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Mutant isocitrate dehydrogenase (IDH) in chondrosarcoma produces the oncometabolite 2-hydroxyglutarate (2-HG) and contributes to malignant progression, and is therefore a potential therapeutic target for chondrosarcoma. Robust historical control data are important in clinical trials of rare cancers such as chondrosarcoma in order to show a clear benefit of new drugs. However, it remains controversial whether IDH mutation status is associated with the clinical outcome of chondrosarcoma, and this hinders the development of mutant IDH inhibitors in clinical trials.background METHODS: We investigated the relationship between IDH gene status and clinicopathological data in 38 chondrosarcoma patients from whom frozen tumor samples were obtained at the time of biopsy or surgery. Targeted next-generation sequencing was also performed to compare genetic alterations between patients with and without IDH mutations.The results revealed 15 cases (40%) of heterozygous IDH1 mutations and five cases (13%) of IDH2 mutations. IDH-mutant chondrosarcoma was associated with worse overall survival than IDH-wild-type chondrosarcoma (IDH1/2 Mut vs. IDH Wt, P = 0.006; IDH1 Mut vs. IDH Wt, P = 0.030; IDH2 Mut vs. IDH Wt, P 0.0001). IDH mutation was also a significant poor prognostic factor both in univariate (P = 0.026) and multivariate (P = 0.048) analyses. Targeted next-generation sequencing revealed that characteristic mutations in chondrosarcoma, including TP53 and COL2A1, were more common in the IDH-mutant group than in the IDH-wild-type group.results CONCLUSION: This study is the first to report in detail the characteristics and clinical courses of IDH-mutant chondrosarcoma patients in Japan. Our data suggested that IDH-mutant chondrosarcomas might have a worse prognosis than that of IDH-wild-type chondrosarcoma, possibly through the more aggressive characters after metastasis. This information will be useful for designing clinical trials of mutant IDH inhibitors for treatment of advanced chondrosarcoma.

Gliomas can be classified into five molecular groups based on the status of IDH mutation, 1p/19q codeletion, and TERT promoter mutation, whereas they need to be obtained by biopsy or surgery. Thus, we aimed to use MRI-based radiomics to noninvasively predict the molecular groups and assess their prognostic value. We retrospectively identified 357 patients with gliomas and extracted radiomic features from their preoperative MRI images. Single-layered radiomic signatures were generated using a single MR sequence using Bayesian-regularization neural networks. Image fusion models were built by combing the significant radiomic signatures. By separately predicting the molecular markers, the predictive molecular groups were obtained. Prognostic nomograms were developed based on the predictive molecular groups and clinicopathologic data to predict progression-free survival (PFS) and overall survival (OS). The results showed that the image fusion model incorporating radiomic signatures from contrast-enhanced T1-weighted imaging (cT1WI) and apparent diffusion coefficient (ADC) achieved an AUC of 0.884 and 0.669 for predicting IDH and TERT status, respectively. cT1WI-based radiomic signature alone yielded favorable performance in predicting 1p/19q status (AUC = 0.815). The predictive molecular groups were comparable to actual ones in predicting PFS (C-index: 0.709 vs. 0.722, P = 0.241) and OS (C-index: 0.703 vs. 0.751, P = 0.359). Subgroup analyses by grades showed similar findings. The prognostic nomograms based on grades and the predictive molecular groups yielded a C-index of 0.736 and 0.735 in predicting PFS and OS, respectively. Accordingly, MRI-based radiomics may be useful for noninvasively detecting molecular groups and predicting survival in gliomas regardless of grades.

Brain stem gliomas (BSG) in adults are rare and less aggressive than those in children. However, the molecular profile of adult BSG cases has not been well characterized. We report a case of adult BSG with isocitrate dehydrogenase (IDH) mutation. A 43-year-old male was admitted to our hospital with diplopia and right-sided hypesthesia. An open biopsy led to the tumor being diagnosed as a diffuse astrocytoma. Immunohistochemically, the tumor was positive for IDH1 R132H, but negative for H3K27M. The patient received 54 Gy of local radiotherapy and adjuvant temozolomide, which resulted in the size of the lesion decreasing significantly. At 56 months after the initial diagnosis, the patient was referred to our hospital with a severe headache and ataxia. Magnetic resonance imaging (MRI) revealed a contrast-enhanced lesion in the brain stem, which extended into the left cerebellar hemisphere and brainstem. Partial tumor removal was performed, and a pathological examination revealed the features of glioblastoma. Immunohistochemically, the tumor was positive for IDH1 R132H and p53 and negative for ATRX. To the best of our knowledge, there are few reports about adult case of brain stem astrocytoma to be confirmed via histological and molecular examinations of the primary and recurrent tumor. We exhibit detailed pathological and molecular findings which resembles to IDH mutant supratentorial diffuse astrocytic tumors.

Objective: The T2-FLAIR mismatch sign is a useful imaging sign in clinical magnetic resonance imaging studies for detecting isocitrate dehydrogenase (IDH)-mutant 1p/19q non-codeleted astrocytomas. However, the association between the mismatch sign and pathologic findings is poorly understood. Therefore, the aim of this study was to elucidate the relationship of histopathologic and radiologic features with the mismatch sign in IDH-mutant 1p/19q non-codeleted astrocytomas. Methods: We divided 17 IDH-mutant 1p/19q non-codeleted patients into 2 groups according to mismatch sign presence (WITH, n = 9; WITHOUT, n = 8) and retrospectively analyzed their pathologic findings and apparent diffusion coefficient (ADC) values. We also compared these findings between the tumor Core (central area) and Rim (marginal area). Results: In the pathologic analysis, Core of the WITH group contained numerous microcysts whereas Rim had abundant neuroglial fibrils and cellularity. In contrast, Core of the WITHOUT group had highly concentrated neuroglial fibrils. In ADC analysis, Core of the WITH group had significantly higher ADC values compared with Rim (P < 0.001). However, there was no significant difference between Core and Rim in the WITHOUT group (P = 0.12). The WITH group had a significantly higher Core/Rim ratio of ADC values compared with the WITHOUT group (P < 0.001). Conclusions: This study provides evidence that a region-dependent microstructural difference could reflect the mismatch sign in IDH-mutant 1p/19q non-codeleted astrocytomas. Core of the mismatch sign characteristically had microcystic changes accompanied by higher ADC values, whereas Rim had abundant neuroglial fibrils and cellularity accompanied by lower ADC values.

Background The rarity of Isocitrate Dehydrogenase mutated (mIDH) glioblastomas relative to wild-type IDH glioblastomas, as well as their distinct tumor physiology, effectively render them "outliers". Specialized tools are needed to identify these outliers. Objective To carefully craft and apply anomaly detection methods to identify mIDH glioblastoma based on radiomic features derived from magnetic resonance imaging. Methods T1-post gadolinium images for 188 patients and 138 patients were downloaded from The Cancer Imaging Archive's (TCIA) The Cancer Genome Atlas (TCGA) glioblastoma collection, and from the University of Minnesota Medical Center (UMMC), respectively. Anomaly detection methods were tested on glioblastoma image features for the precision of mIDH detection and compared to standard classification methods. Results Using anomaly detection training methods, we were able to detect IDH mutations from features in noncontrast-enhancing regions in glioblastoma with an average precision of 75.0%, 69.9%, and 69.8% using three different models. Anomaly detection methods consistently outperformed traditional two-class classification methods from 2 unique learning models (67.9%, 67.6%). The disparity in performances could not be overcome through newer, popular models such as neural networks (67.4%). Conclusion We employed an anomaly detection strategy in the detection of IDH mutation in glioblastoma using preoperative T1 postcontrast imaging. We show these methods outperform traditional two-class classification in the setting of dataset imbalances inherent to IDH mutation prevalence in glioblastoma. We validate our results using an external dataset and highlight new possible avenues for radiogenomic rare event prediction in glioblastoma and beyond.

