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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.

INTRODUCTION Identifying IDH mutation status before treatment is essential for Lower-grade glioma (LrGG) treatment. We have previously revealed that IDH mutated LrGG consists of tumor tissues with significantly longer T1 and T2 relaxation time and is a useful radiological feature to identify IDH mutation status. The ratio of T1-weighted to T2-weighted signal intensity (rT1/T2) is a way to retrieve semi-quantitative relaxation time information of the tissue bypassing the need to perform relaxometry. This investigation aimed to elucidate the correlation between rT1/T2 and T1-, T2-relaxation time (-relax) in glioma tissue and to explore the possibility of rT1/T2 as a radiological surrogate marker to identify IDH mutation status in LrGG. MATERIALS AND METHODS We analyzed 8 LrGGs (IDHwt:4, IDHmt:2, IDHmt&1p19q-CODEL:2) in which relaxometry was performed. rT1/T2 maps were reconstructed as described in previous literature. Regions-of-interest were designed based on T2WI and FLAIR. The correlations between rT1/T2 and T1- and T2-relax were analyzed. Furthermore, We also investigated the correlation of IDH mutation status and rT1/T2. RESULTS 106,488 voxels were analyzed. The correlation between rT1/T2 and T1- and T2-relax were rT1/T2=1.6e-0.0003T1-relax and rT1/T2=1.2e-0.002T2-relax (R=0.77 and 0.70). rT1/T2 of IDH-wildtype tumor was significantly higher than that of IDH-mutant tumor (1.0 vs. 0.75, p< 0.0001). Voxel-wise analysis of rT1/T2 map was able to discriminate IDH-wildtype tumor from the mutant tumor with an AUC of 0.82. CONCLUSIONS rT1/T2, which can be calculated from MRI acquired during routine clinical practice, is a promising radiological surrogate marker to identify IDH mutation status in LrGG.

BACKGROUND Intraoperative detection of residual tumor and isocitrate dehydrogenase (IDH) mutations can assist in maximizing surgical resection beyond contrast enhancing margins and guide intraoperative surgical decision making for glioma patients. We aimed to evaluate the use of desorption electrospray ionization-mass spectrometry (DESI-MS) for intraoperative assessment of IDH mutations and estimation of tumor cell percentage (TCP). METHODS This is a prospective study using intraoperative DESI-MS analysis of freshly obtained tissue samples to evaluate IDH mutations via 2-hydroxyglutarate (2-HG) intensity and TCP via measurement of N-acetylaspartic acid (NAA) intensity and characteristic lipid profiles. These IDH mutation and TCP estimates were subsequently validated by a senior neuropathologist. RESULTS A total of 247 biopsies from a 49-patient study were previously collected and analyzed at Indiana University. Assessment of TCP in 203 margin and core biopsies based on NAA intensity yielded sensitivity, specificity, and accuracy values of 91, 76, and 83%, whereas TCP assessment based on 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%. Further validation of the methodology is being performed in an ongoing collaboration with Mayo Clinic-Jacksonville, where we have collected 178 biopsies from 24 patients. Preliminary results of IDH mutation assessments indicate 100% sensitivity, specificity, and accuracy. DISCUSSION/CONCLUSION We present a novel system to allow intraoperative evaluation of IDH status and to guide surgical resection by TCP measurement from tissue biopsies. Prospectively, we propose to modify our DESI-MS system by placing a surgical material (e.g. cottonoid) along the surgical margin and transferring material from the blot to a microscope slide prior to DESI-MS analysis. This will allow the retention of the spatial distribution of diagnostic molecules while analyzing a wall of the surgical cavity without the need for biopsy.

