Classification Of Diffuse Gliomas Research Articles

Conventional MRI-Derived Biomarkers of Adult-Type Diffuse Glioma Molecular Subtypes: A Comprehensive Review.

The introduction of molecular criteria into the classification of diffuse gliomas has added interesting practical implications to glioma management. This has created a new clinical need for correlating imaging characteristics with glioma genotypes, also known as radiogenomics or imaging genomics. Although many studies have primarily focused on the use of advanced magnetic resonance imaging (MRI) techniques for radiogenomics purposes, conventional MRI sequences remain the reference point in the study and characterization of brain tumors. A summary of the conventional imaging features of glioma molecular subtypes should be useful as a tool for daily diagnostic brain tumor management. Hence, this article aims to summarize the conventional MRI features of glioma molecular subtypes in light of the recent literature.

Clinical Laboratory Testing Practices in Diffuse Gliomas Prior to Publication of 2021 World Health Organization Classification of Central Nervous System Tumors.

Integration of molecular data into glioma classification supports diagnostic, prognostic, and therapeutic decision-making; however, testing practices for these informative biomarkers in clinical laboratories remain unclear. To examine the prevalence of molecular testing for clinically relevant biomarkers in adult and pediatric gliomas through review of a College of American Pathologists proficiency testing survey prior to the release of the 2021 World Health Organization Classification of Central Nervous System Tumors. College of American Pathologists proficiency testing 2020 survey results from 96 laboratories performing molecular testing for diffuse gliomas were used to determine the use of testing for molecular biomarkers in gliomas. The data provide perspective into the testing practices for diffuse gliomas from a broad group of clinical laboratories in 2020. More than 98% of participating laboratories perform testing for glioma biomarkers recognized as diagnostic for specific subtypes, including IDH. More than 60% of laboratories also use molecular markers to differentiate between astrocytic and oligodendroglial lineage tumors, with some laboratories providing more comprehensive analyses, including prognostic biomarkers, such as CDKN2A/B homozygous deletions. Almost all laboratories test for MGMT promoter methylation to identify patients with an increased likelihood of responding to temozolomide. These findings highlight the state of molecular testing in 2020 for the diagnosis and classification of diffuse gliomas at large academic medical centers. The findings show that comprehensive molecular testing is not universal across clinical laboratories and highlight the gaps between laboratory practices in 2020 and the recommendations in the 2021 World Health Organization Classification of Central Nervous System Tumors.

Molecular Subtyping of Diffuse Gliomas Using Magnetic Resonance Imaging: Comparison and Correlation Between Radiomics and Deep Learning

The 2016 WHO classification of diffuse gliomas is significant. The aim of this study was to establish comprehensive predictive models based on preoperative multi-parametric MRI. A total of 1,016 diffuse glioma patients were retrospectively collected from Beijing Tiantan Hospital, China. The patients were randomly divided into a training set (n = 780) and an internal validation set (n = 236). According to the 2016 WHO classification, the diffuse gliomas can be categorized according to four binary classification tasks (tasks I—IV). Predictive models based on radiomics and deep convolutional neural networks (DCNN) were developed respectively, and their performances were compared using receiver operating characteristic (ROC) curves. Additionally, the radiomics and DCNN features were visualized and compared based on t-distributed stochastic neighbor embedding technique and Spearman’s rank-correlation test. In the training set, areas under the curves (AUCs) of the DCNN models (ranging from 0.99—1.00) outperformed those of the radiomics models in all conducted tasks. In the independent validation set, the AUCs of the DCNN models outperformed those of the radiomics models in tasks I, II, and III. DCNN features demonstrated superior discriminative capability compared to radiomics features based on feature visualization analysis, and their general correlations were weak. In conclusion, both the radiomics and DCNN models could preoperatively predict the molecular subtypes of diffuse gliomas, but the latter models performed better in most circumstances. Funding Statement: This study was supported by the National Natural Science Foundation of China (No. 81601452). Declaration of Interests: No conflict of interest to declare. Ethics Approval Statement: Ethical approval for this retrospective study was received from the institutional review board of the Beijing Tiantan Hospital.

