Clinical significance of the 2016 WHO classification in Japanese patients with gliomas

Post-chemo-radiotherapy response and pseudo-progression evaluation on glioma cell types by multi-parametric magnetic resonance imaging: a prospective study

BACKGROUND

We focused on Differentiated pseudoprogression (PPN) of progression (PN) and the response to radiotherapy (RT) or chemoradiotherapy (CRT) using diffusion and metabolic imaging.

METHODS

Seventy-five patients with glioma were included in this prospective study (approved by the Iranian Registry of Clinical Trials (IRCT) (IRCT20230904059352N1) in September 2023). Contrast-enhanced lesion volume (CELV), non-enhanced lesion volume (NELV), necrotic tumor volume (NTV), and quantitative values ​​of apparent diffusion coefficient (ADC) and magnetic resonance spectroscopy (Cho/Cr, Cho/NAA and NAA/Cr) were calculated by a neuroradiologist using a semi-automatic method. All patients were followed at one and six months after CRT.

RESULTS

The results of the study showed statistically significant changes before and six months after RT-CRT for M-CELV in all glioma types (𝑝 < 0.05). In glioma cell types, the changes in M-ADC, M-Cho/Cr, and Cho/NAA indices for PN were incremental and greater for PPN patients. M-NAA/Cr ratio decreased after six months which was significant only on PN for GBM, and Epn (𝑝 < 0.05). A significant difference was observed between diffusion indices, metabolic ratios, and CELV changes after six months in all types (𝑝 < 0.05). None of the patients were suspected PPN one month after treatment. The DWI/ADC indices had higher sensitivity and specificity (98.25% and 96.57%, respectively).

CONCLUSION

The results of the present study showed that ADC values and Cho/Cr and Cho/NAA ratios can be used to differentiate between patients with PPN and PN, although ADC is more sensitive and specific.

Bayesian Depth-Wise Convolutional Neural Network Design for Brain Tumor MRI Classification

In recent years, deep learning has been applied to many medical imaging fields, including medical image processing, bioinformatics, medical image classification, segmentation, and prediction tasks. Computer-aided detection systems have been widely adopted in brain tumor classification, prediction, detection, diagnosis, and segmentation tasks. This work proposes a novel model that combines the Bayesian algorithm with depth-wise separable convolutions for accurate classification and predictions of brain tumors. We combine Bayesian modeling learning and Convolutional Neural Network learning methods for accurate prediction results to provide the radiologists the means to classify the Magnetic Resonance Imaging (MRI) images rapidly. After thorough experimental analysis, our proposed model outperforms other state-of-the-art models in terms of validation accuracy, training accuracy, F1-score, recall, and precision. Our model obtained high performances of 99.03% training accuracy and 94.32% validation accuracy, F1-score, precision, and recall values of 0.94, 0.95, and 0.94, respectively. To the best of our knowledge, the proposed work is the first neural network model that combines the hybrid effect of depth-wise separable convolutions with the Bayesian algorithm using encoders.

Grading of IDH-mutant astrocytoma using diffusion, susceptibility and perfusion-weighted imaging

Background

The accurate grading of IDH-mutant astrocytoma is essential to make therapeutic strategies and assess the prognosis of patients. The purpose of this study was to investigate the usefulness of DWI, SWI and DSC-PWI in grading IDH-mutant astrocytoma.

Methods

One hundred and seven patients with IDH-mutant astrocytoma who underwent DWI, SWI and DSC-PWI were retrospectively reviewed. Minimum apparent diffusion coefficient (ADC_min), intratumoral susceptibility signal intensity(ITSS) and maximum relative cerebral blood volume (rCBV_max) values were assessed. ADC_min, ITSS and rCBV_max values were compared between grade 2 vs. grade 3, grade 3 vs. grade 4 and grade 2 + 3 vs. grade 4 tumors. Logistic regression, tenfold cross-validation,and receiver operating characteristic (ROC) curve analyses were used to assess their diagnostic performances.

Results

Grade 4 IDH-mutant astrocytomas showed significantly lower ADC_min and higher rCBV_max as compared to grade 3 tumors (adjusted P < 0.001). IDH-mutant grade 3 astrocytomas showed significantly lower ITSS levels as compared with grade 4 tumors (adjusted P < 0.001). ITSS levels between IDH-mutant grade 2 and grade 3 astrocytomas were significantly different (adjusted P = 0.002). Combined the ADC_min, ITSS and rCBV_max resulted in the highest AUC for differentiation grade 2 and grade 3 tumors from grade 4 tumors.

