State of the Art in Low-Grade Glioma Management: Insights From Isocitrate Dehydrogenase and Beyond.

Low-grade gliomas present a formidable challenge in neuro-oncology because of the challenges imposed by the blood-brain barrier, predilection for the young adult population, and propensity for recurrence. In the past two decades, the systematic examination of genomic alterations in adults and children with primary brain tumors has uncovered profound new insights into the pathogenesis of these tumors, resulting in more accurate tumor classification and prognostication. It also identified several common recurrent genomic alterations that now define specific brain tumor subtypes and have provided a new opportunity for molecularly targeted therapeutic intervention. Adult-type diffuse low-grade gliomas are frequently associated with mutations in isocitrate dehydrogenase 1 and 2 (IDH1/2), resulting in production of 2-hydroxyglutarate, an oncometabolite important for tumorigenesis. Recent studies of IDH inhibitors have yielded promising results in patients at early stages of disease with prolonged progression-free survival (PFS) and delayed time to radiation and chemotherapy. Pediatric-type gliomas have high rates of alterations in BRAF, including BRAF V600E point mutations or BRAF-KIAA1549 rearrangements. BRAF inhibitors, often combined with MEK inhibitors, have resulted in radiographic response and improved PFS in these patients. This article reviews emerging approaches to the treatment of low-grade gliomas, including a discussion of targeted therapies and how they integrate with the current treatment modalities of surgical resection, chemotherapy, and radiation.

Glioma.

Gliomas are primary brain tumours that are thought to develop from neural stem or progenitor cells that carry tumour-initiating genetic alterations. Based on microscopic appearance and molecular characteristics, they are classified according to the WHO classification of central nervous system (CNS) tumours and graded into CNS WHO grades 1-4 from a low to high grade of malignancy. Diffusely infiltrating gliomas in adults comprise three tumour types with distinct natural course of disease, response to treatment and outcome: isocitrate dehydrogenase (IDH)-mutant and 1p/19q-codeleted oligodendrogliomas with the best prognosis; IDH-mutant astrocytomas with intermediate outcome; and IDH-wild-type glioblastomas with poor prognosis. Pilocytic astrocytoma is the most common glioma in children and is characterized by circumscribed growth, frequent BRAF alterations and favourable prognosis. Diffuse gliomas in children are divided into clinically indolent low-grade tumours and high-grade tumours with aggressive behaviour, with histone 3 K27-altered diffuse midline glioma being the leading cause of glioma-related death in children. Ependymal tumours are subdivided into biologically and prognostically distinct types on the basis of histology, molecular biomarkers and location. Although surgery, radiotherapy and alkylating agent chemotherapy are the mainstay of glioma treatment, individually tailored strategies based on tumour-intrinsic dominant signalling pathways have improved outcome in subsets of patients.

MRI Scoring Systems for Predicting Isocitrate Dehydrogenase Mutation and Chromosome 1p/19q Codeletion in Adult-type Diffuse Glioma Lacking Contrast Enhancement.