Tumor infiltrating lymphocytes (TILs) and programmed death ligand 1 (PD-L1) are targets of immune checkpoint inhibitors. Forty-three World Health Organization (WHO) grade II/III gliomas (39 IDH-mutant [mut], 4 IDH-wildtype [wt]) and 14 IDH-mut glioblastomas (GBM) were analyzed for TIL (CD3+; PD1+) infiltration and PD-L1 expression. Results were compared with the data of a previously published series of 117 IDH-wt glioblastomas. PD-L1 gene expression levels were evaluated in 677 diffuse gliomas grades II-IV from The Cancer Genome Atlas (TCGA) database. TIL and PD-L1 expression were observed in approximately half of WHO grade II/III gliomas. IDH-wt status was associated with significantly higher TIL infiltration and PD-L1 expression among all (grades II-IV) cases (n = 174, P < 0.001) and within the cohort of glioblastomas (n = 131, P < 0.001). In low-grade glioma (LGG) and glioblastoma cohorts of TCGA, significantly higher PD-L1 gene expression levels were evident in IDH-wt compared with IDH-mut samples (LGG: N = 516; P = 1.933e-11, GBM: N = 161; P < 0.009). Lower PD-L1 gene expression was associated with increased promoter methylation (Spearman correlation coefficient -0.36; P < 0.01) in the LGG cohort of TCGA. IDH-mut gliomas had higher PD-L1 gene promoter methylation levels than IDH-wt gliomas (P < 0.01). The immunological tumor microenvironment of diffuse gliomas differs in association with IDH mutation status. IDH-wt gliomas display a more prominent TIL infiltration and higher PD-L1 expression than IDH-mut cases. Mechanistically this may be at least in part due to differential PD-L1 gene promoter methylation levels. Our findings may be relevant for immune modulatory treatment strategies in glioma patients.

OBJECTIVE Non-invasive and accurate diagnostic techniques to detect isocitrate dehydrogenase (IDH) mutant glioma may have great potential in routine clinical practice. With this in mind, we performed a multimodal diagnostic approach to predict the IDH mutation status in newly diagnosed gliomas using: 2-Hydroxyglutarate (2HG) single-voxel spectroscopy (SVS), IDH-mutant cell-free tumor-derived DNA (tDNA) in the CSF, in addition to 2HG (D- and L- forms) concentration measurement in the CSF. METHODS 2HG MR spectroscopy was obtained in 18 patients with a newly diagnosed IDH-mutant glioma. The IDH1/2 mutation status was determined using next generation sequencing in the glioma tissue and in the CSF-tDNA (n=55). In addition, in a subset of patients (n=15), 2HG concentrations were measured in the CSF using liquid chromatography-tandem mass spectrometry (LCMS). Ratios of D-and L-2HG were used to evaluate differences in 2HG accumulation in tumors. RESULTS IDH mutations were correctly predicted using the 2HG spectroscopy with 93.3% sensitivity (17/18, 95% CI, 85.3–100%) and 100% specificity (18/18, 95% CI, 88.6–100%). The IDH mutation in the CSF-tDNA was successfully detected with 100% specificity (95% CI, 87.6–100%) and 73.3% sensitivity (95% CI, 65.6–88.3%). The range of the IDH mutation variant allele frequency (VAF) in the CSF-tDNA was 1.53- 47.9%. 2HG detection in the CSF revealed higher sensitivity (100%) and specificity (100%) in a small subset of patients (n = 7). The D-2HG/L-2HG ratios in IDH-mutant cases varied between 1.2 – 13.8, compared with 0.1 – 0.5 in IDH wild-type gliomas. CONCLUSION Our findings suggest that 2HG spectroscopy and 2HG detection in the CSF are two reliable methods in IDH mutation prediction in gliomas. On the other hand, the sensitivity of genomic IDH mutation detection in the CSF-tDNA was lower when compared with 2HG detection. Further studies are needed to complement the findings of our exploratory analysis.