A radical shift in the diagnostic approach to diffuse gliomas

Astrocytic tumours comprise the majority of central nervous system tumours and they have been traditionally graded as recommended by World Health Organization on the basis of atypia, mitoses, microvascular proliferation and necrosis. The 2016 WHO classification of diffuse gliomas incorporates both molecular and histological criteria to categorize these tumours to better predict behavior. A layered diagnostic format is now the recommended approach with the WHO grade being assigned on histological criteria to be supplemented by molecular characterization once the result of isocitrate dehydrogenase is available. The presence of 1p/19q-codeletion has now been included in the definition of oligodendrogliomas. Oligoastrocytomas have now almost vanished as an entity because they are classified as either astrocytomas or oligodendrogliomas after molecular testing. Tests have to be modified in resource limited settings to reach a molecular diagnosis based on new scientific literature and research.

RNA editing-based classification of diffuse gliomas: predicting isocitrate dehydrogenase mutation and chromosome 1p/19q codeletion

BackgroundAccurate classification of diffuse gliomas, the most common tumors of the central nervous system in adults, is important for appropriate treatment. However, detection of isocitrate dehydrogenase (IDH) mutation and chromosome1p/19q codeletion, biomarkers to classify gliomas, is time- and cost-intensive and diagnostic discordance remains an issue. Adenosine to inosine (A-to-I) RNA editing has emerged as a novel cancer prognostic marker, but its value for glioma classification remains largely unexplored. We aim to (1) unravel the relationship between RNA editing and IDH mutation and 1p/19q codeletion and (2) predict IDH mutation and 1p/19q codeletion status using machine learning algorithms.ResultsBy characterizing genome-wide A-to-I RNA editing signatures of 638 gliomas, we found that tumors without IDH mutation exhibited higher total editing level compared with those carrying it (Kolmogorov-Smirnov test, p < 0.0001). When tumor grade was considered, however, only grade IV tumors without IDH mutation exhibited higher total editing level. According to 10-fold cross-validation, support vector machines (SVM) outperformed random forest and AdaBoost (DeLong test, p < 0.05). The area under the receiver operating characteristic curve (AUC) of SVM in predicting IDH mutation and 1p/19q codeletion were 0.989 and 0.990, respectively. After performing feature selection, AUCs of SVM and AdaBoost in predicting IDH mutation were higher than that of random forest (0.985 and 0.983 vs. 0.977; DeLong test, p < 0.05), but AUCs of the three algorithms in predicting 1p/19q codeletion were similar (0.976–0.982). Furthermore, 67% of the six continuously misclassified samples by our 1p/19q codeletion prediction models were misclassifications in the original labelling after inspection of 1p/19q status and/or pathology report, highlighting the accuracy and clinical utility of our models.ConclusionsThe study represents the first genome-wide analysis of glioma editome and identifies RNA editing as a novel prognostic biomarker for glioma. Our prediction models provide standardized, accurate, reproducible and objective classification of gliomas. Our models are not only useful in clinical decision-making, but also able to identify editing events that have the potential to serve as biomarkers and therapeutic targets in glioma management and treatment.

Clinical insights gained by refining the 2016 WHO classification of diffuse gliomas with: EGFR amplification, TERT mutations, PTEN deletion and MGMT methylation