The WHO 2016 update classifies glioblastomas (WHO grade IV) according to isocitrate dehydrogenase (IDH) gene mutation status. We aimed to determine MRI-based metrics for predicting IDH mutation in glioblastoma. This retrospective study included glioblastoma cases (n = 199) with known IDH mutation status and pre-operative MRI (T1WI, T2WI, FLAIR, contrast-enhanced T1W1 at minimum). Two neuroradiologists determined the following MRI metrics: (1) primary lobe of involvement (frontal or non-frontal); (2) presence/absence of contrast-enhancement; (3) presence/absence of necrosis; (4) presence/absence of fluid attenuation in the non-contrast-enhancing tumor (nCET); (5) maximum width of peritumoral edema (cm); (6) presence/absence of multifocal disease. Inter-reader agreement was determined. After resolving discordant measurements, multivariate association between consensus MRI metrics/patient age and IDH mutation status was determined. Among 199 glioblastomas, 16 were IDH-mutant. Inter-reader agreement was calculated for contrast-enhancement (ĸ = 0.49 [− 0.11–1.00]), necrosis (ĸ = 0.55 [0.34–0.76]), fluid attenuation in nCET (ĸ = 0.83 [0.68–0.99]), multifocal disease (ĸ = 0.55 [0.39–0.70]), and primary lobe (ĸ = 0.85 [0.80–0.91]). Mean difference for peritumoral edema width between readers was 0.3 cm [0.2–0.5], p

T2-fluid-attenuated inversion recovery images (FLAIR) mismatch sign is now known to be a specific yet insensitive image feature for IDH-mutant, 1p19q non-codeleted astrocytoma. The current study revealed that lesion presenting T2-FLAIR mismatch exhibited extremely long T1- and T2-relaxation time while T2-FLAIR matched lesions showed low to moderate values. On the other hand, IDH-wildtype tumors presented noticeably short T1- and T2-relaxation time. These different relaxation time characteristics seemed to render T2-FLAIR mismatch sign of becoming such a unique and specific image feature for IDH-mutant, 1p19q non-codeleted astrocytoma.

Approximately 10% of IDH-mutant gliomas harbour non-canonical IDH mutations (non-p.R132H IDH1 and IDH2 mutations). The aim of this study was to analyse the characteristics of non-canonical IDH-mutant gliomas. We retrospectively analysed the characteristics of 166 patients with non-canonical IDH mutant gliomas and compared them to those of 155 consecutive patients with IDH1 p.R132H mutant gliomas. The median age at diagnosis was 38 years in patients with non-canonical IDH mutant gliomas and 43 years in glioma patients with IDH1 p.R132H-mutant tumours. Family history of cancer was more frequent among glioma patients harbouring non-canonical IDH mutations than in patients with IDH1 p.R132H mutations (22.2% vs 5.1%; P

Purpose The updated 2016 CNS World Health Organization classification differentiates three main groups of diffuse glioma according to their molecular characteristics: astrocytic tumors with and without isocitrate dehydrogenase (IDH) mutation and 1p/19q co-deleted oligodendrogliomas. The present study aimed to determine whether dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) is an independent prognostic marker within the molecular subgroups of diffuse glioma. Methods Fifty-six patients with treatment-naive gliomas and advanced preoperative MRI examination were assessed retrospectively. The mean and maximal normalized cerebral blood volume values from DSC-MRI within the tumors were measured. Optimal cutoff values for the 1-year progression-free survival (PFS) were defined, and Kaplan-Meier analyses were performed separately for the three glioma subgroups. Results IDH wild-type astrocytic tumors had a higher mean and maximal perfusion than IDH-mutant astrocytic tumors and oligodendrogliomas. Patients with IDH wild-type astrocytic tumors and a low mean or maximal perfusion had a significantly shorter PFS than patients of the same group with high perfusion (p = 0.0159/0.0112). Furthermore, they had a significantly higher risk for early progression (hazard ratio = 5.6/5.1). This finding was independent of the methylation status of O6-methylguanin-DNA-methyltransferase and variations of the therapy. Within the groups of IDH-mutant astrocytic tumors and oligodendrogliomas, the PFS of low and highly perfused tumors did not differ. Conclusion High perfusion upon initial diagnosis is not compellingly associated with worse short-term prognosis within the different molecular subgroups of diffuse glioma. Particularly, the overall highly perfused group of IDH wild-type astrocytic tumors contains tumors with low perfusion but unfavorable prognosis.

Anaplastic oligodendrogliomas are a type of glioma that occurs primarily in adults but are also found in children. These tumors are genetically defined according to the mutations they harbor. Grade II and grade III tumors can be differentiated most of the times by the presence of anaplastic features. The earliest regimen used for the treatment of these tumors was procarbazine, lomustine, and vincristine. The treatment modalities have shifted over time, and recent studies are considering immunotherapy as an option as well. This review assesses the latest management modalities along with the pathways involved in the pathogenesis of this malignancies.

Background Many low-grade gliomas (LGG) harbor isocitrate dehydrogenase (IDH) mutations. Although IDH mutation is known to be epileptogenic, the rate of refractory seizures in LGG with IDH mutation vs wild-type had not been previously compared. We therefore compared seizure pharmacoresistance in IDH-mutated and wild-type LGGs. Methods Single-institution retrospective study of patients with histologic proven LGG, known IDH mutation status, seizures, and ≥2 neurology clinic encounters. Seizure history was followed until histological high-grade transformation or death. Seizures requiring ≥2 changes in anti-epileptic drugs were considered pharmacoresistant. Incidence rates of pharmacoresistant seizures were estimated using competing risks methodology. Results Of 135 patients, 25 patients (19%) had LGGs classified as IDH wild-type. Of those with IDH mutation, 104 (94.5%) were IDH1 R132H; only 6 were IDH2 R172K. 120 patients (89%) had tumor resection, and 14 (10%) had biopsy. Initial post-surgical management included observation (64%), concurrent chemoradiation (23%), chemotherapy alone (9%), and radiotherapy alone (4%). Seizures became pharmacoresistant in 24 IDH-mutated patients (22%) and in 3 IDH wild-type patients (12%). The 4-year cumulative incidence of intractable seizures was 17.6% (95% CI: 10.6%-25.9%) in IDH-mutated and 11% (95% CI: 1.3%-32.6%) in IDH wild-type LGG (Gray’s P-value = .26). Conclusions 22% of the IDH-mutated patients developed pharmacoresistant seizures, compared to 12% of the IDH wild-type tumors. The likelihood of developing pharmacoresistant seizures in patients with LGG-related epilepsy is independent to IDH mutation status, however, IDH-mutated tumors were approximately twice as likely to experience LGG-related pharmacoresistant seizures.

BACKGROUND Mutation of isocitrate dehydrogenase (IDH) is not only an important landmark in the development of low-grade gliomas, but also has prognostic significance and is a potential therapeutic target. There is a high need to determinate IDH mutation status at diagnosis and during the course of therapy in a non-invasive and reliable manner. We established a machine learning approach based on a support vector machine to detect IDH mutation status in in vivo standard 1H-magnetic resonance spectroscopy (1H-MRS) at 3T with an accuracy of 88.2%, a sensitivity of 95.5% (95% CI, 77.2–99.9%), and a specificity of 75% (95% CI, 42.85–94.5%) in a prospective monocentric clinical trial. Here, the same method is applied in a retrospective cohort at 1.5T and tested for transferability. MATERIAL AND METHODS Validation cohort. The validation cohort comprised 100 patients with glioma for which standard in vivo 1H-MRS spectra had been acquired between 2002 and 2007. Standard single voxel spectroscopy had been measured at 1.5T using a PRESS sequence with a TR of 1500ms and a TE of 30ms. One sample had to be excluded due to non-malignant histology and for 15 samples the IDH mutation status was not available. Therefore, the validation cohort comprised 84 samples, of which 35 were bearing an IDH mutation in immunohistochemistry (sequencing for confirmation is outstanding). Machine learning. To transfer our method to an independent validation cohort our previously established machine learning approach was first trained on all samples of the 3T group. The trained algorithm was then applied to the data of the validation cohort. Here, among other factors the different field strengths, with which the spectra were acquired (3T vs. 1.5T) had to be considered. RESULTS 27 samples of the validation cohort had to be excluded due to poor spectra quality. Our approach correctly detected IDH mutation status in 47 of 62 patients (75.8%), although the technical conditions were significantly different from our published prospective cohort. 17 of 30 patients bearing an IDH mutation were correctly identified, while 30 of 32 wild type patients were determined successfully. CONCLUSION Our approach to detect IDH mutation status has promising application in an unselected retrospective cohort, demonstrating transferability across different technical conditions. Further investigations to improve our technique and an advanced neuropathological processing of the samples are planned.

Background Although IDH-mutant tumors aggregate to the frontotemporal regions, the clustering pattern of IDH-wildtype tumors is less clear. As voxel-based lesion-symptom mapping (VLSM) has several limitations for solid lesion mapping, a new technique, whole-lesion phenotype analysis (WLPA), is developed. We utilize WLPA to assess spatial clustering of tumors with IDH mutation from The Cancer Genome Atlas and The Cancer Imaging Archive. Methods The degree of tumor clustering segmented from T1 weighted images is measured to every other tumor by a function of lesion similarity to each other via the Hausdorff distance. Each tumor is ranked according to the degree to which its neighboring tumors show identical phenotypes, and through a permutation technique, significant tumors are determined. VLSM was applied through a previously described method. Results A total of 244 patients of mixed-grade gliomas (WHO II–IV) are analyzed, of which 150 were IDH-wildtype and 139 were glioblastomas. VLSM identifies frontal lobe regions that are more likely associated with the presence of IDH mutation but no regions where IDH-wildtype was more likely to be present. WLPA identifies both IDH-mutant and -wildtype tumors exhibit statistically significant spatial clustering. Conclusion WLPA may provide additional statistical power when compared with VLSM without making several potentially erroneous assumptions. WLPA identifies tumors most likely to exhibit particular phenotypes, rather than producing anatomical maps, and may be used in conjunction with VLSM to understand the relationship between tumor morphology and biologically relevant tumor phenotypes.