Background According to 2021 World Health Organization criteria, adult-type diffuse gliomas include glioblastoma, isocitrate dehydrogenase (IDH)-wildtype; oligodendroglioma, IDH-mutant and 1p/19q-codeleted; and astrocytoma, IDH-mutant, even when contrast enhancement is lacking. Purpose To develop and validate simple scoring systems for predicting IDH and subsequent 1p/19q codeletion status in gliomas without contrast enhancement using standard clinical MRI sequences. Materials and Methods This retrospective study included adult-type diffuse gliomas lacking contrast at contrast-enhanced MRI from two tertiary referral hospitals between January 2012 and April 2022 with diagnoses confirmed at pathology. IDH status was predicted primarily by using T2-fluid-attenuated inversion recovery (FLAIR) mismatch sign, followed by 1p/19q codeletion prediction. A visual rating of MRI features, apparent diffusion coefficient (ADC) ratio, and relative cerebral blood volume was measured. Scoring systems were developed through univariable and multivariable logistic regressions and underwent calibration and discrimination, including internal and external validation. Results For the internal validation cohort, 237 patients were included (mean age, 44.4 years ± 14.4 [SD]; 136 male patients; 193 patients in IDH prediction and 163 patients in 1p/19q prediction). For the external validation cohort, 35 patients were included (46.1 years ± 15.3; 20 male patients; 28 patients in IDH prediction and 24 patients in 1p/19q prediction). The T2-FLAIR mismatch sign demonstrated 100% specificity and 100% positive predictive value for IDH mutation. IDH status prediction scoring system for tumors without mismatch sign included age, ADC ratio, and morphologic characteristics, whereas 1p/19q codeletion prediction for IDH-mutant gliomas included ADC ratio, cortical involvement, and mismatch sign. For IDH status and 1p/19q codeletion prediction, bootstrap-corrected areas under the receiver operating characteristic curve were 0.86 (95% CI: 0.81, 0.90) and 0.73 (95% CI: 0.65, 0.81), respectively, whereas at external validation they were 0.99 (95% CI: 0.98, 1.0) and 0.88 (95% CI: 0.63, 1.0). Conclusion The T2-FLAIR mismatch sign and scoring systems using standard clinical MRI predicted IDH and 1p/19q codeletion status in gliomas lacking contrast enhancement. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Badve and Hodges in this issue.

Structural- and DTI- MRI enable automated prediction of IDH Mutation Status in CNS WHO Grade 2-4 glioma patients: a deep Radiomics Approach.

BACKGROUND: The role of isocitrate dehydrogenase (IDH) mutation status for glioma stratification and prognosis is established. While structural magnetic resonance image (MRI) is a promising biomarker, it may not be sufficient for non-invasive characterisation of IDH mutation status. We investigated the diagnostic value of combined diffusion tensor imaging (DTI) and structural MRI enhanced by a deep radiomics approach based on convolutional neural networks (CNNs) and support vector machine (SVM), to determine the IDH mutation status in Central Nervous System World Health Organization (CNS WHO) grade 2-4 gliomas. METHODS: This retrospective study analyzed the DTI-derived fractional anisotropy (FA) and mean diffusivity (MD) images and structural images including fluid attenuated inversion recovery (FLAIR), non-enhanced T1-, and T2-weighted images of 206 treatment-naïve gliomas, including 146 IDH mutant and 60 IDH-wildtype ones. The lesions were manually segmented by experienced neuroradiologists and the masks were applied to the FA and MD maps. Deep radiomics features were extracted from each subject by applying a pre-trained CNN and statistical description. An SVM classifier was applied to predict IDH status using imaging features in combination with demographic data. RESULTS: We comparatively assessed the CNN-SVM classifier performance in predicting IDH mutation status using standalone and combined structural and DTI-based imaging features. Combined imaging features surpassed stand-alone modalities for the prediction of IDH mutation status [area under the curve (AUC) = 0.846; sensitivity = 0.925; and specificity = 0.567]. Importantly, optimal model performance was noted following the addition of demographic data (patients' age) to structural and DTI imaging features [area under the curve (AUC) = 0.847; sensitivity = 0.911; and specificity = 0.617]. CONCLUSIONS: Imaging features derived from DTI-based FA and MD maps combined with structural MRI, have superior diagnostic value to that provided by standalone structural or DTI sequences. In combination with demographic information, this CNN-SVM model offers a further enhanced non-invasive prediction of IDH mutation status in gliomas.

Transformation of IDH-wildtype glioblastoma to gliosarcoma with features of osteosarcoma.

Gliosarcoma (GS) is a rare variant of IDH-wildtype glioblastoma. It is classified as grade 4 in the latest WHO CNS classification of both glial and mesenchymal components. Gliosarcoma may arise de novo or secondary from glioblastoma. It occurs in up to 2% of patients diagnosed with glioblastoma. We present a case report of a 51-year-old patient who was initially diagnosed with glioblastoma multiforme, which transformed into secondary gliosarcoma with an osteosarcoma component 16 months after the initial diagnosis. We believe that increasing reporting of secondary gliosarcoma (sGS) will be helpful in understanding, diagnosing and providing more effective treatment for this cancer.