Conclusion

ADC_min, rCBV_max and ITSS can be used for grading the IDH-mutant astrocytomas. The combination of ADC_min, ITSS and rCBV_max could improve the diagnostic performance in grading of IDH-mutant astrocytoma.

The Use of Pro-Angiogenic and/or Pro-Hypoxic miRNAs as Tools to Monitor Patients with Diffuse Gliomas

IDH (isocitrate dehydrogenase) mutation, hypoxia, and neo-angiogenesis, three hallmarks of diffuse gliomas, modulate the expression of small non-coding RNAs (miRNA). In this paper, we tested whether pro-angiogenic and/or pro-hypoxic miRNAs could be used to monitor patients with glioma. The miRNAs were extracted from tumoral surgical specimens embedded in the paraffin of 97 patients with diffuse gliomas and, for 7 patients, from a blood sample too. The expression of 10 pro-angiogenic and/or pro-hypoxic miRNAs was assayed by qRT-PCR and normalized to the miRNA expression of non-tumoral brain tissues. We confirmed in vitro that IDH in hypoxia (1% O₂, 24 h) alters pro-angiogenic and/or pro-hypoxic miRNA expression in HBT-14 (U-87 MG) cells. Then, we reported that the expression of these miRNAs is (i) strongly affected in patients with glioma compared to that in a non-tumoral brain; (ii) correlated with the histology/grade of glioma according to the 2016 WHO classification; and (iii) predicts the overall and/or progression-free survival of patients with glioma in univariate but not in a multivariate analysis after adjusting for sex, age at diagnosis, and WHO classification. Finally, the expression of miRNAs was found to be the same between the plasma and glial tumor of the same patient. This study highlights a panel of seven pro-angiogenic and/or pro-hypoxic miRNAs as a potential tool for monitoring patients with glioma.

PIK3CA Mutations in Diffuse Gliomas: An Update on Molecular Stratification, Prognosis, Recurrence, and Aggressiveness

Introduction:

PIK3CA is one of the most mutated oncogenes in solid tumors. In breast cancer (ER-positive, HER2-negative), these events represent a predictive biomarker of response to alpelisib. In glioblastomas (GBM), PIK3CA mutations were described as early constitutive events. Here, we investigated PIK3CA mutational profile across glioma molecular subgroups and its relevance during glioma recurrence. Furthermore, PIK3CA mutations’ effect in PI3K pathway, prognosis, and response to therapy was also explored.

Material and Methods:

Exons 10 and 21 of PIK3CA mutations were evaluated in 394 gliomas and 19 glioma recurrences from Instituto Português de Oncologia Lisboa Francisco Gentil (IPOLFG) and compared with The Cancer Genome Atlas (TCGA) data. TIMER2.0 and NetMHCpan4.1 were used to assess the immune-microenvironment contribution.

Results:

PIK3CA mutations were identified among all glioma subgroups, although with no impact on their stratification or prognosis. In both cohorts (IPOLFG and TCGA), PIK3CA mutation frequencies in IDH-mutant and IDH-wild-type GBM were similar (IPOLFG: 9% and 3%; TCGA: 8% and 2%). These mutations were not mutually exclusive with PTEN deletion and EGFR amplification. Despite their reduced frequency, we discovered PIK3CA mutations were maintained during glioma recurrence regardless of administered therapies. The immune microenvironment might not contribute to this phenotype as PIK3CA mutations did not influence immune cell infiltration.

Conclusions:

Despite the absence of a predominant effect in glioma stratification, PIK3CA mutations were maintained during glioma recurrence, possibly contributing to glioma cell survival, representing promising therapeutic targets in recurrent glioma. Nevertheless, understanding the potential synergistic effects between PIK3CA mutations, PTEN deletion, and EGFR amplification is pivotal to targeted therapies’ efficiency.

Molecular subtyping of diffuse gliomas using magnetic resonance imaging: comparison and correlation between radiomics and deep learning

OBJECTIVES

The molecular subtyping of diffuse gliomas is important. The aim of this study was to establish predictive models based on preoperative multiparametric MRI.

METHODS

A total of 1016 diffuse glioma patients were retrospectively collected from Beijing Tiantan Hospital. Patients were randomly divided into the training (n = 780) and validation (n = 236) sets. According to the 2016 WHO classification, diffuse gliomas can be classified into four binary classification tasks (tasks I-IV). Predictive models based on radiomics and deep convolutional neural network (DCNN) were developed respectively, and their performances were compared with receiver operating characteristic (ROC) curves. Additionally, the radiomics and DCNN features were visualized and compared with the t-distributed stochastic neighbor embedding technique and Spearman's correlation test.