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.

Background Tumor hypoxia and glycolysis have been recognized as determinant factors characterizing tumor aggressiveness in malignant gliomas. To clarify in vivo hypoxia and glucose metabolism in relation to isocitrate dehydrogenase (IDH) mutation and chromosome 1p and 19q (1p/19q) codeletion status, we retrospectively analyzed hypoxia as assessed by positron emission tomography (PET) with [18F]-fluoromisonidazole (FMISO) and glucose metabolism as assessed by PET with [18F]-fluoro-2-deoxy-d-glucose (FDG) in newly diagnosed malignant gliomas. Methods In total, 87 patients with newly diagnosed supratentorial malignant (WHO grade III and IV) gliomas were enrolled in this study. They underwent PET studies with FMISO and FDG before surgery. The molecular features and histopathological diagnoses based on the 2016 WHO classification were determined using surgical specimens. Maximal tumor-to-normal ratio (TNR) was calculated for FDG PET, and maximal tumor-to-blood SUV ratio (TBR) was calculated for FMISO PET. The PET uptake values in relation to IDH mutation and 1p/19q codeletion status were statistically analyzed. Results In all tumors and malignant astrocytomas, the median FMISO TBR in IDH-wildtype tumors was significantly higher than that in IDH-mutant tumors (P P IDH-wildtype tumors tended to be higher than that in IDH-mutant tumors, but the difference was not statistically significant. In WHO grade III anaplastic astrocytomas, there were no significant differences in median FMISO TBR or FDG TNR between IDH-mutant and IDH-wildtype tumors. In IDH-mutant WHO grade III anaplastic gliomas, there were no significant differences in median FMISO TBR or FDG TNR between anaplastic astrocytomas and anaplastic oligodendrogliomas. Conclusions Tumor hypoxia as assessed by FMISO PET was informative for prediction of the IDH mutation status in newly diagnosed malignant gliomas. However, the accuracy of the discrimination was not satisfactory for clinical application. On the other hand, glucose metabolism as assessed by FDG PET could not differentiate the IDH-mutant status. Moreover, PET studies using FMISO and FDG could not predict IDH mutation and 1p/19q codeletion status in WHO grade III tumors.

Gliomas are primary brain tumors that originate from glial cells. Classification and grading of these tumors is critical to prognosis and treatment planning. The current criteria for glioma classification in central nervous system (CNS) was introduced by World Health Organization (WHO) in 2016. This criteria for glioma classification requires the integration of histology with genomics. In 2017, the Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy (cIMPACT-NOW) was established to provide up-to-date recommendations for CNS tumor classification, which in turn the WHO is expected to adopt in its upcoming edition. In this work, we propose a novel glioma analytical method that, for the first time in the literature, integrates a cellularity feature derived from the digital analysis of brain histopathology images integrated with molecular features following the latest WHO criteria. We first propose a novel over-segmentation strategy for region-of-interest (ROI) selection in large histopathology whole slide images (WSIs). A Deep Neural Network (DNN)-based classification method then fuses molecular features with cellularity features to improve tumor classification performance. We evaluate the proposed method with 549 patient cases from The Cancer Genome Atlas (TCGA) dataset for evaluation. The cross validated classification accuracies are 93.81% for lower-grade glioma (LGG) and high-grade glioma (HGG) using a regular DNN, and 73.95% for LGG II and LGG III using a residual neural network (ResNet) DNN, respectively. Our experiments suggest that the type of deep learning has a significant impact on tumor subtype discrimination between LGG II vs. LGG III. These results outperform state-of-the-art methods in classifying LGG II vs. LGG III and offer competitive performance in distinguishing LGG vs. HGG in the literature. In addition, we also investigate molecular subtype classification using pathology images and cellularity information. Finally, for the first time in literature this work shows promise for cellularity quantification to predict brain tumor grading for LGGs with IDH mutations.

This review discusses current and investigative strategies for targeting DNA repair in the management of glioma. Recent strategies in glioma treatment rely on the production of overwhelming DNA damage and inhibition of repair mechanisms, resulting in lethal cytotoxicity. Many strategies are effective in preclinical glioma models while clinical feasibility remains under investigation. The presence of glioma biomarkers, including IDH mutation and/or MGMT promoter methylation, may confer particular susceptibility to DNA damage and inhibition of repair. These biomarkers have been adopted as eligibility criteria in the design of multiple ongoing clinical trials. Targeting DNA repair mechanisms with novel agents or therapeutic combinations is a promising approach to the treatment of glioma. Further investigations are underway to optimize this approach in the clinical setting.

European journal of nuclear medicine and molecular imaging 48(6), 1956-1965 (2020). doi:10.1007/s00259-020-05114-0, Published by Springer-Verl., Heidelberg [u.a.]

Background Isocitrate dehydrogenase (IDH) is an enzyme family involved in cell aerobic metabolism of tricarboxylic acid cycle. However, the landscape of IDH mutations in pan‐cancer has not been fully characterized. Methods Tissue or blood samples were subjected to next‐generation sequencing (NGS) for detection the IDH mutation. Results A total of 28.868 patients from more than 20 solid tumor species were analyzed. A total of 374 cases (1.30%) with IDH mutations were identified. Among all the IDH mutations cases, 80 (21.4%) were biliary tract cancer (BTC), 80 (21.4%) were lung cancer, 57 (15.2%) were liver cancer, and 42 (11.2%) were colorectal cancer. The most common IDH variant were IDH1 and IDH2 which were discovered in 0.81% cases and 0.47% cases, respectively. However, there were significant differences in IDH1 and IDH2 mutation frequency among different tumor species (p = 0.0003). Of the patients with IDH1 mutations, about 53.0% of these mutations occur in codons 132. Codons 172 (25.4%) was high‐frequency mutation subtypes in IDH2 mutation. TP53, PBRM1, and BAP1 were the most significantly mutated genes in BTC which were different from others cancer. Moreover, TMB were significantly higher in lung cancer, colorectal cancer, and gastric cancer than BTC (p = 0.0164, p, Somatic IDH mutation was found in multiple solid tumors and IDH would be a driver gene in biliary tract cancer.

B7H3 (also known as CD276) is a co-stimulator checkpoint protein of the cell surface B7 superfamily. Recently, the function beyond immune regulation of B7H3 has been widely studied. However, the expression preference and the regulation mechanism underlying B7H3 in different subtypes of gliomas is rarely understood. We show here that B7H3 expression is significantly decreased in IDH-mutated gliomas and in cultured IDH1-R132H glioma cells. Accumulation of 2-HG leads to a remarkable downregulation of B7H3 protein and the activity of IDH1-R132H mutant is responsible for B7H3 reduction in glioma cells. Inhibition of autophagy by inhibitors like leupeptin, chloroquine (CQ), and Bafilomycin A1 (Baf-A1) blocks the degradation of B7H3 in glioma cells. In the meantime, the autophagy flux is more active with higher LC3B-II and lower p62 in IDH1-R132H glioma cells than in IDH1-WT cells. Furthermore, sequence alignment analysis reveals potential LC3-interacting region (LIR) motifs “F-V-S/N-I/V” in B7H3. Moreover, B7H3 interacts with p62 and CQ treatment significantly enhances this interaction. Additionally, we find that B7H3 is positively correlated with VEGFA and MMP2 by bioinformatics analysis in gliomas. B7H3 and VEGFA are decreased in IDH-mutated gliomas and further reduced in 2-HGhigh gliomas compared to 2-HGlow glioma sections by IHC staining. Our study demonstrates that B7H3 is preferentially overexpressed in IDH wild-type gliomas and could serve as a potential theranostic target for the precise treatment of glioma patients with wild-type IDH.