IDH1 mutation produces R-2-hydroxyglutarate (R-2HG) and induces mir-182-5p expression to regulate cell cycle and tumor formation in glioma.

BACKGROUND: Mutations in isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2), are present in most gliomas. IDH1 mutation is an important prognostic marker in glioma. However, its regulatory mechanism in glioma remains incompletely understood. RESULTS: miR-182-5p expression was increased within IDH1-mutant glioma specimens according to TCGA, CGGA, and online dataset GSE119740, as well as collected clinical samples. (R)-2-hydroxyglutarate ((R)-2HG) treatment up-regulated the expression of miR-182-5p, enhanced glioma cell proliferation, and suppressed apoptosis; miR-182-5p inhibition partially eliminated the oncogenic effects of R-2HG upon glioma cells. By direct binding to Cyclin Dependent Kinase Inhibitor 2 C (CDKN2C) 3'UTR, miR-182-5p inhibited CDKN2C expression. Regarding cellular functions, CDKN2C knockdown promoted R-2HG-treated glioma cell viability, suppressed apoptosis, and relieved cell cycle arrest. Furthermore, CDKN2C knockdown partially attenuated the effects of miR-182-5p inhibition on cell phenotypes. Moreover, CDKN2C knockdown exerted opposite effects on cell cycle check point and apoptosis markers to those of miR-182-5p inhibition; also, CDKN2C knockdown partially attenuated the functions of miR-182-5p inhibition in cell cycle check point and apoptosis markers. The engineered CS-NPs (antagomir-182-5p) effectively encapsulated and delivered antagomir-182-5p, enhancing anti-tumor efficacy in vivo, indicating the therapeutic potential of CS-NPs(antagomir-182-5p) in targeting the miR-182-5p/CDKN2C axis against R-2HG-driven oncogenesis in mice models. CONCLUSIONS: These insights highlight the potential of CS-NPs(antagomir-182-5p) to target the miR-182-5p/CDKN2C axis, offering a promising therapeutic avenue against R-2HG's oncogenic influence to glioma.

Cost-effectiveness of ivosidenib versus chemotherapy for previously treated IDH1-mutant advanced intrahepatic cholangiocarcinoma in Taiwan.

BACKGROUND: International guidelines recommend ivosidenib followed by modified FOLFOX (mFOLFOX) for advanced intrahepatic cholangiocarcinoma (ICC) with isocitrate dehydrogenase 1 (IDH1) mutations. Taiwan National Health Insurance covers only fluorouracil/leucovorin (5-FU/LV) chemotherapy for this ICC group, and there has been no prior economic evaluation of ivosidenib. Therefore, we aimed to assess ivosidenib's cost-effectiveness in previously treated, advanced ICC-presenting IDH1 mutations compared with mFOLFOX or 5-FU/LV. METHODS: A 3-state partitioned survival model was employed to assess ivosidenib's cost-effectiveness over a 10-year horizon with a 3% discount rate, setting the willingness-to-pay threshold at 3 times the 2022 GDP per capita. Efficacy data for Ivosidenib, mFOLFOX, and 5-FU/LV were sourced from the ClarIDHy, ABC06, and NIFTY trials, respectively. Ivosidenib's cost was assumed to be NT$10,402/500 mg. Primary outcomes included incremental cost-effectiveness ratios (ICERs) and net monetary benefit. Deterministic sensitivity analyses (DSA) and probabilistic sensitivity analyses (PSA) were employed to evaluate uncertainty and explore price reduction scenarios. RESULTS: Ivosidenib exhibited ICERs of NT$6,268,528 and NT$5,670,555 compared with mFOLFOX and 5-FU/LV, respectively, both exceeding the established threshold. PSA revealed that ivosidenib was unlikely to be cost-effective, except when it was reduced to NT$4,161 and NT$5,201/500 mg when compared with mFOLFOX and 5-FU/LV, respectively. DSA underscored the significant influence of ivosidenib's cost and utility values on estimate uncertainty. CONCLUSIONS: At NT$10,402/500 mg, ivosidenib was not cost-effective for IDH1-mutant ICC patients compared with mFOLFOX or 5-FU/LV, indicating that a 50-60% price reduction is necessary for ivosidenib to be cost-effective in this patient group.