BackgroundSignificant advances in the molecular profiling of gliomas, led the 2016 World Health Organization (WHO) Classification to include, for the first-time, molecular biomarkers in glioma diagnosis: IDH mutations and 1p/19q codeletion. Here, we evaluated the effect of this new classification in the stratification of gliomas previously diagnosed according to 2007 WHO classification. Then, we also analyzed the impact of TERT promoter mutations, PTEN deletion, EGFR amplification and MGMT promoter methylation in diagnosis, prognosis and response to therapy in glioma molecular subgroup.MethodsA cohort of 444 adult gliomas was analyzed and reclassified according to the 2016 WHO. Mutational analysis of IDH1 and TERT promoter mutations was performed by Sanger sequencing. Statistical analysis was done using SPSS Statistics 21.0.ResultsThe reclassification of this cohort using 2016 WHO criteria led to a decrease of the number of oligodendrogliomas (from 82 to 49) and an increase of astrocytomas (from 49 to 98), while glioblastomas (GBM) remained the same (n = 256). GBM was the most common diagnosis (57.7%), of which 55.2% were IDH-wildtype. 1p/19q codeleted gliomas were the subgroup associated with longer median overall survival (198 months), while GBM IDH-wildtype had the worst outcome (10 months). Interestingly, PTEN deletion had poor prognostic value in astrocytomas IDH-wildtype (p = 0.015), while in GBM IDH-wildtype was associated with better overall survival (p = 0.042) as well as MGMT promoter methylation (p = 0.009). EGFR amplification and TERT mutations had no impact in prognosis. Notably, EGFR amplification predicted a better response to radiotherapy (p = 0.011) and MGMT methylation to chemo-radiotherapy (p = 0.003).ConclusionIn this study we observed that the 2016 WHO classification improved the accuracy of diagnosis and prognosis of diffuse gliomas, although the available biomarkers are not enough. Therefore, we suggest MGMT promoter methylation should be added to glioma classification. Moreover, we found two genetic/clinical correlations that must be evaluated to understand their impact in the clinical setting: i) how is PTEN deletion a favorable prognostic factor in GBM IDH wildtype and an unfavorable prognostic factor in astrocytoma IDH wildtype and ii) how EGFR amplification is an independent and strong factor of response to radiotherapy.

Clinical evaluation of a dedicated next generation sequencing panel for routine glioma diagnostics

Since 2013 next-generation sequencing (NGS) targeting genes mutated in diffuse gliomas is part of routine diagnostics in our institute. In the present report, we evaluate the use of this custom tailored NGS platform on 434 samples. The NGS panel assesses mutations in ATRX, CIC, EGFR, FUBP1, NOTCH1, PTEN; H3F3A, IDH1/2, PIK3CA, and BRAF, amplifications in EGFR or MDM2 and copy number alterations (CNA) of chromosome 1p, 7, 10 and 19q. TERT promoter mutations were assessed separately when indicated. Of the 433 samples of individual tumors with NGS data available, 176 cases were diagnosed as grade 2 or 3 glioma (40.6) and in 201 patients a glioblastoma (46.4%). Of the remaining 56 patients, 22 had inconclusive histology. In 378 cases (87.1%) a diagnosis solely based on glioma-targeted NGS could be established and resulted in a different diagnosis in ~ 1/4 of the cases. In 17 out of 22 cases without a conclusive histological diagnosis NGS resulted in a molecular diagnosis.The current study on a large cohort of patients confirms the diagnostic strength of the platform we developed, with a clear separation of glioma subgroups with different outcomes. It demonstrates the diagnostic value and the efficiency of glioma-targeted NGS for routine glioma diagnostics allowing with a single assay a glioma diagnosis in the large majority of cases. It allows in one run the molecular assessments required for the WHO classification of diffuse gliomas, including the recent recommendations to assess copy number alterations of chromosome 7 and 10, and of the TERT promoter region in IDHwt lower grade glioma.

Study of Histomolecular Classification of Glioma-Integrating Histology and Molecular Analysis in the Diagnosis of Brain Tumors

