Prognostication and Surgical Management of Diffuse Gliomas in the Era of Molecular Diagnostics

Gliomas are the most common type of primary malignant brain tumors. Several subtypes of glioma are recognized by the World Health Organization (WHO), based on histological and molecular criteria. The WHO classification of brain tumors was updated in 2016 and in this thesis the results of several studies on classification and clinical management of lower-grade glioma in the context of these updated WHO criteria are described

PI3 kinase mutations and mutational load as poor prognostic markers in diffuse glioma patients

INTRODUCTION: Recent advances in molecular diagnostics allow diffuse gliomas to be classified based on their genetic changes into distinct prognostic subtypes. However, a systematic analysis of all molecular markers has thus far not been performed; most classification schemes use a predefined and select set of genes/molecular markers. Here, we have analysed the TCGA dataset (combined glioblastoma (GBM) and lower grade glioma (LGG) datasets) to identify all prognostic genetic markers in diffuse gliomas in order to generate a comprehensive classification scheme. RESULTS: Of the molecular markers investigated (all genes mutated at a population frequency >1.7 % and frequent chromosomal imbalances) in the entire glioma dataset, 57 were significantly associated with overall survival. Of these, IDH1 or IDH2 mutations are associated with lowest hazard ratio, which confirms IDH as the most important prognostic marker in diffuse gliomas. Subsequent subgroup analysis largely confirms many of the currently used molecular classification schemes for diffuse gliomas (ATRX or TP53 mutations, 1p19q codeletion). Our analysis also identified PI3-kinase mutations as markers of poor prognosis in IDH-mutated + ATRX/TP53 mutated diffuse gliomas, median survival 3.7 v. 6.3 years (P = 0.02, Hazard rate (HR) 2.93, 95 % confidence interval (CI) 1.16 - 7.38). PI3-kinase mutations were also prognostic in two independent datasets. In our analysis, no additional molecular markers were identified that further refine the molecular classification of diffuse gliomas. Interestingly, these molecular classifiers do not fully explain the variability in survival observed for diffuse glioma patients. We demonstrate that tumor grade remains an important prognostic factor for overall survival in diffuse gliomas, even within molecular glioma subtypes. Tumor grade was correlated with the mutational load (the number of n

Does early resection of presumed low-grade glioma improve survival? A clinical perspective

Early resection is standard of care for presumed low-grade gliomas. This is based on studies including only tumors that were post-surgically confirmed as low-grade glioma. Unfortunately this does not represent the clinicians’ situation wherein he/she has to deal with a lesion on MRI that is suspect for low-grade glioma (i.e. without prior knowledge on the histological diagnosis). We therefore aimed to determine the optimal initial strategy for patients with a lesion suspect for low-grade glioma, but not histologically proven yet. We retrospectively identified 150 patients with a resectable presumed low-grade-glioma and who were otherwise in good clinical condition. In this cohort we compared overall survival between three types of initital treatment strategy: a wait-and-scan approach (n = 38), early resection (n = 83), or biopsy for histopathological verification (n = 29). In multivariate analysis, no difference was observed in overall survival for early resection compared to wait-and-scan: hazard ratio of 0.92 (95% CI 0.43–2.01; p = 0.85). However, biopsy strategy showed a shorter overall survival compared to wait-and-scan: hazard ratio

Survival of diffuse astrocytic glioma, IDH1/2 wildtype, with molecular features of glioblastoma, WHO grade IV: a confirmation of the cIMPACT-NOW criteria