Isocitrate dehydrogenase 1 upregulation in urinary extracellular vesicles from proximal tubules of type 2 diabetic rats.

Diabetic nephropathy (DN) is a major cause of chronic kidney disease. Microalbuminuria is currently the most common non-invasive biomarker for the early diagnosis of DN. However, renal structural damage may have advanced when albuminuria is detected. In this study, we sought biomarkers for early DN diagnosis through proteomic analysis of urinary extracellular vesicles (uEVs) from type 2 diabetic model rats and normal controls. Isocitrate dehydrogenase 1 (IDH1) was significantly increased in uEVs from diabetic model rats at the early stage despite minimal differences in albuminuria between the groups. Calorie restriction significantly suppressed the increase in IDH1 in uEVs and 24-hour urinary albumin excretion, suggesting that the increase in IDH1 in uEVs was associated with the progression of DN. Additionally, we investigated the origin of IDH1-containing uEVs based on their surface sugar chains. Lectin affinity enrichment and immunohistochemical staining showed that IDH1-containing uEVs were derived from proximal tubules. These findings suggest that the increase in IDH1 in uEVs reflects pathophysiological alterations in the proximal tubules and that IDH1 in uEVs may serve as a potential biomarker of DN in the proximal tubules.

SRC inhibition enables formation of a growth suppressive MAGI1-PP2A complex in isocitrate dehydrogenase-mutant cholangiocarcinoma.

Intrahepatic cholangiocarcinoma (ICC) is an aggressive bile duct malignancy that frequently exhibits isocitrate dehydrogenase (IDH1/IDH2) mutations. Mutant IDH (IDHm) ICC is dependent on SRC kinase for growth and survival and is hypersensitive to inhibition by dasatinib, but the molecular mechanism underlying this sensitivity is unclear. We found that dasatinib reduced p70 S6 kinase (S6K) and ribosomal protein S6 (S6), leading to substantial reductions in cell size and de novo protein synthesis. Using an unbiased phosphoproteomic screen, we identified membrane-associated guanylate kinase, WW, and PDZ domain containing 1 (MAGI1) as an SRC substrate in IDHm ICC. Biochemical and functional assays further showed that SRC inhibits a latent tumor-suppressing function of the MAGI1-protein phosphatase 2A (PP2A) complex to activate S6K/S6 signaling in IDHm ICC. Inhibiting SRC led to activation and increased access of PP2A to dephosphorylate S6K, resulting in cell death. Evidence from patient tissue and cell line models revealed that both intrinsic and extrinsic resistance to dasatinib is due to increased phospho-S6 (pS6). To block pS6, we paired dasatinib with the S6K/AKT inhibitor M2698, which led to a marked reduction in pS6 in IDHm ICC cell lines and patient-derived organoids in vitro and substantial growth inhibition in ICC patient-derived xenografts in vivo. Together, these results elucidated the mechanism of action of dasatinib in IDHm ICC, revealed a signaling complex regulating S6K phosphorylation independent of mTOR, suggested markers for dasatinib sensitivity, and described a combination therapy for IDHm ICC that may be actionable in the clinic.

Large enrichments in fatty acid 2H/1H ratios distinguish respiration from aerobic fermentation in yeast Saccharomyces cerevisiae.