Background:Chromosome 1p/19q codeletion is one of the most important genetic alterations for low grade gliomas (LGGs), and patients with 1p/19q codeletion have significantly prolonged survival compared to those without the codeletion. And the tumor immune microenvironment also plays a vital role in the tumor progression and prognosis. However, the effect of 1p/19q codeletion on the tumor immune microenvironment in LGGs is unclear.Methods:Immune cell infiltration of 281 LGGs from The Cancer Genome Atlas (TCGA) and 543 LGGs from the Chinese Glioma Genome Atlas (CGGA) were analyzed for immune cell infiltration through three bioinformatics tools: ESTIMATE algorithm, TIMER, and xCell. The infiltrating level of immune cells and expression of immune checkpoint genes were compared between different groups classified by 1p/19q codeletion and IDH (isocitrate dehydrogenase) mutation status. The differential biological processes and signaling pathways were evaluated through Gene Set Enrichment Analysis (GSEA). Correlations were analyzed using Spearman correlation.Results:1p/19q codeletion was associated with immune-related biological processes in LGGs. The infiltrating level of multiple kinds of immune cells and expression of immune checkpoint genes were significantly lower in 1p/19q codeletion LGGs compared to 1p/19q non-codeletion cohorts. There are 127 immune-related genes on chromosome 1p or 19q, such as TGFB1, JAK1, and CSF1. The mRNA expression of these genes was positively correlated with their DNA copy number. These genes are distributed in multiple immune categories, such as chemokines/cytokines, TGF-β family members, and TNF family members, regulating immune cell infiltration and expression of the immune checkpoint genes in tumors.Conclusion:Our results indicated that 1p/19q codeletion status is closely associated with the immunosuppressive microenvironment in LGGs. LGGs with 1p/19q codeletion display less immune cell infiltration and lower expression of immune checkpoint genes than 1p/19q non-codeletion cases. Mechanistically, this may be, at least in part, due to the deletion of copy number of immune-related genes in LGGs with 1p/19q codeletion. Our findings may be relevant to investigate immune evasion in LGGs and contribute to the design of immunotherapeutic strategies for patients with LGGs.

Purpose: Isocitrate dehydrogenase (IDH) mutations are common in low-grade gliomas and the IDH mutation status is now integrated into the WHO classification of gliomas. IDH mutations lead to preferential accumulation of the R- relative to the S-enantiomer of 2-hydroxyglutarate (2-HG). We investigated the utility of tissue total 2-HG, R-2-HG, and the R-2-HG/S-2-HG ratio (rRS) as diagnostic and prognostic biomarkers for IDH mutations in gliomas. Experimental Design: Glioma tissue and blood samples from 87 patients were analyzed with HPLC-MS/MS coupled with a CHIROBIOTIC column to quantify both enantiomers of 2-HG. ROC analysis was conducted to evaluate the sensitivity and specificity of 2-HG, R-2-HG, and rRS. The feasibility of real-time determination of IDH status was evaluated in 11 patients intraoperatively. The prognostic value of rRS was evaluated using the Kaplan–Meier method. Results: The rRS in glioma tissues clearly distinguished patients with IDH-mutant versus wild-type tumors (P < 0.001). Sensitivity and specificity using an rRS cut-off value of 32.26 were 97% and 100%, respectively. None of total 2-HG, R-2-HG, or rRS was elevated in serum samples. Among patients with IDH-mutant tumors, tissue rRS stratifies overall survival. The duration of tissue analysis is approximately 60 minutes. Conclusions: Our study demonstrates that rRS is a reliable biomarker of IDH mutation status. This technique can be used to determine IDH mutation status intraoperatively, and to guide treatment decisions based on IDH mutation status in real time. Finally, rRS values may provide additional prognostic information and further validation is required.

The role of amino acid positron emission tomography (PET) in glioma grading and outcome prognostication has not yet been well established. This is particularly true in the context of the new WHO 2016 classification, which introduced a definition of glioma subtypes primarily based on molecular fingerprints. The aim of the present study was to correlate 3,4‑dihydroxy‑6‑[18F]‑fluoro-l‑phenylalanine (F-DOPA) uptake parameters with IDH mutation, 1p/19q status, and survival outcomes in patients with glioma. The study population consisted of 33 patients (17 M/16 F, mean age: 46 ± 13 years) who underwent F-DOPA PET/CT for the evaluation of tumor extent before the start of chemo or radiotherapy. The presence of IDH mutation and 1p/19q status was assessed in all the cases. Tumor volume and semiquantitative uptake parameters, namely SUVmax, tumor-to-normal brain ratio and tumor-to-normal striatum ratio, were calculated for each tumor. Imaging-derived parameters were compared between patients stratified according to molecular fingerprints, using parametric or non-parametric tests, where appropriate. The Kaplan–Meier method was used to assess differences of overall survival (OS) and progression-free survival (PFS) between groups. PET parameters were also tested as prognostic factors in univariate Cox survival regression models. There were 12 IDH-wild-type and 21 IDH-mutant patients. Stratification according to 1p/19q co-deletion resulted in 20 non-co-deleted and 13 co-deleted patients. Median follow-up time from PET/CT exam was 30.5 months (range 3.5–74 months). Semiquantitative uptake parameters did correlate neither with IDH mutation nor with 1p/19q status. Uptake was similar in low-grade and high-grade tumors, respectively. In addition, F-DOPA uptake parameters, macroscopic tumor volume, or tumor grade did not stratify OS, while a correlation between SUVmax and PFS was shown in the subgroup of astrocytomas. On the other hand, IDH mutation status and presence of 1p/19q co-deletion had a significant impact on survival outcomes. The prognostic value of IDH mutation status was also confirmed in the subgroup of patients with astrocytic tumors. F-DOPA uptake parameters do not correlate with tumor molecular and histological characteristics. The predictive value of PET-derived parameters on outcomes of survival is limited.

The finding that most grades II and III gliomas harbor isocitrate dehydrogenase (IDH) mutations conveying a relatively favorable and fairly similar prognosis in both tumor grades highlights that these tumors represent a fundamentally different entity from IDH wild-type gliomas exemplified in most glioblastoma. Herein we review the most recent developments in molecular neuropathology leading to reclassification of these tumors based upon IDH and 1p/19q status, as well as the potential roles of methylation profiling and deletional analysis of cyclin-dependent kinase inhibitor 2A and 2B. We discuss the epidemiology, clinical manifestations, benefit of surgical resection, and neuroimaging features of lower-grade gliomas as they relate to molecular subtype, including advanced imaging techniques such as 2-hydroxyglutarate magnetic resonance spectroscopy and amino acid PET scanning. Recent, ongoing, and planned studies of radiation therapy and both cytotoxic and targeted chemotherapies are summarized, including both small molecule and immunotherapy approaches specifically targeting the mutant IDH protein.

Unravelling the heterogeneity is the central challenge for glioma precession oncology. In this study, we extracted quantitative image features from T2-weighted MR images and revealed that the isocitrate dehydrogenase (IDH) wild type and mutant lower grade gliomas (LGGs) differed in their expression of 146 radiomic descriptors. The logistic regression model algorithm further reduced these to 86 features. The classification model could discriminate the two types in both the training and validation sets with area under the curve values of 1.0000 and 0.9932, respectively. The transcriptome-radiomic analysis revealed that these features were associated with the immune response, biological adhesion, and several malignant behaviors, all of which are consistent with biological processes that are differentially expressed in IDH wild type and IDH mutant LGGs. Finally, a prognostic signature showed an ability to stratify IDH mutant LGGs into high and low risk groups with distinctive outcomes. By extracting a large number of radiomic features, we identified an IDH mutation-specific radiomic signature with prognostic implications. This radiomic signature may provide a way to non-invasively discriminate lower-grade gliomas as with or without the IDH mutation.

Mutation of the telomerase reverse transcriptase (TERT) promoter has been demonstrated as an unfavorable prognostic marker in patients with isocitrate dehydrogenase wild-type (IDHwt) glioma. This study aimed to investigate the immune role of TERT promoter mutation status which could improve prognostic prediction in IDHwt. TERT mutation status, IDH mutation, and 1p-19q codeletion status data were obtained from 614 glioma cases from the Cancer Genome Atlas, and 325 cases from the Chinese Glioma Genome Atlas. The same information was obtained from 49 clinical glioma tissues. TERT mutation is preferentially present in glioblastoma and IDH-wt gliomas and is associated with poor prognosis. Moreover, TERT mutation was associated with infiltration of neutrophils and expression of neutrophil chemokines. which might partially contribute to the poor outcome in IDH-wt glioma. Furthermore, patients with IDH-wt glioma did not harbor increased peripheral neutrophils, implying that the infiltrated neutrophil in the tumor environment might due to cytokine chemotaxis. In this study, we hereby propose that TERT mutation might be a molecular driver of the dysfunctional immune microenvironment in IDH-wt glioma. TERT mutation may be a potential immune therapeutic target for optimizing treatment combinations and patient selection for glioma immunotherapy.