RESULTS

In the training set, areas under the curves (AUCs) of the DCNN models (ranging from 0.99 to 1.00) outperformed the radiomics models in all tasks, and the accuracies of the DCNN models (ranging from 0.90 to 0.94) outperformed the radiomics models in tasks I, II, and III. In the independent validation set, the accuracies of the DCNN models outperformed the radiomics models in all tasks (0.74-0.83), and the AUCs of the DCNN models (0.85-0.89) outperformed the radiomics models in tasks I, II, and III. DCNN features demonstrated more superior discriminative capability than the radiomics features in feature visualization analysis, and their general correlations were weak.

CONCLUSIONS

Both the radiomics and DCNN models could preoperatively predict the molecular subtypes of diffuse gliomas, and the latter performed better in most circumstances.

KEY POINTS

• The molecular subtypes of diffuse gliomas could be predicted with MRI. • Deep learning features tend to outperform radiomics features in large cohorts. • The correlation between the radiomics features and DCNN features was low.

Molecular biomarkers and integrated pathological diagnosis in the reclassification of gliomas

The present study aimed to evaluate the impact caused by the 2016 World Health Organization (WHO) diagnostic classification of gliomas in 139 patients studied in Argentina. Formalin-fixed paraffin-embedded tissues were used for histological and immunohistochemical analysis [glial fibrillary acidic protein, KI67, synaptophysin and isocitrate dehydrogenase (IDH)1-R132H]. DNA from formalin-fixed paraffin-embedded tissues was used for molecular analysis: 1p/19q co-deletion and mutation status of the IDH gene. These experiments were performed by direct Sanger sequencing and multiplex ligation-dependent probe amplification. According to the new classification, diagnoses included oligodendroglioma IDH-mutant and 1p/19q co-deletion (4.20%), anaplastic oligodendroglioma IDH-mutant and 1p/19q co-deletion (2.52%), diffuse astrocytoma IDH-mutant (6.72%), diffuse astrocytoma IDH-wild type (1.68%), anaplastic astrocytoma IDH-mutant (5.04%), anaplastic astrocytoma IDH-wild type (8.40%), glioblastoma IDH-mutant (5.88%) and glioblastoma IDH-wild type (65.56%). Regarding tumor histology, 60% of oligodendrogliomas, 35% of astrocytoma and 100% of unclassified gliomas were re-classified, while glioblastomas maintained their initial classification. Additionally, the present study evaluated the prognostic value of the histological grade for the 2007 and 2016 WHO classifications of gliomas. The histological subgroup associated with longer overall survival (OS) was grade II glioma (OS-2007WHO, 35.6 months; and OS-2016WHO, 47.7 months). Glioblastoma was the subgroup associated with a poor outcome (OS-2007WHO, 10.4 months; and OS-2016WHO, 11.1 months). The present study evaluated the OS of tumor grade subgroups with respect to their IDH status. For all subgroups, IDH-mutant tumors were associated with an improved prognosis compared with IDH-wild type tumors. The results suggested that the incorporation of molecular biomarkers in the new WHO classification improves tumor characterization and prognostic value of the subgroups.

Take Advantage of Glutamine Anaplerosis, the Kernel of the Metabolic Rewiring in Malignant Gliomas

Glutamine is a non-essential amino acid that plays a key role in the metabolism of proliferating cells including neoplastic cells. In the central nervous system (CNS), glutamine metabolism is particularly relevant, because the glutamine-glutamate cycle is a way of controlling the production of glutamate-derived neurotransmitters by tightly regulating the bioavailability of the amino acids in a neuron-astrocyte metabolic symbiosis-dependent manner. Glutamine-related metabolic adjustments have been reported in several CNS malignancies including malignant gliomas that are considered ‘glutamine addicted’. In these tumors, glutamine becomes an essential amino acid preferentially used in energy and biomass production including glutathione (GSH) generation, which is crucial in oxidative stress control. Therefore, in this review, we will highlight the metabolic remodeling that gliomas undergo, focusing on glutamine metabolism. We will address some therapeutic regimens including novel research attempts to target glutamine metabolism and a brief update of diagnosis strategies that take advantage of this altered profile. A better understanding of malignant glioma cell metabolism will help in the identification of new molecular targets and the design of new therapies.