Shifts in the hydrogen stable isotopic composition (2H/1H ratio) of lipids relative to water (lipid/water 2H-fractionation) at natural abundances reflect different sources of the central cellular reductant, NADPH, in bacteria. Here, we demonstrate that lipid/water 2H-fractionation (2εfattyacid/water) can also constrain the relative importance of key NADPH pathways in eukaryotes. We used the metabolically flexible yeast Saccharomyces cerevisiae, a microbial model for respiratory and fermentative metabolism in industry and medicine, to investigate 2εfattyacid/water. In chemostats, fatty acids from glycerol-respiring cells were >550‰ 2H-enriched compared to those from cells aerobically fermenting sugars via overflow metabolism, a hallmark feature in cancer. Faster growth decreased 2H/1H ratios, particularly in glycerol-respiring cells by 200‰. Variations in the activities and kinetic isotope effects among NADP+-reducing enzymes indicate cytosolic NADPH supply as the primary control on 2εfattyacid/water. Contributions of cytosolic isocitrate dehydrogenase (cIDH) to NAPDH production drive large 2H-enrichments with substrate metabolism (cIDH is absent during fermentation but contributes up to 20 percent NAPDH during respiration) and slower growth on glycerol (11 percent more NADPH from cIDH). Shifts in NADPH demand associated with cellular lipid abundance explain smaller 2εfattyacid/water variations (<30‰) with growth rate during fermentation. Consistent with these results, tests of murine liver cells had 2H-enriched lipids from slower-growing, healthy respiring cells relative to fast-growing, fermenting hepatocellular carcinoma. Our findings point to the broad potential of lipid 2H/1H ratios as a passive natural tracker of eukaryotic metabolism with applications to distinguish health and disease, complementing studies that rely on complex isotope-tracer addition methods.

A longer time to relapse is associated with a larger increase in differences between paired primary and recurrent IDH wild-type glioblastomas at both the transcriptomic and genomic levels.

Glioblastoma (GBM) is the most common malignant brain tumor in adults, which remains incurable and often recurs rapidly after initial therapy. While large efforts have been dedicated to uncover genomic/transcriptomic alternations associated with the recurrence of GBMs, the evolutionary trajectories of matched pairs of primary and recurrent (P-R) GBMs remain largely elusive. It remains challenging to identify genes associated with time to relapse (TTR) and construct a stable and effective prognostic model for predicting TTR of primary GBM patients. By integrating RNA-sequencing and genomic data from multiple datasets of patient-matched longitudinal GBMs of isocitrate dehydrogenase wild-type (IDH-wt), here we examined the associations of TTR with heterogeneities between paired P-R GBMs in gene expression profiles, tumor mutation burden (TMB), and microenvironment. Our results revealed a positive correlation between TTR and transcriptomic/genomic differences between paired P-R GBMs, higher percentages of non-mesenchymal-to-mesenchymal transition and mesenchymal subtype for patients with a short TTR than for those with a long TTR, a high correlation between paired P-R GBMs in gene expression profiles and TMB, and a negative correlation between the fitting level of such a paired P-R GBM correlation and TTR. According to these observations, we identified 55 TTR-associated genes and thereby constructed a seven-gene (ZSCAN10, SIGLEC14, GHRHR, TBX15, TAS2R1, CDKL1, and CD101) prognostic model for predicting TTR of primary IDH-wt GBM patients using univariate/multivariate Cox regression analyses. The risk scores estimated by the model were significantly negatively correlated with TTR in the training set and two independent testing sets. The model also segregated IDH-wt GBM patients into two groups with significantly divergent progression-free survival outcomes and showed promising performance for predicting 1-, 2-, and 3-year progression-free survival rates in all training and testing sets. Our findings provide new insights into the molecular understanding of GBM progression at recurrence and potential targets for therapeutic treatments.

Active site remodeling in tumor-relevant IDH1 mutants drives distinct kinetic features and potential resistance mechanisms.

Mutations in human isocitrate dehydrogenase 1 (IDH1) drive tumor formation in a variety of cancers by replacing its conventional activity with a neomorphic activity that generates an oncometabolite. Little is understood of the mechanistic differences among tumor-driving IDH1 mutants. We previously reported that the R132Q mutant unusually preserves conventional activity while catalyzing robust oncometabolite production, allowing an opportunity to compare these reaction mechanisms within a single active site. Here, we employ static and dynamic structural methods and observe that, compared to R132H, the R132Q active site adopts a conformation primed for catalysis with optimized substrate binding and hydride transfer to drive improved conventional and neomorphic activity over R132H. This active site remodeling reveals a possible mechanism of resistance to selective mutant IDH1 therapeutic inhibitors. This work enhances our understanding of fundamental IDH1 mechanisms while pinpointing regions for improving inhibitor selectivity.

Comprehensive analysis of the REST transcription factor regulatory networks in IDH mutant and IDH wild-type glioma cell lines and tumors.