Background Mutations in the isocitrate dehydrogenase (IDH) enzyme affect 40% of gliomas and represent a major diagnostic and prognostic marker. The goals of this study were to evaluate the performance of noninvasive magnetic resonance spectroscopy (MRS) methods to determine the IDH status of patients with brain gliomas through detection of the oncometabolite 2-hydroxyglutarate (2HG) and to compare performance of these methods with DNA sequencing and tissue 2HG analysis. Methods Twenty-four subjects with suspected diagnosis of low-grade glioma were included prospectively in the study. For all subjects, MRS data were acquired at 3T using 2 MRS methods, edited MRS using Mescher-Garwood point-resolved spectroscopy (MEGA-PRESS) sequence and a PRESS sequence optimized for 2HG detection, using a volume of interest larger than 6 mL. IDH mutational status was determined by a combination of automated immunohistochemical analysis and Sanger sequencing. Levels of 2HG in tissue samples measured by gas chromatography-mass spectrometry were compared with those estimated by MRS. Results Edited MRS provided 100% specificity and 100% sensitivity in the detection of 2HG. The 2HG levels estimated by this technique were in line with those derived from tissue samples. Optimized PRESS provided lower performance, in agreement with previous findings. Conclusions Our results suggest that edited MRS is one of the most reliable tools to predict IDH mutation noninvasively, showing high sensitivity and specificity for 2HG detection. Integrating edited MRS in clinical practice may be highly beneficial for noninvasive diagnosis of glioma, prognostic assessment, and treatment planning.

Due to the decreasing prevalence of IDH1 mutations in older patients, the 2016 World Health Organization (WHO) classification of brain tumors proposed not to perform sequencing for isocitrate dehydrogenase (IDH) in glioblastoma patients ≥55 years old. We present a cost-effectiveness analysis to estimate the financial impact of these guidelines.From 2010 to 2015 we performed 1023 IDH tests in gliomas, amounting to ~$1.09 million in direct laboratory test costs. Samples were tested using R132H-specific immunohistochemistry, DNA sequencing validated for detection of noncanonical IDH1/2 mutations, or both methods.In cases tested by DNA sequencing, the fraction of non-R132H mutations was 5.4%, which included only 2 high-grade gliomas in patients ≥55 years (0.9%). When remodeling the optimal age cutoff in our patient population using 5-year age-binning, we found a 10-times higher pretest probability for the presence of a noncanonical IDH1 mutation in the setting of a negative IDH1-R132H immunohistochemistry result in patients55 years. Applying the independently confirmed age cutoff of 55 years to glioblastoma patients (64%) would result in $403200 saved (43%). By not performing sequencing in patients ≥55 years, the turn-around time to final integrated neuropathological diagnosis is reduced by 53%, allowing these patients to gain earlier benefits from personalized genomic medicine.The negligible prevalence of noncanonical IDH mutations in glioblastoma patients ≥55 years argues against universal IDH sequencing in this population. We predict that adoption of this age-based sequencing cutoff recommendation from the 2016 WHO guidelines will result in significant cost and time savings throughout the global health care system.

OBJECTIVE: Creating a machine learning model using diffusion tensor and kurtosis images are effective for malignancy diagnosing of glioma. However, it is unknown whether an IDH mutation, which is the most important mutation in glioma, can be predicted using diffusion tensor and kurtosis images. The purpose of our research was to predict the IDH mutation by using diffusion tensor and kurtosis images based on a machine learning. METHODS: Between August 2014 and July 2017, 38 consecutive patients with suspected glioma and preoperative MRI including diffusion coefficient (ADC), fractional anisotropy (FA), mean kurtosis (MK), were included in the study. All IDH mutations were identified by Sanger sequencing. A volume of interest (VOI) was created manually and applied to T2-weighted images, diffusion-weighted images (DWI), ADC, FA, MK. 476 per imaging sequence and 2856 features were extracted. RESULTS: 39 datasets were obtained. The number of cases for the IDH mutation and wild-type was 21 cases of the IDH1 mutation (3 diffuse astrocytoma, 8 anaplastic astrocytoma, 4 oligodendroglioma, 3 anaplastic oligodendroglioma, 3 glioblastoma, 18 cases of wild-type(2 anaplastic astrocytoma, 16 glioblastoma). An IDH2 mutation was not observed in our cases. Features were selected by using recursive feature elimination (RFE). The most accurate machine learning model was created using the extracted eight features from ADC, Fa, and MK. The best AUC was 0.95 ± 0.02 in a support vector machine (SVM). Discussion: Imaging sequences useful for the IDH1 mutation identification are ADC, MK, FA, similar to malignancy diagnosing of glioma. However, useful features were different. The machine learning models using diffusion images may be useful for identifying the IDH1 mutations.