CeRNA Network Analysis Representing Characteristics of Different Tumor Environments Based on 1p/19q Codeletion in Oligodendrogliomas

Simple Summary

Oligodendroglioma (OD) is a subtype of glioma occurring in the central nervous system. The 1p/19q codeletion is a prognostic marker of OD with an isocitrate dehydrogenase (IDH) mutation and is associated with a clinically favorable overall survival (OS). The long non-coding RNAs (lncRNAs) protects the mRNA from degradation by binding with the same miRNA by acting as a competitive endogenous RNA (ceRNA). Recently, although there is an increasing interest in lncRNAs on glioma studies, however, studies regarding their effects on OD and the 1p/19q codeletion remain limited. In our study, we performed in silico analyses using low-grade gliomas from datasets obtained from The Cancer Genome Atlas to investigate the effects of ceRNA with 1p/19q codeletion on ODs. We constructed 16 coding RNA–miRNA–lncRNA networks and the ceRNA network participated in ion channel activity, insulin secretion, and collagen network and extracellular matrix (ECM) changes. In conclusion, our results can provide insights into the possibility in the different tumor microenvironments and OS following 1p/19q codeletion through changes in the ceRNA network.

Abstract

Oligodendroglioma (OD) is a subtype of glioma occurring in the central nervous system. The 1p/19q codeletion is a prognostic marker of OD with an isocitrate dehydrogenase (IDH) mutation and is associated with a clinically favorable overall survival (OS); however, the exact underlying mechanism remains unclear. Long non-coding RNAs (lncRNAs) have recently been suggested to regulate carcinogenesis and prognosis in cancer patients. Here, we performed in silico analyses using low-grade gliomas from datasets obtained from The Cancer Genome Atlas to investigate the effects of ceRNA with 1p/19q codeletion on ODs. Thus, we selected modules of differentially expressed genes that were closely related to 1p/19q codeletion traits using weighted gene co-expression network analysis and constructed 16 coding RNA–miRNA–lncRNA networks. The ceRNA network participated in ion channel activity, insulin secretion, and collagen network and extracellular matrix (ECM) changes. In conclusion, ceRNAs with a 1p/19q codeletion can create different tumor microenvironments via potassium ion channels and ECM composition changes; furthermore, differences in OS may occur. Moreover, if extrapolated to gliomas, our results can provide insights into the consequences of identical gene expression, indicating the possibility of tracking different biological processes in different subtypes of glioma.

Targeted next-generation sequencing of adult gliomas for retrospective prognostic evaluation and up-front diagnostics

AIMS

We aimed to reclassify a population-based cohort of 529 adult glioma patients to evaluate the prognostic impact of the 2016 World Health Organization (WHO) central nervous system tumour classification. Moreover, we evaluated the feasibility of gene panel next-generation sequencing (NGS) in daily diagnostics of 225 prospective glioma patients.

METHODS

The retrospective cohort was reclassified according to WHO 2016 criteria by immunohistochemistry for IDH-R132H, fluorescence in situ hybridization for 1p/19q-codeletion and gene panel NGS. All tumours of the prospective cohort were subjected to NGS analysis up-front.

RESULTS

The entire population-based cohort was successfully reclassified according to WHO 2016 criteria. NGS results were obtained for 98% of the prospective patients. Survival analyses in the population-based cohort confirmed three major prognostic subgroups, that is, isocitrate dehydrogenase (IDH)-mutant and 1p/19q-codeleted oligodendrogliomas, IDH-mutant astrocytomas and IDH-wildtype glioblastomas. The distinction between WHO grade II and III was prognostic in patients with IDH-mutant astrocytoma. The survival of patients with IDH-wildtype diffuse astrocytomas carrying TERT promoter mutation and/or EGFR amplification overlapped with the poor survival of IDH-wildtype glioblastoma patients.

CONCLUSIONS

Gene panel NGS proved feasible in daily diagnostics. In addition, our study confirms the prognostic role of glioma classification according to WHO 2016 in a large population-based cohort. Molecular features of glioblastoma in IDH-wildtype diffuse glioma were linked to poor survival corresponding to IDH-wildtype glioblastoma patients. The distinction between WHO grade II and III retained prognostic significance in patients with IDH-mutant diffuse astrocytic gliomas.

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

BACKGROUND

Significant 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.

METHODS

A 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.

RESULTS

The 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).

CONCLUSION

In 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.