The RE1-silencing transcription factor (REST) acts either as a repressor or activator of transcription depending on the genomic and cellular context. REST is a key player in brain cell differentiation by inducing chromatin modifications, including DNA methylation, in a proximity of its binding sites. Its dysfunction may contribute to oncogenesis. Mutations in IDH1/2 significantly change the epigenome contributing to blockade of cell differentiation and glioma development. We aimed at defining how REST modulates gene activation and repression in the context of the IDH mutation-related phenotype in gliomas. We studied the effects of REST knockdown, genome wide occurrence of REST binding sites, and DNA methylation of REST motifs in IDH wild type and IDH mutant gliomas. We found that REST target genes, REST binding patterns, and TF motif occurrence proximal to REST binding sites differed in IDH wild-type and mutant gliomas. Among differentially expressed REST targets were genes involved in glial cell differentiation and extracellular matrix organization, some of which were differentially methylated at promoters or gene bodies. REST knockdown differently impacted invasion of the parental or IDH1 mutant glioma cells. The canonical REST-repressed gene targets showed significant correlation with the GBM NPC-like cellular state. Interestingly, results of REST or KAISO silencing suggested the interplay between these TFs in regulation of REST-activated and repressed targets. The identified gene regulatory networks and putative REST cooperativity with other TFs, such as KAISO, show distinct REST target regulatory networks in IDH-WT and IDH-MUT gliomas, without concomitant DNA methylation changes. We conclude that REST could be an important therapeutic target in gliomas.

Relaxation Along a Fictitious Field, continuous wave T1rho, adiabatic T1rho and adiabatic T2rho imaging of human gliomas at 3T: A feasibility study.

In pre-clinical models of brain gliomas, Relaxation Along a Fictitious Field in second rotating frame (TRAFF2), continues wave T1rho (T1ρcw), adiabatic T1rho (T1ρadiab), and adiabatic T2rho (T2ρadiab) relaxation time mappings have demonstrated potential to non-invasively characterize brain gliomas. Our aim was to evaluate the feasibility and potential of 4 different spin lock methods at 3T to characterize primary brain glioma. 22 patients (26-72 years) with suspected primary glioma. T1ρcw was performed using pulse peak amplitude of 500Hz and pulse train durations of 40 and 80 ms while the corresponding values for T1ρadiab, T2ρadiab, TRAFF2 were 500/500/500Hz and 48 and 96, 64 and 112, 45 and 90 ms, respectively. The parametric maps were calculated using a monoexponential model. Molecular profiles were evaluated from tissue specimens obtained during the resection. The lesion regions-of-interest were segmented from high intensity FLAIR using automatic segmentation with manual refinement. Statistical descriptors from the voxel intensity values inside each lesion and radiomic features (Pyrad MRC package) were calculated. From extracted radiomics, mRMRe R package version 2.1.0 was used to select 3 features in each modality for statistical comparisons. Of the 22 patients, 10 were found to have IDH-mutant gliomas and of those 5 patients had 1p/19q codeletion group comparisons. Following correction for effects of age and gender, at least one statistical descriptor was able to differentiate between IDH and 1p/19q codeletion status for all the parametric maps. In the radiomic analysis, corner-edge detector features with Harris-Stephens filtered signal showed significant group differences in IDH and 1p/19q codeletion groups. Spin lock imaging at 3T of human glioma was feasible and various qualitative parameters derived from the parametric maps were found to have potential to differentiate IDH and 1p19q codeletion status. Future larger prospective clinical trials are warranted to evaluate these methods further.

Tumor suppressor role of the complement inhibitor CSMD1 and its role in TNF-induced neuroinflammation in gliomas.