Background Mutations in isocitrate dehydrogenase 1 or 2 (IDH1/2) define glioma subtypes and are considered primary events in gliomagenesis, impacting tumor epigenetics and metabolism. IDH enzyme activity is crucial for the generation of reducing potential in normal cells, yet the impact of the mutation on the cellular antioxidant system in glioma is not understood. The aim of this study was to determine how glutathione (GSH), the main antioxidant in the brain, is maintained in IDH1-mutant gliomas, despite an altered NADPH/NADP balance. Methods Proteomics, metabolomics, metabolic tracer studies, genetic silencing, and drug targeting approaches in vitro and in vivo were applied. Analyses were done in clinical specimen of different glioma subtypes, in glioma patient-derived cell lines carrying the endogenous IDH1 mutation and corresponding orthotopic xenografts in mice. Results We find that cystathionine-γ-lyase (CSE), the enzyme responsible for cysteine production upstream of GSH biosynthesis, is specifically upregulated in IDH1-mutant astrocytomas. CSE inhibition sensitized these cells to cysteine depletion, an effect not observed in IDH1 wild-type gliomas. This correlated with an increase in reactive oxygen species and reduced GSH synthesis. Propargylglycine (PAG), a brain-penetrant drug specifically targeting CSE, led to delayed tumor growth in mice. Conclusions We show that IDH1-mutant astrocytic gliomas critically rely on NADPH-independent de novo GSH synthesis via CSE to maintain the antioxidant defense, which highlights a novel metabolic vulnerability that may be therapeutically exploited.

Background Seizures are common among patients with low-grade glioma (LGG) and can significantly affect morbidity. We sought to determine the association between the clinical and molecular factors with seizure incidence and refractoriness in LGG patients. Methods We conducted a retrospective review at the University of Virginia in patients with LGG (World Health Organization, WHO Grade II) evaluated between 2002 and 2015. Descriptive statistics were calculated for variables of interest, and the Kaplan-Meier method was used to estimate survival curves, which were compared with the log-rank test. Results A total of 291 patients were included; 254 had molecular testing performed for presence of an isocitrate dehydrogenase (IDH) mutation and/or 1p/19q codeletion. Sixty-eight percent of patients developed seizures prior to LGG diagnosis; 41% of all patients had intractable seizures. Using WHO 2016 integrated classification, there was no significant difference in seizure frequency during preoperative and postoperative periods or in developing intractable seizures, though a trend toward increased preoperative seizure incidence among patients with the IDH mutation was identified (P = .09). Male sex was significantly associated with higher seizure incidence during preoperative (P < .001) and postoperative periods (P < .001); men were also more likely to develop intractable seizures (P = .01). Conclusions Seizures are common among patients with LGG. Differences in preoperative or postoperative and intractable seizure rates by WHO 2016 classification were not detected. Our data showed a trend toward higher seizure incidence preoperatively in patients with IDH-mutant LGG. We describe a unique association between male sex and seizure incidence and intractability that warrants further study.

Introduction/Objective Maximizing surgical resection in gliomas, while avoiding compromising non-infiltrated tissue, is associated with survival benefit. Current methodologies are suboptimal in providing rapid, intraoperative molecular characterization of tissue. We address this unmet need by using desorption electrospray ionization mass spectrometry (DESI-MS) for the intraoperative molecular assessment of gliomas. Methods/Case Report This prospective study uses intraoperative DESI-MS analysis of fresh tissue to evaluate IDH mutations via 2-hydroxyglutarate intensity and TCP via measurement of N-acetylaspartic acid (NAA) intensity and characteristic lipid profiles in less than three minutes. Blinded review of the tissue smears by a neuropathologist is used to validate IDH mutation status and TCP estimates. Results (if a Case Study enter NA) Presently, 529 biopsies from 85 enrolled patients have been collected and analyzed at two institutions. TCP assessment based on NAA intensity in 203 biopsies at the first institution yielded sensitivity, specificity, and accuracy values of 91, 76, and 83%, whereas TCP estimates via characteristic lipid profiles yielded 76, 85, and 81%, respectively. Assessment of IDH mutation status of 71 core biopsies yielded sensitivity, specificity, and accuracy values of 89, 100, and 94%. Ongoing validation of the methodology is being performed at a second institution, where we have collected 282 biopsies from 36 patients. IDH mutation assessment of the first 15 patients indicate 100% sensitivity, specificity, and accuracy. Conclusion This study represents the first and largest study using DESI-MS for the intraoperative evaluation of IDH status and TCP measurement in gliomas. Prospectively, we propose to modify our DESI-MS system to allow estimation of IDH mutation status and TCP in surgical cavities without the need for a biopsy by placing a surgical material along the margin and transferring material from the blot to a microscope slide prior to DESI-MS analysis. We envision molecular analysis by DESI-MS as a complementary technique to histopathology capable of providing additional clinical information in near real-time.

Isocitrate dehydrogenase (IDH) mutant and wildtype glioblastoma multiforme (GBM) often show overlapping features on magnetic resonance imaging (MRI), representing a diagnostic challenge. Deep learning showed promising results for IDH identification in mixed low/high grade glioma populations, however, a GBM-specific model is still lacking in the literature. Our aim was to develop a GBM-tailored deep-learning model for IDH prediction by applying convoluted neural networks (CNN) on multiparametric MRI. We selected 100 adult patients with pathologically demonstrated WHO grade IV gliomas and IDH testing. MRI sequences included: MPRAGE, T1, T2, FLAIR, rCBV and ADC. The model consisted of a 4-block 2D CNN, applied to each MRI sequence. Probability of IDH mutation was obtained from the last dense layer of a softmax activation function. Model performance was evaluated in the test cohort considering categorical cross-entropy loss (CCEL) and accuracy. Calculated performance was: rCBV (accuracy 83%, CCEL 0.64), T1 (accuracy 77%, CCEL 1.4), FLAIR (accuracy 77%, CCEL 1.98), T2 (accuracy 67%, CCEL 2.41), MPRAGE (accuracy 66%, CCEL 2.55). Lower performance was achieved on ADC maps. We present a GBM-specific deep-learning model for IDH mutation prediction, with a maximal accuracy of 83% on rCBV maps. Highest predictivity achieved on perfusion images possibly reflects the known link between IDH and neoangiogenesis through the hypoxia inducible factor.

Isocitrate dehydrogenase (IDH) status is an important basis for the diagnosis of gliomas in the 2016 World Health Organization classification scheme. A strong relationship exists between IDH mutation status and glioma prognosis. The preoperative prediction of IDH status is essential for the treatment of gliomas. However, the existing medical methods cannot predict IDH status before an operation. In this study, we propose a modality self-attention network to predict IDH mutation status on multimodality magnetic resonance imaging images. The proposed method predicts the importance of each modality for classification task and calculates weights and then uses weighted images for training. Moreover, we select a light and high-performance self-attention network for the classification to solve the overfitting problem on the glioma dataset of the First Affiliated Hospital of Zhengzhou University (FHZU). The proposed method achieved an F1-score of 0.6570 on the FHZU dataset, which is better than SE-Net (0.2563), a method proposed by Yoon Seong Choi et al. (0.3999), and SA-Net (0.5245).

Highlights • We identified ten hub genes which were driving IDH status in GBM and LGG. • We constructed a prognostic model for IDH-mutant patients. • Our findings have important clinical implications for accurate treatment in glioma., Our study attempted to identify hub genes related to isocitrate dehydrogenase (IDH) mutation in glioma and develop a prognostic model for IDH-mutant glioma patients. In a first step, ten hub genes significantly associated with the IDH status were identified by weighted gene coexpression analysis (WGCNA). The functional enrichment analysis demonstrated that the most enriched terms of these hub genes were cadherin binding and glutathione metabolism. Three of these hub genes were significantly linked with the survival of glioma patients. 328 samples of IDH-mutant glioma were separated into two datasets: a training set (N = 228) and a test set (N = 100). Based on the training set, we identified two IDH-mutant subtypes with significantly different pathological features by using consensus clustering. A 31 gene-signature was identified by the least absolute shrinkage and selection operator (LASSO) algorithm and used for establishing a differential prognostic model for IDH-mutant patients. In addition, the test set was employed for validating the prognostic model, and the model was proven to be of high value in classifying prognostic information of samples. The functional annotation revealed that the genes related to the model were mainly enriched in nuclear division, DNA replication, and cell cycle. Collectively, this study provided novel insights into the molecular mechanism of IDH mutation in glioma, and constructed a prognostic model which can be effective for predicting prognosis of glioma patients with IDH-mutation, which might promote the development of IDH target agents in glioma therapies and contribute to accurate prognostication and management in IDH-mutant glioma patients.

Background The interplay between glycolysis and immunosuppression in cancer has recently emerged as an intriguing area of research. The aim of this study was to elucidate a potential epigenetic link between glycolysis, isocitrate hydrogenase (IDH) status, and immune checkpoint expression in human lower-grade glioma (LGG). Methods Genomic analysis was conducted on 507 LGG samples from The Cancer Genome Atlas (TCGA). Data types analyzed included RNA-seq (IlluminaHiSeq) and DNA methylation (Methylation450K). Unsupervised clustering grouped samples according to glycolytic expression level and IDH status. Global promoter methylation patterns were examined, as well as methylation levels of LDHA/LDHB and immune checkpoint genes. Methylation data from a knock-in IDH1R132H/WT allele in HCT116 cells and ChIP-seq data from immortalized human astrocytes using an inducible IDH1R132H mutation were also assessed. Results Glycolytic expression distinguished a tumor cluster enriched for wild-type IDH and poorer overall survival (P < .0001). This cluster showed lower levels of LDHA promoter methylation and a higher LDHA/LDHB expression ratio. These samples also displayed lower PDL1/2 promoter methylation and higher PDL1/2 expression, which was more pronounced for PDL2. IDH1R132H/WT cell line data showed that induced changes in methylation were enriched for genes involved in immune regulation, and ChIP-seq data showed that promoter H3K4me3 decreased for LDHA, PDL2, and PDL1 upon induction of IDH1R132H. Conclusions These results suggest a previously unrecognized epigenetic link between glycolysis and immune checkpoint expression in LGG. This work advances our understanding of glioma genomics and provides support for further exploration of the metabolic-immune interface in LGG.