Abstract Introduction The updated 2016 classification of gliomas incorporates well-established molecular parameters into the classification of diffuse gliomas, taking into account isocitrate dehydrogenase 1 (IDH1) mutation, α-thalassemia/mental retardation syndrome X-linked (ATRX) loss, and 1p/19q co-deletion. Aim and Objectives To study IDH1 and ATRX mutations in gliomas, 1p/19q co-deletion by fluorescent in situ hybridization (FISH) in oligodendroglioma, and to correlate IDH1, ATRX, and 1p/19q with tumor type and grade. Material and Methods Total 73 cases of gliomas were diagnosed on histology and graded as astrocytoma (grades 2–4), oligodendroglioma (grades 2–3), and oligoastrocytoma (grades 2–3) by two pathologists independently. IDH mutation and ATRX expression were analyzed using immunohistochemistry in all cases whereas 1p/19q co-deletion was studied using FISH in cases with oligodendroglioma and oligoastrocytoma morphology. Results Total 48 cases of astrocytoma, 9 cases of oligoastrocytoma, and 16 cases of oligodendroglioma were included. The maximum number of IDH1 mutation cases were seen in diffuse astrocytoma (7/10; 70%) as compared with anaplastic astrocytoma (5/15; 33.33%), glioblastoma multiforme (GBM) (3/23; 13.04%) grade II oligoastrocytoma (3/6; 50%), anaplastic oligoastrocytoma (2/3; 66.67%), and oligodendroglioma grade II (7/10; 70%). ATRX loss was seen in diffuse astrocytoma grade II (6/10; 60%), anaplastic astrocytoma (6/15; 40%), oligoastrocytoma grade II (2/6; 33.33%), and anaplastic oligoastrocytoma (1/3; 33.33%). 1p/19q co-deletion was seen in oligoastrocytoma (2/2; 100%), anaplastic oligoastrocytoma (1/2; 50%), oligodendroglioma (3/4; 75%), and anaplastic oligodendroglioma (1/3; 33.33%). Six of the seven cases with 1p/19q co-deletion also showed IDH1 mutation. One of seven 1p/19q co-deleted cases had loss of expression of ATRX. Conclusion Incorporation of IDH1 mutation, ATRX loss, and 1p/19q co-deletion molecular studies help in a more accurate diagnosis and classification of gliomas.

Practical Implications of the Updated WHO Classification of Brain Tumors.

The updated 2016 WHO classification of Central Nervous System tumors introduced a novel concept of neuropathology diagnostics. Molecular parameters are now included into the definition of several entities. This evolution from a previously purely histology-based classification to an integrated approach of histology and genetic characteristics has implications in daily diagnostic and clinical practice. Both the spectrum of diagnostic workup demanded from the neuropathologist and the range of relevant markers to be considered by clinicians and clinical investigators have increased. This article reviews the major changes in the classification of diffuse gliomas, ependymoma, and medulloblastoma, the practical consequences for diagnostics and clinical trials, and points toward recent developments that potentially will influence the next update of the classification.

Current therapeutic approaches to diffuse grade II and III gliomas.

The 2016 WHO classification of Tumors of the Central Nervous System brought major conceptual and practical changes in the classification of diffuse gliomas, by combining molecular features and histology into ‘integrated’ diagnoses. In diffuse gliomas, molecular profiling has thus become essential for nosological purposes, as well as to plan adequate treatment strategies and identify patients susceptible of target therapy. WHO grade II (low grade) and grade III (anaplastic) diffuse gliomas form a heterogeneous group of neoplasms, also known as ‘lower-grade gliomas’, characterized by a wide range of malignant potential. Molecular profile accounts for this biological diversity, and provides an accurate prognostic stratification of tumors in this group. Treatment strategies in lower-grade gliomas are ultimately based on molecular profile and WHO grade, as well as on patient characteristics such as age and Karnofsky performance status. The purpose of this review is to summarize recent advances in the classification of grade II and III gliomas, synthesize current treatment schemes according to molecular profile and describe ongoing research and future perspectives for the use of target therapies.

