<i>IDH1/IDH2</i>but Not<i>TP53</i>Mutations Predict Prognosis in Bulgarian Glioblastoma Patients

Stancheva, G.; Goranova, Teodora; Laleva, Maria; Kamenova, M.; Mitkova, A.; Velinov, N.; Poptodorov, G.; Mitev, Vanio; Kaneva, Radka; Gabrovsky, N.

doi:10.1155/2014/654727

Cited by 41 publications

(42 citation statements)

References 45 publications

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“…As a significant predictive indicator for prognosis in GBM, IDH1 mutation has been investigated in some MGMT promoter methylation was not predictive for survival outcome studies (Yan et al, 2012;Sarmiento et al, 2014;Stancheva et al, 2014). It has been demonstrated that patients with mutant IDH1 had significantly longer PFS and OS than those with wild-type IDH.…”

Section: Discussionmentioning

confidence: 99%

“…Nevertheless, other research found that MGMT promoter methylation is a predictive biomarker in patients with IDH1wild-type, but not IDH1-mutant, malignant gliomas for those who received alkylating agent chemotherapy (Wick et al, 2013). The combination of IDH1 and TP53 mutation has also been evaluated for the survival of patients with GBM, but no expected conclusion regarding the prognostic value of the combined alternation of IDH1 and TP53 for outcome had been drawn (Stancheva et al, 2014). Because the study was carried out in the Bulgarian population that may be a limitation of the research.…”

Section: Discussionmentioning

confidence: 99%

“…Three gene markers that have attracted most interest in this respect are mutations in the isocitrate dehydrogenase 1 (IDH1) or 2 (IDH2) gene (Stancheva et al, 2014), hypermethylation of the O 6 -methylguanine-DNA methyltransferase (MGMT) promoter, and complete deletion of both 1p and 19q. …”

Section: Introductionmentioning

confidence: 99%

“…Besides, tumor-suppressor gene TP53 mutation status also acts in the pathogenesis of gliomas and influences patients' prognosis (Stancheva et al, 2014). Mutations in IDH1 were shown to be a positive prognostic marker for GBM patient survival (Nobusawa et al, 2009;Sanson et al, 2009Bleeker et al, 2010.…”

Section: Introductionmentioning

confidence: 99%

“…

Asian Pac J Cancer Prev, 15 (24), 10893-10898

IntroductionGlioblastoma multiform (GBM), classified as World Health Organization (WHO) grade IV, is the most common malignant brain tumors in adults with an incidence rate of 23 per 100,000 persons (Stancheva et al, 2014). Their clinical course varies substantially, such that some patients succumb to progressive disease within weeks while others survive for a decade or more.

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confidence: 99%

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Prognostic Value of MGMT Promoter Methylation and TP53 Mutation in Glioblastomas Depends on IDH1 Mutation

Wang

Wang²,

Ma³

et al. 2015

Asian Pacific Journal of Cancer Prevention

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Asian Pac J Cancer Prev, 15 (24), 10893-10898 IntroductionGlioblastoma multiform (GBM), classified as World Health Organization (WHO) grade IV, is the most common malignant brain tumors in adults with an incidence rate of 23 per 100,000 persons (Stancheva et al., 2014). Their clinical course varies substantially, such that some patients succumb to progressive disease within weeks while others survive for a decade or more. Current treatments include surgery, radiation therapy and chemotherapy (Sathornsumetee et al., 2007;Koca et al., 2014;Pashaki et al., 2014). However, the median survival is still not optimistic. In spite of the existing classification, GBM subgroups are not homogeneous in terms of survival (Molenaar et al., 2014). Several prognostic factors have been established, including age, preoperative Karnofsky Performance Status (KPS), extent of resection, and also some molecular markers.Recently, molecular markers were shown to be helpful in predicting prognosis and treatment response. Three gene markers that have attracted most interest in this respect are mutations in the isocitrate dehydrogenase 1 (IDH1) or 2 (IDH2) gene (Stancheva et al., 2014), hypermethylation of the O 6 -methylguanine-DNA methyltransferase (MGMT) promoter, and complete deletion of both 1p and 19q. Abstract Several molecular markers have been proposed as predictors of outcome in patients with glioblastomas.We investigated the prognostic significance of O 6 -methylguanine-DNA methyltransferase (MGMT) promoter methylation and TP53 mutation status dependent on isocitrate dehydrogenase 1 (IDH1) mutation in glioblastoma patients. A cohort of 78 patients with histologically confirmed glioblastomas treated with radiation therapy and chemotherapy were reviewed retrospectively. We evaluated the prognostic value of MGMT promoter methylation and TP53 mutation status with regard to progression-free survival (PFS) and overall survival (OS). It was revealed that mutations in IDH1, promoter methylation of MGMT, TP53 mutation, age, Karnofsky performance status (KFS), and extension of resection were independent prognostic factors. In patients with an IDH1 mutation, those with an MGMT methylation were associated with longer PFS (p=0.016) and OS (p=0.013). Nevertheless, the presence of TP53 mutation could stratify the PFS and OS of patients with IDH1 wild type (p=0.003 and 0.029 respectively, log-rank). The MGMT promoter methylation and TP53 mutation were associated with a favorable outcome of patients with and without mutant IDH1, respectively. The results indicate that glioblastomas with MGMT methylation or TP53 mutations have improved survival that may be influenced by IDH1 mutation status.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…