First autopsy analysis of the efficacy of intra-operative additional photodynamic therapy for patients with glioblastoma

The study aim to demonstrate the therapeutic tissue depth of photodynamic therapy (PDT) using the photosensitizer talaporfin sodium and semiconductor laser for malignant glioma from an autopsy finding. Three patients diagnosed with glioblastoma by pre-operative imaging (1 newly diagnosed patient and 2 patients with recurrence) were treated with intra-operative additional PDT and adjuvant therapy such as post-operative radiotherapy or chemotherapy. All three patients died of brain stem dysfunction owing to cerebrospinal fluid dissemination or direct invasion of the tumor cells from 13, 18, or 20 months after PDT. Antemortem magnetic resonance images demonstrated no tumor recurrence in the site of PDT, and autopsy was performed for the pathological analysis. Macroscopic observation demonstrated no tumor recurrence in two patients, but one patient demonstrated tumor recurrence in the therapeutic depth of PDT. Microscopic analysis demonstrated histopathological changes reaching depths of 9, 11, and 18 mm (mean: 12.7 mm) from the surface of the cavity of tumor resection, suggesting the therapeutic tissue depth of PDT to be in this range. This region demonstrated glial scarring with infiltration of T lymphocytes and macrophages, with slight degeneration of small vessel walls. However, viable tumor tissues were observed beyond or around the therapeutic tissue depth of PDT in two patients. PDT for glioblastoma prevented early local recurrence, which suggests the possibility that activation of the immune mechanisms was involved. The therapeutic tissue depth was suggested to be 9-18 mm from the surface of the cavity of tumor resection; however, the viable tumor tissues were demonstrated beyond this therapeutic range.

Reclassification of Mongolian Diffuse Gliomas According to the Revised 2016 World Health Organization Central Nervous System Tumor Classification

Background

The 2016 World Health Organization (WHO) classification of central nervous system (CNS) tumors has been modified to incorporate the IDH mutation and 1p/19q co-deletion in the diagnosis of diffuse gliomas. In this study, we aimed to evaluate the feasibility and prognostic significance of the revised 2016 WHO classification of CNS tumors in Mongolian patients with diffuse gliomas.

Methods

A total of 124 cases of diffuse gliomas were collected, and tissue microarray blocks were made. IDH1 mutation was tested using immunohistochemistry, and 1p/19q co-deletion status was examined using fluorescence in situ hybridization analysis.

Results

According to the 2016 WHO classification, 124 cases of diffuse brain glioma were reclassified as follows: 10 oligodendroglioma, IDH^mut and 1p/19q co-deleted; three anaplastic oligodendroglioma, IDH^mut and 1p/19q co-deleted; 35 diffuse astrocytoma, IDH^mut, 11 diffuse astrocytoma, IDH^wt, not otherwise specified (NOS); 22 anaplastic astrocytoma, IDH^mut, eight anaplastic astrocytoma, IDH^wt, NOS; and 35 glioblastoma, IDH^wt, NOS, respectively. The 2016 WHO classification presented better prognostic value for overall survival in patients with grade II tumors than traditional histological classification. Among patients with grade II tumors, those with oligodendroglioma IDH^mut and 1p/19q co-deleted and diffuse astrocytoma IDH^mut showed significantly higher survival than those with diffuse astrocytoma IDH^wt, NOS (p<.01).

Conclusions

Mongolian diffuse gliomas could be reclassified according to the new 2016 WHO classification. Reclassification revealed substantial changes in diagnosis of both oligodendroglial and astrocytic entities. We have confirmed that the revised 2016 WHO CNS tumor classification has prognostic significance in Mongolian patients with diffuse gliomas, especially those with grade II tumors.

Bridging Cancer Biology with the Clinic: Comprehending and Exploiting IDH Gene Mutations in Gliomas

Isocitrate dehydrogenases 1 and 2 (IDH1/2) are enzymes that play a major role in the Krebs cycle. Mutations in these enzymes are found in the majority of lower gliomas and secondary glioblastomas, but also in myeloid malignancies and other cancers. IDH1 and IDH2 mutations are restricted to specific arginine residues in the active site of the enzymes and are gain-of-function, i.e. they confer a neomorphic enzyme activity resulting in the accumulation of D-2-hydroxyglutarate (2-HG). 2-HG is an oncometabolite causing profound metabolic dysregulation which, among others, results in methylator phenotypes and in defects in homologous recombination repair. In this review, we summarize current knowledge regarding the function of normal and mutated IDH, explain the possible mechanisms through which these mutations might drive malignant transformation of progenitor cells in the central nervous system, and provide a comprehensive review of potential treatment strategies for IDH-mutated malignancies, focusing on gliomas.