Multidimensional scaling of diffuse gliomas: application to the 2016 World Health Organization classification system with prognostically relevant molecular subtype discovery

Recent updating of the World Health Organization (WHO) classification of central nervous system (CNS) tumors in 2016 demonstrates the first organized effort to restructure brain tumor classification by incorporating histomorphologic features with recurrent molecular alterations. Revised CNS tumor diagnostic criteria also attempt to reduce interobserver variability of histological interpretation and provide more accurate stratification related to clinical outcome. As an example, diffuse gliomas (WHO grades II–IV) are now molecularly stratified based upon isocitrate dehydrogenase 1 or 2 (IDH) mutational status, with gliomas of WHO grades II and III being substratified according to 1p/19q codeletion status. For now, grading of diffuse gliomas is still dependent upon histological parameters. Independent of WHO classification criteria, multidimensional scaling analysis of molecular signatures for diffuse gliomas from The Cancer Genome Atlas (TCGA) has identified distinct molecular subgroups, and allows for their visualization in 2-dimensional (2D) space. Using the web-based platform Oncoscape as a tool, we applied multidimensional scaling-derived molecular groups to the 2D visualization of the 2016 WHO classification of diffuse gliomas. Here we show that molecular multidimensional scaling of TCGA data provides 2D clustering that represents the 2016 WHO classification of diffuse gliomas. Additionally, we used this platform to successfully identify and define novel copy-number alteration-based molecular subtypes, which are independent of WHO grading, as well as predictive of clinical outcome. The prognostic utility of these molecular subtypes was further validated using an independent data set of the German Glioma Network prospective glioblastoma patient cohort.

Prognostic impact of the 2016 WHO classification of diffuse gliomas in the French POLA cohort.

The new WHO classification of diffuse gliomas has been refined and now includes the 1p/19q codeletion, IDH1/2 mutation, and histone H3-K27M mutation. Our objective was to assess the prognostic value of the updated 2016 WHO classification in the French POLA cohort. All cases of high-grade oligodendroglial tumors sent for central pathological review and included into the French nationwide POLA cohort were reclassified according to the updated 4th WHO classification. In total, 1041 patients were included, with a median age at diagnosis of 50.4years (range 17.1-84.4). Based on the new histomolecular classification, diagnoses included anaplastic oligodendroglioma IDH mutant and 1p/19q-codeleted (32.5%), anaplastic astrocytoma IDH mutant (IDH (mut)) (11.0%), anaplastic astrocytoma IDH wild type (IDH (wt)) (5.3%), glioblastoma IDH (mut) (17.1%), and glioblastoma IDH (wt) (33.2%). Ten patients presented with a diffuse midline tumor, H3 K27M mutant. The new WHO classification was prognostic for progression-free survival (PFS) and overall survival (OS) (p<0.001). We did not find prognosis differences between grades III and IV for IDH (mut) 1p/19q intact and IDH (wt) gliomas in univariate and multivariate analyses. Among anaplastic astrocytoma IDH (wt), cases with chromosome arm 7p gain and 10q loss (55%) had shorter PFS than the others (p=0.027). In conclusion, the new WHO histomolecular classification of diffuse gliomas presented with high prognostic value. Grading was not discriminant between grade III and IV high-grade gliomas.

The next step in brain tumor classification: “Let us now praise famous men”… or molecules?

The next step in brain tumor classification: “Let us now praise famous men”… or molecules?

Klassifikation und Dokumentation diffuser Gliome

Most current grading systems of diffuse gliomas are based solely on the microscopic evaluation of surgical specimens and the TNM classification does not have a value for brain tumors. Here additional parameters are presented, which are suitable for a classification and documentation of diffuse gliomas. As additional parameters to the WHO typing and grading we discuss age groups, different tumor devolutions, circumstances such as a second malignant neoplasm or hereditary tumors, tumor expansion based on anatomically defined brain regions, Karnofsky Scale, eloquence of the brain regions, diag-nostic certainty and informativity of tissue samples. This work shows that clinical data and imaging studies can contribute substantially to the classification of diffuse gliomas. The additional parameters presented here constitute a significant improvement of glioma documentation. Especially complex courses of long duration and repeated therapeutic interventions can be better surveyed and digitally processed.

Molecular classification of diffuse gliomas by gene expression profiling is gaining momentum

Molecular classification of diffuse gliomas by gene expression profiling is gaining momentum