in predicting BRAF mutation status preoperatively, especially in E-GBM. Further study with larger cases may provide more evidences to guide the pretreatment of targeted medicine for GBM patients with MUT BRAF in future.
| S-EPMC9393738 | biostudies-literature
Project description:Mutations of the isocitrate dehydrogenase (IDH) 1 and 2 genes occur in ~80% of lower-grade (WHO grade II and grade III) gliomas. Mutant IDH produces (R)-2-hydroxyglutarate, which induces DNA hypermethylation and presumably drives tumorigenesis. Interestingly, IDH mutations are associated with improved survival in glioma patients, but the underlying mechanism for the difference in survival remains unclear. Through comparative analyses of 286 cases of IDH-wildtype and IDH-mutant lower-grade glioma from a TCGA data set, we report that IDH-mutant gliomas have increased expression of tumor-suppressor genes (NF1, PTEN, and PIK3R1) and decreased expression of oncogenes(AKT2, ARAF, ERBB2, FGFR3, and PDGFRB) and glioma progression genes (FOXM1, IGFBP2, and WWTR1) compared with IDH-wildtype gliomas. Furthermore, each of these genes is prognostic in overall gliomas; however, within the IDH-mutant group, none remains prognostic except IGFBP2 (encodinginsulin-like growth factor binding protein 2). Through validation in an independent cohort, we show that patients with low IGFBP2 expressiondisplay a clear advantage in overall and disease-free survival, whereas those with high IGFBP2 expressionhave worse median survival than IDH-wildtype patients. These observations hold true across different histological and molecular subtypes of lower-grade glioma. We propose therefore that an unexpected biological consequence of IDH mutations in glioma is to ameliorate patient survival by promoting tumor-suppressor signaling while inhibiting that of oncogenes, particularly IGFBP2.
| S-EPMC5352106 | biostudies-literature
Project description:To address the current lack of dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI)-based radiomics to predict isocitrate dehydrogenase (IDH) mutations in gliomas, we present a multicenter study that featured an independent exploratory set for radiomics model development and external validation using two independent cohorts. The maximum performance of the IDH mutation status prediction on the validation set had an accuracy of 0.544 (Cohen's kappa: 0.145, F1-score: 0.415, area under the curve-AUC: 0.639, sensitivity: 0.733, specificity: 0.491), which significantly improved to an accuracy of 0.706 (Cohen's kappa: 0.282, F1-score: 0.474, AUC: 0.667, sensitivity: 0.6, specificity: 0.736) when dynamic-based standardization of the images was performed prior to the radiomics. Model explainability using local interpretable model-agnostic explanations (LIME) and Shapley additive explanations (SHAP) revealed potential intuitive correlations between the IDH-wildtype increased heterogeneity and the texture complexity. These results strengthened our hypothesis that DSC-MRI radiogenomics in gliomas hold the potential to provide increased predictive performance from models that generalize well and provide understandable patterns between IDH mutation status and the extracted features toward enabling the clinical translation of radiogenomics in neuro-oncology.
| S-EPMC8391559 | biostudies-literature
Project description:Background:Glioblastoma (GBM) is the most common malignant central nervous system tumor, and MGMT promoter hypermethylation in this tumor has been shown to be associated with better prognosis. We evaluated the capacity of radiomics features to add complementary information to MGMT status, to improve the ability to predict prognosis. Methods:159 patients with untreated GBM were included in this study and divided into training and independent test sets. 286 radiomics features were extracted from the magnetic resonance images acquired prior to any treatments. A least absolute shrinkage selection operator (LASSO) selection followed by Kaplan-Meier analysis was used to determine the prognostic value of radiomics features to predict overall survival (OS). The combination of MGMT status with radiomics was also investigated and all results were validated on the independent test set. Results:LASSO analysis identified 8 out of the 286 radiomic features to be relevant which were then used for determining association to OS. One feature (edge descriptor) remained significant on the external validation cohort after multiple testing (p=0.04) and the combination with MGMT identified a group of patients with the best prognosis with a survival probability of 0.61 after 43 months (p=0.0005). Conclusion:Our results suggest that combining radiomics with MGMT is more accurate in stratifying patients into groups of different survival risks when compared to with using these predictors in isolation. We identified two subgroups within patients who have methylated MGMT: one with a similar survival to unmethylated MGMT patients and the other with a significantly longer OS.
| S-EPMC6363013 | biostudies-literature
Project description:BackgroundThe host inflammatory response has a vital role in carcinogenesis and tumour progression. We examined the prognostic value of inflammatory markers (albumin, white-cell count and its components, and platelets) in pre-treated patients with advanced renal cell carcinoma (RCC).MethodsUsing data from a randomised trial, multivariable proportional hazards models were generated to examine the impact of inflammatory markers and established prognostic factors (performance status, calcium, and haemoglobin) on overall survival (OS). We evaluated a new prognostic classification incorporating additional information from inflammatory markers.ResultsOf the 416 patients, 362 were included in the analysis. Elevated neutrophil counts, elevated platelet counts, and a high neutrophil-lymphocyte ratio were significant independent predictors for shorter OS in a model with established prognostic factors. The addition of inflammatory markers improves the discriminatory value of the prognostic classification as compared with established factors alone (C-statistic 0.673 vs 0.654, P=0.002 for the difference), with 25.8% (P=0.004) of patients more appropriately classified using the new classification.ConclusionMarkers of systemic inflammation contribute significantly to prognostic classification in addition to established factors for pre-treated patients with advanced RCC. Upon validation of these data in independent studies, stratification of patients using these markers in future clinical trials is recommended.
| S-EPMC3708579 | biostudies-literature