Background: To compare the application of two DKI post-processing methods that DKE software and DKI histogram analysis in glioma grading, IDH mutation typing, and evaluation of tumor heterogeneity.Methods: Patients who underwent surgery and were pathologically diagnosed with glioma after MR DKI scan. DKE software was used to calculate diffusion parameters, including fractional anisotropy, mean kurtosis (MK), radial kurtosis, and axial kurtosis. Histogram parameters were calculated, including minimum, maximum, mean, standard deviation, percentile values (25th, 50th, 75th, 95th), kurtosis, and skewness of Kapp and Dapp. The ROIs of the two post-processing methods were consistently and manually selected in continuous solid tumor regions. According to the result of Kolmogorov-Smirnov (K-S) test, Independent-samples T test or Mann - Whitney - Wilcoxon test was used to distinguish glioma grads. The parameters with the best percentile were identified by analysis of the area under the curve (AUC) of the receiver operating characteristic (ROC) analysis.Results: Seventy-three patients with glioma were observed, including 21 with low-grade gliomas (WHO II) and 52 with high-grade gliomas (WHO III, n=13; WHO IV, n=39), 38 of whom had IDH mutation status. There were significant differences between the high- and low-grade glioma groups regarding the maximum, mean, standard deviation, C75, and C95 of the Kapp values and the minimum, mean, C25, C50, C75, C95, and skewness of the Dapp values. The MK values were significantly different among the WHO II, III, and IV grades. MK, mean Kapp, and C75 and C95 of the Kapp could be used to predict IDH mutations in patients with glioma. Conclusions: Several quantitative DKI parameters obtained from the DKE software and histogram analysis could be used for glioma grading and predicting IDH mutations. However, DKI histogram analysis was useful for glioma heterogeneity.

OBJECTIVE Examine whether the status of the isocitrate dehydrogenase (IDH) gene is a risk factor for the development of venous thromboembolism (VTE) in astrocytoma patients. BACKGROUND The risk of venous thromboembolism (VTE) is high for patients with gliomas (10–30%). Unfortunately, biomarkers and predictive models for development of a VTE in brain cancer have not been validated. Prior research has suggested that IDH wildtype gliomas are at higher risk for development of VTE compared to IDH mutant tumors. DESIGN/METHODS We conducted a retrospective chart review of glioma patients enrolled in the PROACTIVE (Prospective Assessment of Correlative Biomarker) study at MD Anderson Cancer Center (MDACC). We obtained demographics, date of tumor diagnosis, initial pathology, IDH status (mutated or wildtype), extent of initial resection, KPS at time of initial resection, history of VTE, development of VTE, type of VTE (PE/DVT), KPS at time of VTE, treatment for VTE, bleeding complications, glioma treatments, date of last follow up and/or death. RESULTS We identified 282 astrocytoma patients consisting of 49 IDH mutant and 233 IDH wildtype astrocytomas. Glioblastoma was the histopathologic diagnosis in 30 (61.2%) of the IDH mutated astrocytomas compared to 227(97.4%) of the IDH wild type astrocytomas. VTE was identified in 52 (18.4%) of patients. VTE was diagnosed in 7 (14.3%) of the IDH mutated astrocytomas compared to 45 (19.3%) of the IDH wild type astrocytomas (p = 0.4094). Median time to VTE from diagnosis was 2.71 months. Median time to VTE from diagnosis was 2.6 months for IDH mutated astrocytomas compared to 3.06 months for the IDH wild type astrocytomas (p =0.8663). CONCLUSIONS IDH gene status did not appear as a significant risk factor for the development of venous thromboembolism (VTE) in our cohort of astrocytoma patients. Further research into potential biomarkers for VTE may be warranted.

Simple Summary Ferroptosis is increasingly recognized as a promising avenue for cancer therapy, while the biomarkers that predict the sensitivity and/or resistance of ferroptosis and the molecular mechanisms that can be therapeutically exploited to modulate ferroptosis are not yet known. Here, we perform an integrated pharmacotranscriptomic analysis to systematically identify compounds and gene networks that regulate ferroptosis. Our results provide mechanistic insights into the deregulation of ferroptosis in cancer and suggest new approaches for ferroptosis-based cancer therapy. Abstract (1) Background: Ferroptosis is an apoptosis-independent cell death program implicated in many diseases including cancer. Emerging evidence suggests ferroptosis as a promising avenue for cancer therapy, but the paucity of mechanistic understanding of ferroptosis regulation and lack of biomarkers for sensitivity to ferroptosis inducers have significantly hampered the utility of ferroptosis-based therapy. (2) Methods: We performed integrated dataset analysis by correlating the sensitivity of small-molecule compounds (n = 481) against the transcriptomes of solid cancer cell lines (n = 659) to identify drug candidates with the potential to induce ferroptosis. Generalizable gene signatures of ferroptosis sensitivity and resistance are defined by interrogating drug effects of ferroptosis inducers (n = 7) with transcriptomic data of pan-solid cancer cells. (3) Results: We report, for the first time, the comprehensive identification of drug compounds that induce ferroptosis and the delineation of generalizable gene signatures of pro- and anti-ferroptosis in pan-cancer. We further reveal that small cell lung cancer (SCLC) and isocitrate dehydrogenase (IDH1/2)-mutant brain tumors show enrichment of pro-ferroptosis gene signature, suggesting a unique vulnerability of SCLC and IDH-mutant tumors to ferroptosis inducers. Finally, we demonstrate that targeting class I histone deacetylase (HDAC) significantly enhances ferroptotic cell death caused by Erastin, an ferroptosis inducer, in lung cancer cells, revealing a previously underappreciated role for HDAC in ferroptosis regulation. (4) Conclusions: Our work reveals novel drug compounds and gene networks that regulate ferroptosis in cancer, which sheds light on the mechanisms of ferroptosis and may facilitate biomarker-guided stratification for ferroptosis-based therapy.

Simple Summary: Targeted therapies are of growing interest to physicians in cancer treatment. These drugs target specific genes and proteins involved in the growth and survival of cancer cells. Brain tumor therapy is complicated by the fact that not all drugs can penetrate the blood brain barrier and reach their target. We explored the non-invasive method, Magnetic Resonance Spectroscopy, for monitoring drug penetration and its effects in live animals bearing brain tumors. We were able to show the presence of the investigated drug in mouse brains and its on-target activity. Abstract: Background: BAY1436032 is a fluorine-containing inhibitor of the R132X-mutant isocitrate dehydrogenase (mIDH1). It inhibits the mIDH1-mediated production of 2-hydroxyglutarate (2-HG) in glioma cells. We investigated brain penetration of BAY1436032 and its effects using 1H/19F-Magnetic Resonance Spectroscopy (MRS). Methods: 19F-Nuclear Magnetic Resonance (NMR) Spectroscopy was conducted on serum samples from patients treated with BAY1436032 (NCT02746081 trial) in order to analyze 19F spectroscopic signal patterns and concentration-time dynamics of protein-bound inhibitor to facilitate their identification in vivo MRS experiments. Hereafter, 30 mice were implanted with three glioma cell lines (LNT-229, LNT-229 IDH1-R132H, GL261). Mice bearing the IDH-mutated glioma cells received 5 days of treatment with BAY1436032 between baseline and follow-up 1H/19F-MRS scan. All other animals underwent a single scan after BAY1436032 administration. Mouse brains were analyzed by liquid chromatography-mass spectrometry (LC-MS/MS). Results: Evaluation of 1H-MRS data showed a decrease in 2-HG/total creatinine (tCr) ratios from the baseline to post-treatment scans in the mIDH1 murine model. Whole brain concentration of BAY1436032, as determined by 19F-MRS, was similar to total brain tissue concentration determined by Liquid Chromatography with tandem mass spectrometry (LC-MS/MS), with a signal loss due to protein binding. Intratumoral drug concentration, as determined by LC-MS/MS, was not statistically different in models with or without R132X-mutant IDH1 expression. Conclusions: Non-invasive monitoring of mIDH1 inhibition by BAY1436032 in mIDH1 gliomas is feasible.