BACKROUND & PURPOSE: The presence of mutation in the encoding gene of isocitrate-dehydrogenase (IDH) enzyme has been defined as a molecular biomarker by World Health Organisation (WHO) in 2016 in the diagnosis and differentiation of gliomas. MRI techniques have been widely used in the radiological evaluation of gliomas. Among advanced MRI techniques, Dynamic Susceptibility Contrast Perfusion- Weighted Imaging (DSC - PWI) appears as a recently established technique for histopathological WHO grading of gliomas. In this study, we aimed to investigate whether DSC - PWI, enhanced by texture analysis and machine learning, can stratify gliomas according to their IDH mutation status. MATERIAL & METHODS: 208 patients (F/ M: 84 /119, median age: 47 [range: 21–81 year]) from a multicenter setting, who have been immunohistopathologically diagnosed with gliomas (IDH positive / negative: 98 /105) were prospectively included in our study. The raw data from DSC - PWI was processed on a dedicated workstation to create leakage-corrected relative cerebral blood volume (rCBV) maps. Tumours were manually segmented and registered to rCBV maps. rCBV maps were used to generate distribution and rotational invariant Haralick texture features over the tumour mask. The predictive power of the extracted features in differentiating between IDH status was assessed in a 2-fold cross-validation setting of 1000 iterations using support vector machine and multinomial ordinal regression, respectively. RESULTS: In the differentiation of IDH-mutant tumours from wild-type ones, overall sensitivity and specificity rates for the rCBV values were 68% and 81%, respectively. Nine of the ten classical histogram statistics and twelve texture features appeared significantly different across mutation status (p< 0.05) when using a non parametric Wilcoxon test. CONCLUSION: Preliminary results are promising in the differentiation of gliomas with DSC- PWI on the basis of IDH mutation status, especially regarding the high specificity rates obtained using features from rCBV data.

BACKGROUND: Isocitrate dehydrogenase (IDH) mutation (IDH-mut) is an important marker for survival in diffuse glioma patients. Patients with an IDH-mut glioma have a better prognosis but more often suffer from epilepsy. Patients with a wildtype glioma (IDH-wt) are generally older and more often have cognitive deficits. Regardless of IDH status, cognitive deficits in glioma patients are associated with altered functional connectivity throughout the brain as calculated through statistical correlations between regional neurophysiological activity patterns measured with magnetoencephalography (MEG). Cognitive variation in glioma patients is specifically related to altered theta (4–8 Hz) and alpha (8–13 Hz) band functional connectivity. We investigated whether global brain functional connectivity differs between patients with an IDH-mut and IDH-wt diffuse glioma, and whether this measure reflects variations in cognitive functioning in these subpopulations beyond the associated differences in age and epilepsy. MATERIAL AND METHODS: IDH mutation status was determined in 54 diffuse glioma patients via immunohistochemistry (31 IDH-mut, 23 IDH-wt). We recorded MEG and patients underwent cognitive testing. Global functional connectivity between 78 atlas regions spanning the entire cortex was calculated in the theta and alpha frequency bands. Group differences in cognition and global functional connectivity were tested. Next, the association between functional connectivity and cognitive performance was tested. RESULTS: As expected, patients with IDH-mut glioma were younger (P = 0.001) and more often had epilepsy (P = 0.010). Patients with IDH-wt glioma showed poorer verbal memory (P = 0.027, corrected for age, education and presence of epilepsy). More importantly, patients with IDH-wt glioma had lower functional connectivity in the alpha band than patients with IDH-mut glioma (P = 0.015, corrected for age and presence of epilepsy). Alpha band functional connectivity was positively associated with executive functioning (P = 0.049) and information processing speed (P = 0.009), regardless of IDH status and corrected for age, education, and presence of epilepsy. CONCLUSION: These results suggest that global functional connectivity is lower in patients with IDH-wt diffuse glioma compared to patients with IDH-mut diffuse glioma. Moreover, functional connectivity relates to cognitive performance in both IDH-wt and IDH-mut diffuse glioma patients, regardless of age, education and presence of epilepsy. These findings contribute to our understanding of cognitive functioning in patients with diffuse glioma in general, and cognitive deficits in patients with IDH-wt glioma specifically.