BACKGROUND: The Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy (cIMPACT-NOW) has recommended that isocitrate dehydrogenase 1 and 2 wildtype (IDH1/2wt) diffuse lower-grade gliomas (LGGs) World Health Organization (WHO) grade II or III that present with (i) a telomerase reverse transcriptase promoter mutation (pTERTmt), and/or (ii) gain of chromosome 7 combined with loss of chromosome 10, and/or (iii) epidermal growth factor receptor (EGFR) amplification should be reclassified as diffuse astrocytic glioma, IDH1/2 wildtype, with molecular features of glioblastoma, WHO grade IV (IDH1/2wt astrocytomas WHO IV). This paper describes the overall survival (OS) of IDH1/2wt astrocytoma WHO IV patients, and more in detail patients with tumors with pTERTmt only. METHODS: In this retrospective multicenter study, we compared the OS of 71 IDH1/2wt astrocytomas WHO IV patients, with radiological characteristics of LGGs, with the OS of 197 IDH1/2wt glioblastoma patients. Moreover, we compared the OS of 22 pTERTmt only astrocytoma patients with the OS of the IDH1/2wt glioblastoma patients. RESULTS: Median OS was similar for IDH1/2wt astrocytoma WHO IV patients (23.8 mo) and IDH1/2wt glioblastoma patients (19.2 mo) (Cox proportional hazards model: hazard ratio [HR] 1.27, 95% CI: 0.85-1.88, P = 0.242). OS was also similar in patients with IDH1/2wt astrocytomas WHO IV, pTERTmt only, and IDH1/2wt glioblastomas (HR 1.15, 95% CI: 0.64-2.10, P = 0.641). CONCLUSIONS: The presented data confirm the cIMPACT-NOW recommendation and we propose that IDH1/2wt astrocytomas WHO IV in the absence of other qualifying mutations should be classified as IDH1/2wt glioblastomas

The T2-FLAIR mismatch sign as an imaging marker for non-enhancing IDH-mutant, 1p/19q-intact lower-grade glioma: A validation study

Background. The purpose of this study was to assess the reproducibility of the previously describedT2–fluid attenuated inversion recovery (FLAIR) mismatch sign as a specific imaging marker in non-enhancing isocitrate dehydrogenase (IDH) mutant, 1p/19q non-codeleted lower-grade glioma (LGG), encompassing both diffuse and anaplastic astrocytoma. Methods. MR scans (n = 154) from 3 separate databases with genotyped LGG were evaluated by 2 independent reviewers to assess (i) presence/absence of “T2-FLAIR mismatch” sign and (ii) presence/absence of homogeneous signal onT2-weighted images. Interrater agreement with Cohen's kappa (κ) was calculated, as well as diagnostic test performance of theT2-FLAIR mismatch sign to identify IDH-mutant astrocytoma. Results. There was substantial interrater agreement for theT2-FLAIR mismatch sign [κ = 0.75 (0.64–0.87)], but only fair agreement forT2 homogeneity [κ = 0.38 (0.25–0.52)].TheT2-FLAIR mismatch sign was present in 38 cases (25%) and had a positive predictive value of 100%, negative predictive value of 68%, a sensitivity of 51%, and a specificity of 100%. Conclusions. With a robust interrater agreement, our study confirms that among non-enhancing LGG theT2-FLAIR mismatch sign represents a highly specific imaging marker for IDH-mutant astrocytoma.This non-invasive marker may enable a more informed patient counsel and can aid in the treatment decision processes in a significant proportion of patients presenting with non-enhancing, LGG-like lesions

The Erasmus Glioma Database (EGD)

The Erasmus Glioma Database (EGD) contains structural magnetic resonance imaging (MRI) scans, genetic and histological features (specifying the WHO 2016 subtype), and whole tumor segmentations of patients with glioma. Pre-operative MRI data of 774 patients with glioma (281 female, 492 male, 1 unknown, age range 19–86 years) treated at the Erasmus MC between 2008 and 2018 is available. For all patients a pre-contrast T1-weighted, post-contrast T1-weighted, T2-weighted, and T2-weighted FLAIR scan are available, made on a variety of scanners from four different vendors. All scans are registered to a common atlas and defaced. Genetic and histological data consists of the IDH mutation status (available for 467 patients), 1p/19q co-deletion status (available for 259 patients), and grade (available for 716 patients). The full WHO 2016 subtype is available for 415 patients. Manual segmentations are available for 374 patients and automatically generated segmentations are available for 400 patients. The dataset can be used to relate the visual appearance of the tumor on the scan with the genetic and histological features, and to develop automatic segmentation methods.</p