The aim of the study is to assess the diagnostic performance of inflow-based vascular-space-occupancy (iVASO) MR imaging for differentiating glioblastomas (grade IV, GBM) and lower-grade diffuse gliomas (grade II and III, LGG) and its potential to predict IDH mutation status.One hundred and two patients with diffuse cerebral glioma (56 males; median age, 43.5 years) underwent iVASO and dynamic susceptibility contrast (DSC) MR imaging. The iVASO-derived arteriolar cerebral blood volume (CBVa), relative CBVa (rCBVa), and the DSC-derived relative cerebral blood volume (rCBV) were obtained, and these measurements were compared between the GBM group (n = 43) and the LGG group (n = 59) and between the IDH-mutation group (n = 54) and the IDH-wild group (n = 48).Significant correlation was observed between rCBV and CBVa (P 0.001) or rCBVa (P 0.001). Both CBVa (P 0.001) and rCBVa (P 0.001) were higher in the GBM group. Both CBVa (P 0.001) and rCBVa (P 0.001) were lower in the IDH-mutation group compared to the IDH-wild group. Receiver operating characteristic analyses showed the area under curve (AUC) of 0.95 with CBVa and 0.97 with rCBVa in differentiating GBM from LGG. The AUCs were 0.82 and 0.85 for CBVa and rCBVa in predicting IDH gene status, respectively, which were lower than that of rCBV (AUC = 0.90). Combined rCBV and rCBVa significantly improved the diagnostic performance (AUC = 0.95).iVASO MR imaging has the potential to predict IDH mutation and grade in glioma.

Background Gliomas are the most common and lethal type of intracranial tumors. With the current treatment regime, the median survival of patients with grade IV glioma (glioblastoma/GBM) remains at 14–16 months. RNA editing modifies the function and regulation of transcripts. The development of glial tumors may be caused by altered RNA editing events. Methods In this study, we uncover the global RNA editome landscape of glioma patients from RNA-seq data of control, lower grade glioma (LGG) and GBM samples (n = 1,083). Results A-to-I editing events were found to comprise 80% of the total editing events of which 96% were located in the Alu regions. The total RNA editing events were found to be reduced in glioma compared to control samples. More specifically, we found Gamma-aminobutyric acid type A receptor alpha3 (GABRA3) to be edited (c.1026 A-to-G; pI343M) in 73% (editing ratio 0.8) of control samples compared to LGG (28.96%; 0.47) and GBM (5.2%; 0.53) samples. GABRA3 transcript level was found to be downregulated in glioma compared to control in a grade-specific manner with GBMs having the lowest level of the transcript. Further, GABRA3 transcripts were observed to be higher in edited compared to unedited glioma samples. The transcript and protein levels of exogenously expressed gene were found to be higher for edited compared to unedited GABRA3 in glioma cells. Further, exogenously expressed edited GABRA3 inhibited migration and invasion of glioma cells efficiently but not the unedited GABRA3. Conclusion Collectively, our study discovered a reduction in RNA editing during glioma development. We further demonstrate that elevated RNA editing maintains a high level of GABRA3 RNA and protein in normal glial cells which provides a less migratory environment for the normal functioning of the brain. In contrast, the reduction in GABRA3 protein levels, due to lower stability of unedited RNA, results in the loss of function which confers an aggressive phenotype to GBM tumor.

Highlights • MRI derived total 23Na concentration differs significantly in glioma subregions. • Total 23Na concentration could reflect IDH mutation status and tumor grade. • 23Na MRI yields potential non-invasive biomarkers for the treatment of gliomas., Purpose This prospective clinical trial investigated sodium (23Na) MRI at 7 Tesla (T) field strength as biomarker for tumor extent, isocitrate dehydrogenase (IDH) mutation and O6-methylguanine DNA methyltransferase (MGMT) promotor methylation in glioma patients. Methods 28 glioma patients underwent 23Na MRI on a 7T scanner (Siemens Healthcare, Erlangen, Germany) parallel to standard 3T MRI before chemoradiation. Areas of Gadolinium-contrast enhancement (gdce), non-enhancing T2-hyperintensity (regarded as edema), necrosis, and normal-appearing white matter (nawm) were segmented on 3T MRI imaging and were co-registered with the 23Na images. The median total 23Na concentrations of all areas were compared by pairwise t-tests. Furthermore, areas of gdce and edema were merged to yield the whole tumor area without necrosis. Subsequently, the difference in median of the 23Na concentration of this whole tumor area was compared between IDH-mutated and IDH wild-type gliomas as well as MGMT methylated and MGMT not-methylated glioblastomas using Whitney-Mann U-tests. All p-values were corrected after the Bonferroni-Holm procedure. Results The 23Na concentration increased successively from nawm to necrotic areas (mean ± sd: nawm = 37.84 ± 5.87 mM, edema = 54.69 ± 10.64 mM, gdce = 61.72 ± 12.95 mM, necrosis = 81.88 ± 17.53 mM) and the concentrations differed statistically significantly between all regarded areas (adjusted p-values for all pairwise comparisons

Mutations in isocitrate dehydrogenase (IDH) are commonly observed in lower-grade glioma and secondary glioblastomas. IDH mutants confer a neomorphic enzyme activity that converts α-ketoglutarate to an oncometabolite D-2-hydroxyglutarate, which impacts cellular epigenetics and metabolism. IDH mutation establishes distinctive patterns in metabolism, cancer biology, and the therapeutic sensitivity of glioma. Thus, a deeper understanding of the roles of IDH mutations is of great value to improve the therapeutic efficacy of glioma and other malignancies that share similar genetic characteristics. In this review, we focused on the genetics, biochemistry, and clinical impacts of IDH mutations in glioma.

Background Isocitrate dehydrogenase (IDH) mutation and 1p/19q-codeletion are oncogenetic alterations with a positive prognostic value for diffuse gliomas, especially grade II and III. Some studies have suggested differences in biological behavior as reflected by radiological characteristics. In this paper, the literature regarding radiological characteristics in grade II and III glioma subtypes was systematically evaluated and a meta-analysis was performed. Methods Studies that addressed the relationship between conventional radiological characteristics and IDH mutations and/or 1p/19q-codeletions in newly diagnosed, grade II and III gliomas of adult patients were included. The “3-group analysis” compared radiological characteristics between the WHO 2016 glioma subtypes (IDH-mutant astrocytoma, IDH-wildtype astrocytoma, and oligodendroglioma), and the “2-group analysis” compared radiological characteristics between 1p/19q-codeleted gliomas and 1p/19q-intact gliomas. Results Fourteen studies (3-group analysis: 670 cases, 2-group analysis: 1042 cases) were included. IDH-mutated astrocytomas showed more often sharp borders and less frequently contrast enhancement compared to IDH-wildtype astrocytomas. 1p/19q-codeleted gliomas had less frequently sharp borders, but showed a heterogeneous aspect, calcification, cysts, and edema more frequently. For the 1p/19q-codeleted gliomas, a sensitivity of 96% was found for heterogeneity and a specificity of 88.1% for calcification. Conclusions Significant differences in conventional radiological characteristics exist between the WHO 2016 glioma subtypes, which may reflect differences in biological behavior. However, the diagnostic value of the independent radiological characteristics is insufficient to reliably predict the molecular genetic subtype.

Diffuse gliomas are among the most common adult central nervous system tumors with an annual incidence of more than 16,000 cases in the United States. Until very recently, the diagnosis of these tumors was based solely on morphologic features, however, with the publication of the WHO Classification of Tumours of the Central Nervous System, revised 4th edition in 2016, certain molecular features are now included in the official diagnostic and grading system. One of the most significant of these changes has been the division of adult astrocytomas into IDH-wildtype and IDH-mutant categories in addition to histologic grade as part of the main-line diagnosis, although a great deal of heterogeneity in the clinical outcome still remains to be explained within these categories. Since then, numerous groups have been working to identify additional biomarkers and prognostic factors in diffuse gliomas to help further stratify these tumors in hopes of producing a more complete grading system, as well as understanding the underlying biology that results in differing outcomes. The field of neuro-oncology is currently in the midst of a “molecular revolution” in which increasing emphasis is being placed on genetic and epigenetic features driving current diagnostic, prognostic, and predictive considerations. In this review, we focus on recent advances in adult diffuse glioma biomarkers and prognostic factors and summarize the state of the field.