BACKGROUND Grade II and III gliomas have variable clinical behaviors, showing the distinct molecular genetic alterations from glioblastoma (GBM), many of which eventually transform into more aggressive tumors. Since the classifications of grade II/III gliomas based on the genetic alterations have been recently emerging, it is now a trend to include molecular data into the standard diagnostic algorithm of glioma. METHODS Here we sequenced TERT promoter mutational status (TERTp-mut) in the DNA of 377 grade II/III gliomas and analyzed the clinical factors, molecular aberrations, and transcriptome profiles. RESULTS We found that TERTp-mut occurred in 145 of 377 grade II and III gliomas (38.5%), mutually exclusive with a TP53 mutation (TP53-mut; P < .001) and coincident with a 1p/19q co-deletion (P = .002). TERTp-mut was an independent predictive factor of a good prognosis in all patients (P = .048). It has been an independent factor associated with a good outcome in the IDH mutation (IDH-mut) subgroup (P = .018), but it has also been associated with a poor outcome in the IDH wild-type (IDH-wt) subgroup (P = .049). Combining TERTp-mut and IDH-mut allowed the grade II/III malignancies to be reclassified into IDH-mut/TERTp-mut, IDH-mut only, TERTp-mut only, and IDH-wt/TERTp-wt. 1p/19q co-deletion, TP53-muts, Ki-67 expression differences, and p-MET expression differences characterized IDH-mut/TERTp-mut, IDH-mut only, TERTp-mut only, and IDH-wt/TERTp-wt subtypes, respectively. CONCLUSIONS Our results showed that TERTp-mut combined with IDH-mut allowed simple classification of grade II/III gliomas for stratifying patients and clarifying diagnostic accuracy by supplementing standard histopathological criteria.

BACKGROUND: Glioblastoma carries a poor prognosis primarily because of its high rate of recurrence. Similarly, anaplastic gliomas without IDH mutation present poor prognosis similar to glioblastoma. The ability to predict the recurrence pattern and timing would be highly useful for determining effective treatment strategies. We here examined high grade glioma to determine their recurrence pattern and the expression of CD133, a cell surface marker of glioma stem cells. METHODS: We retrospectively analyzed 198 patients with high grade gliomas (glioblastoma 112 cases, anaplastic glioma 86 patients,). Patients' characteristics, recurrence pattern, and prognosis were obtained from medical records. CD133 expression was examined by western blotting and immunohistochemistry, and IDH mutation was examined by direct sequencing. RESULTS: Of the 112 glioblastoma patients, 99 suffered recurrence. The first recurrence was local in 77 patients and distant in 22 patients. Among the factors to predict the pattern of recurrence, CD133 expression was significantly higher in distant than in local recurrence. As for anaplastic gliomas, of the 86 patients, 58 carried IDH mutation and 39 patients experienced recurrence. The first recurrence was local and distant in 26 and 13 patients, respectively. Patients without IDH mutation exhibited significantly higher CD133 expression and more frequent distant recurrence than those with IDH mutation. Patients with high CD133 expression showed shorter overall survival. CONCLUSIONS: The expression of CD133 may be a predictor of the pattern and timing of recurrence of primary glioblastoma. Patients with anaplastic gliomas without IDH mutation experience distant recurrence and exhibit high CD133 expression, indicating that this subset may share some malignant characteristics with glioblastoma. SECONDARY CATEGORY: Clinical Neuro-Oncology.