Asian Pac J Cancer Prev, 15 (24), 10893-10898

…”

mentioning

confidence: 99%

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Prognostic Value of MGMT Promoter Methylation and TP53 Mutation in Glioblastomas Depends on IDH1 Mutation

Wang

Wang²,

Ma³

et al. 2015

Asian Pacific Journal of Cancer Prevention

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Frequency and clinical significance of chromosome 7 and 10 aneuploidies, amplification of the EGFR gene, deletion of PTEN and TP53 genes, and 1p/19q deficiency in a sample of adult patients diagnosed with glioblastoma from Southern Brazil

et al. 2017

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Glioblastoma stands out as the most frequent central nervous system neoplasia, presenting a poor prognosis. The aim of this study was to verify the frequency and clinical significance of the aneuploidy of chromosomes 7 and 10, EGFR amplification, PTEN and TP53 deletions and 1p/19q deficiency in adult patients diagnosed with glioblastoma. The sample consisted of 40 patients treated from November 2011 to March 2015 at two major neurosurgery services from Southern Brazil. Molecular cytogenetic analyses of the tumor were performed through fluorescent in situ hybridization (FISH). The clinical features evaluated consisted of age, sex, tumor location, clinical symptoms, family history of cancer, type of resection and survival. The mean age of the patients was 59.3 years (ranged from 41 to 83). Most of them were males (70%). The median survival was 145 days. Chromosome 10 monosomy was detected in 52.5% of the patients, chromosome 7 polysomy in 50%, EGFR amplification in 42.5%, PTEN deletion in 35%, TP53 deletion in 22.5%, 1p deletion in 5% and 19q deletion in 7.5%. Age was shown to be a prognostic factor, and patients with lower age presented higher survival (p = 0.042). TP53 and PTEN deletions had a negative impact on survival (p = 0.011 and p = 0.037, respectively). Our data suggest that TP53 and PTEN deletions may be associated with a poorer prognosis. These findings may have importance over prognosis determination and choice of the therapy to be administered.

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A combined diffusion tensor imaging and Ki-67 labeling index study for evaluating the extent of tumor infiltration using the F98 rat glioma model

Wang

Chen

et al. 2018

J Neurooncol

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Diffusion tensor imaging (DTI) has been proven to be a sophisticated and useful tool for the delineation of tumors. In the present study, we investigated the predictive role of DTI compared to other magnetic resonance imaging (MRI) techniques in combination with Ki-67 labeling index in defining tumor cell infiltration in the peritumoral regions of F98 glioma-bearing rats. A total of 29 tumor-bearing Fischer rats underwent T2-weighted imaging, contrast-enhanced T1-weighted imaging, and DTI of their brain using a 7.0-T MRI scanner. The fractional anisotropy (FA) ratios were correlated to the Ki-67 labeling index using the Spearman correlation analysis. A receiver operating characteristic curve (ROC) analysis was established to evaluate parameters with sensitivity and specificity in order to identify the threshold values for predicting tumor infiltration. Significant correlations were observed between the FA ratios and Ki-67 labeling index (r = - 0.865, p < 0.001). The ROC analysis demonstrated that the apparent diffusion coefficient (ADC) and FA ratios could predict 50% of the proliferating cells in the regions of interest (ROI), with a sensitivity of 88.1 and 81.3%, and a specificity of 86.2 and 90.2%, respectively (p < 0.001). Meanwhile, the two ratios could also predict 10% of the proliferating cells in the ROI, with a sensitivity of 82.5 and 94.9%, and a specificity of 100 and 88.9%, respectively (p < 0.001). The present study demonstrated that the FA ratios are closely correlated with the Ki-67 labeling index. Furthermore, both ADC and FA ratios, derived from DTI, were useful for quantitatively predicting the Ki-67 labeling of glioma cells.

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IDH1/IDH2but NotTP53Mutations Predict Prognosis in Bulgarian Glioblastoma Patients

Cited by 41 publications

References 45 publications

Prognostic Value of MGMT Promoter Methylation and TP53 Mutation in Glioblastomas Depends on IDH1 Mutation

Prognostic Value of MGMT Promoter Methylation and TP53 Mutation in Glioblastomas Depends on IDH1 Mutation

Frequency and clinical significance of chromosome 7 and 10 aneuploidies, amplification of the EGFR gene, deletion of PTEN and TP53 genes, and 1p/19q deficiency in a sample of adult patients diagnosed with glioblastoma from Southern Brazil

A combined diffusion tensor imaging and Ki-67 labeling index study for evaluating the extent of tumor infiltration using the F98 rat glioma model

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