International audience; Purpose: 18F-FDopa PET imaging of gliomas is routinely interpreted with standardized uptake value (SUV)-derived indices. This study aimed to determine the added value of dynamic 18F-FDopa PET parameters for predicting the molecular features of newly diagnosed gliomas.Methods: We retrospectively included 58 patients having undergone an 18F-FDopa PET for establishing the initial diagnosis of gliomas, whose molecular features were additionally characterized according to the WHO 2016 classification. Dynamic parameters, involving time-to-peak (TTP) values and curve slopes, were tested for the prediction of glioma types in addition to current static parameters, i.e., tumor-to-normal brain or tumor-to-striatum SUV ratios and metabolic tumor volume (MTV).Results: There were 21 IDH mutant without 1p/19q co-deletion (IDH+/1p19q−) gliomas, 16 IDH mutants with 1p/19q co-deletion (IDH+/1p19q+) gliomas, and 21 IDH wildtype (IDH−) gliomas. Dynamic parameters enabled differentiating the gliomas according to these molecular features, whereas static parameters did not. In particular, a longer TTP was the single best independent predictor for identifying (1) IDH mutation status (area under the curve (AUC) of 0.789, global accuracy of 74% for the criterion of a TTP ≥ 5.4 min) and (2) 1p/19q co-deletion status (AUC of 0.679, global accuracy of 69% for the criterion of a TTP ≥ 6.9 min). Moreover, the TTP from IDH− gliomas was significantly shorter than those from both IDH+/1p19q− and IDH+/1p19q+ (p ≤ 0.007).Conclusion: Prediction of the molecular features of newly diagnosed gliomas with 18F-FDopa PET and especially of the presence or not of an IDH mutation, may be obtained with dynamic but not with current static uptake parameters.

In the WHO glioma classification guidelines grade (glioblastoma versus lower-grade glioma), IDH mutation and 1p/19q co-deletion status play a central role as they are important markers for prognosis and optimal therapy planning. Currently, diagnosis requires invasive surgical procedures. Therefore, we propose an automatic segmentation and classification pipeline based on routinely acquired pre-operative MRI (T1, T1 postcontrast, T2 and/or FLAIR). A 3D U-Net was designed for segmentation and trained on the BraTS 2019 training dataset. After segmentation, the 3D tumor region of interest is extracted from the MRI and fed into a CNN to simultaneously predict grade, IDH mutation and 1p19q co-deletion. Multi-task learning allowed to handle missing labels and train one network on a large dataset of 628 patients, collected from The Cancer Imaging Archive and BraTS databases. Additionally, the network was validated on an independent dataset of 110 patients retrospectively acquired at the Ghent University Hospital (GUH). Segmentation performance calculated on the BraTS validation set shows an average whole tumor dice score of 90% and increased robustness to missing image modalities by randomly excluding input MRI during training. Classification area under the curve scores are 93%, 94% and 82% on the TCIA test data and 94%, 86% and 87% on the GUH data for grade, IDH and 1p19q status respectively. We developed a fast, automatic pipeline to segment glioma and accurately predict important (molecular) markers based on pre-therapy MRI.

Objectives To explore the characteristics of IDH and TERT promoter mutations in gliomas in Chinese patients. Methods A total of 124 Chinese patients with gliomas were enrolled to study the frequencies of mutations in isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase promoter (TERTp). Among the 124 patients, 59 patients were enrolled to study the classification of gliomas based on mutations in IDH and TERTp. Results Isocitrate dehydrogenase mutations are positively correlated with a good prognosis but mutations in TERTp cannot predict prognoses independently. The combined analysis of the mutations of IDH and TERTp can predict the prognosis more accurately. Patients with IDH and TERTp glioma mutations have the best prognosis, followed by only IDH mutation patients and only TERTp mutation patients, which have the worst prognosis. IDH and TERTp mutations occur frequently in males, younger patients or lower‐grade patients. In contrast, only TERTp mutations occur frequently in females, older patients or higher‐grade patients. Conclusions Patients with IDH and TERTp glioma mutations have the best prognosis, and only IDH mutation patients and only TERTp mutation patients have the worst prognosis. Moreover, the molecular classification of gliomas by mutations of IDH and TERTp is not suitable for pediatric patients., Patients with IDH and TERTp glioma mutations have the best prognosis, and only IDH mutation patients and only TERTp mutation patients have the worst prognosis. Both IDH and TERTp mutations occur frequently in males, younger patients, and lower‐grade patients. In contrast, only TERTp mutations occur frequently in females, older patients, and higher‐grade patients. Moreover, the molecular classification of gliomas by mutations of IDH and TERTp is not suitable for pediatric patients.

International audience

Background: Gliomas can be classified into five molecular subgroups based on the status of IDH mutation, 1p/19q codeletion, and TERT promoter mutation, whereas they need to be obtained by biopsy or surgery. We aimed to use MRI-based radiomic approach to noninvasively predict the five molecular subgroups and assess its prognostic value in glioma. Methods: We retrospectively identified 357 patients with grade II-IV gliomas. We extracted radiomic features of tumor and/or edema from preoperative MRI. Features were selected using the least absolute shrinkage and selection operator (LASSO). The predictive model was developed by incorporating preoperative clinical data into the multiparametric MR radiomic signature constructed by machine learning. We compared the prognostic value of predictive molecular subgroups with actual molecular subgroups in predicting progression-free survival (PFS) and overall survival (OS). We developed prognostic nomograms to predict PFS and OS of patients. Findings: Age, tumor location, and LASSO-based multiparametric MR radiomic model yielded the highest performance in predicting IDH mutation status (AUC = 0.855). Decision tree-based multiparametric MR radiomic model performed the best in predicting 1p/19q codeletion (AUC = 0.796) and TERT promoter mutation (AUC = 0.849). The predictive molecular subgroups were comparable to actual molecular subgroups in predicting PFS (C-index: 0.710 vs 0.717, P = 0.890) and OS (C-index: 0.707 vs 0.720, P = 0.630). The prognostic nomograms yielded a C-index of 0.742 and 0.747 in predicting PFS and OS, respectively. Interpretation: Multiparametric MRI-based radiomics with machine learning can be useful for noninvasively detecting molecular subgroups and predicting survival in gliomas. Funding Statement: This work was supported by the National Natural Science Foundation of China (No: 81571664, 81871323, 81801665, 81702465 and U1804172); the National Natural Science Foundation of Guangdong Province (No: 2018B030311024); the Scientific Research General Project of Guangzhou Science Technology and Innovation Commission (No: 201707010328); the China Postdoctoral Science Foundation (No: 2016M600145), the Science and Technology Program of Henan Province (No: 182102310113, 192102310050 and 192102310123), and the Youth Innovation Fund of The First Affiliated Hospital of Zhengzhou University to Zhen-yu Zhang, the Key Research Projects of Henan Higher Education (No: 18A310033). Declaration of Interests: The authors declared no competing interest exists. Ethics Approval Statement: The institutional review board in all participating centers approved this retrospective study and waived the need to obtain written consent.

International audience; Purpose of review Magnetic resonance spectroscopy (MRS) may play a key role for the management of patients with glioma. We highlighted the utility of MRS in the noninvasive diagnosis of gliomas with mutations in isocitrate dehydrogenase (IDH) genes, by providing an overview of the neurochemical alterations observed in different glioma subtypes, as well as during treatment and progression, both in vivo and ex vivo.Recent findings D-2-hydroxyglutarate (2HG) decrease during anticancer treatments was recently shown to be associated with altered levels of other metabolites, including lactate, glutamate and glutathione, suggesting that tumour treatment leads to a metabolic reprogramming beyond 2HG depletion. In combination with 2HG quantification, cystathionine and glycine seem to be the most promising candidates for higher specific identification of glioma subtypes and follow-up of disease progression and response to treatment.Summary The implementation of advanced MRS methods in the routine clinical practice will allow the quantification of metabolites that are not detectable with conventional methods and may enable immediate, accurate diagnosis of gliomas, which is crucial for planning optimal therapeutic strategies and follow-up examinations. The role of different metabolites as predictors of patient outcome still needs to be elucidated.

Introduction According to the stem cell theory, two neurogenic niches in the adult human brain may harbor cells that initiate the formation of gliomas: The larger subventricular zone (SVZ) and the subgranular zone (SGZ) in the hippocampus. We wanted to explore whether defining molecular markers in low-grade gliomas (LGG; WHO grade II) are related to distance to the neurogenic niches. Methods Patients treated at two Norwegian university hospitals with population-based referral were included. Eligible patients had histopathological verified supratentorial low-grade glioma. IDH mutational status and 1p19q co-deletion status was retrospectively assessed. 159 patients were included, and semi-automatic tumor segmentation was done from pre-treatment T2-weighted (T2W) or Fluid-Attenuated Inversion Recovery (FLAIR) images. 3D maps showing the anatomical distribution of the tumors were then created for each of the three molecular subtypes (IDH mutated/1p19q co-deleted, IDH mutated and IDH wild-type). Both distance from tumor center and tumor border to the neurogenic niches were recorded. Results In this population-based cohort of previously untreated low-grade gliomas, we found that low-grade gliomas are more often found closer to the SVZ than the SGZ, but IDH wild-type tumors are more often found near SGZ. Conclusion Our study suggests that the stem cell origin of IDH wild-type and IDH mutated low-grade gliomas may be different.