BACKGROUND: The complement inhibitor CSMD1 acts as a tumor suppressor in various types of solid cancers. Despite its high level of expression in the brain, its function in gliomas, malignant brain tumors originating from glial cells, has not been investigated. METHODS: Three cohorts of glioma patients comprising 1500 patients were analyzed in our study along with their clinical data. H4, U-118 and U-87 cell lines were used to investigate the tumor suppressor function of CSMD1 in gliomas. PDGFB-induced brain tumor model was utilized for the validation of in vitro data. RESULTS: The downregulation of CSMD1 expression correlated with reduced overall and disease-free survival, elevated tumor grade, wild-type IDH genotype, and intact 1p/19q status. Moreover, enhanced activity was noted in the neuroinflammation pathway. Importantly, ectopic expression of CSMD1 in glioma cell lines led to decreased aggressiveness in vitro. Mechanically, CSMD1 obstructed the TNF-induced NF-kB and STAT3 signaling pathways, effectively suppressing the secretion of IL-6 and IL-8. There was also reduced survival in PDGFB-induced brain tumors in mice when Csmd1 was downregulated. CONCLUSIONS: Our study has identified CSMD1 as a tumor suppressor in gliomas and elucidated its role in TNF-induced neuroinflammation, contributing to a deeper understanding of glioma pathogenesis.

Metabologenomic characterization uncovers a clinically aggressive IDH mutant glioma subtype.

Mutations in the pivotal metabolic isocitrate dehydrogenase (IDH) enzymes are recognized to drive the molecular footprint of diffuse gliomas, and patients with IDH mutant gliomas have overall favorable outcomes compared to patients with IDH wild-type tumors. However, survival still varies widely among patients with IDH mutated tumors. Here, we aimed to characterize molecular signatures that explain the range of IDH mutant gliomas. By integrating matched epigenome-wide methylome, transcriptome, and global metabolome data in 154 patients with gliomas, we identified a group of IDH mutant gliomas with globally altered metabolism that resembled IDH wild-type tumors. IDH-mutant gliomas with altered metabolism have significantly shorter overall survival from their IDH mutant counterparts that is not fully accounted for by recognized molecular prognostic markers of CDKN2A/B loss and glioma CpG Island Methylator Phenotype (GCIMP) status. IDH-mutant tumors with dysregulated metabolism harbored distinct epigenetic alterations that converged to drive proliferative and stem-like transcriptional profiles, providing a window to target novel dependencies in gliomas.

Whole brain morphologic features improve the predictive accuracy of IDH status and VEGF expression levels in gliomas.

Glioma is a systemic disease that can induce micro and macro alternations of whole brain. Isocitrate dehydrogenase and vascular endothelial growth factor are proven prognostic markers and antiangiogenic therapy targets in glioma. The aim of this study was to determine the ability of whole brain morphologic features and radiomics to predict isocitrate dehydrogenase status and vascular endothelial growth factor expression levels. This study recruited 80 glioma patients with isocitrate dehydrogenase wildtype and high vascular endothelial growth factor expression levels, and 102 patients with isocitrate dehydrogenase mutation and low vascular endothelial growth factor expression levels. Virtual brain grafting, combined with Freesurfer, was used to compute morphologic features including cortical thickness, LGI, and subcortical volume in glioma patient. Radiomics features were extracted from multiregional tumor. Pycaret was used to construct the machine learning pipeline. Among the radiomics models, the whole tumor model achieved the best performance (accuracy 0.80, Area Under the Curve 0.86), while, after incorporating whole brain morphologic features, the model had a superior predictive performance (accuracy 0.82, Area Under the Curve 0.88). The features contributed most in predicting model including the right caudate volume, left middle temporal cortical thickness, first-order statistics, shape, and gray-level cooccurrence matrix. Pycaret, based on morphologic features, combined with radiomics, yielded highest accuracy in predicting isocitrate dehydrogenase mutation and vascular endothelial growth factor levels, indicating that morphologic abnormalities induced by glioma were associated with tumor biology.

Scutellarin activates IDH1 to exert antitumor effects in hepatocellular carcinoma progression.

Isochlorate dehydrogenase 1 (IDH1) is an important metabolic enzyme for the production of α-ketoglutarate (α-KG), which has antitumor effects and is considered to have potential antitumor effects. The activation of IDH1 as a pathway for the development of anticancer drugs has not been attempted. We demonstrated that IDH1 can limit glycolysis in hepatocellular carcinoma (HCC) cells to activate the tumor immune microenvironment. In addition, through proteomic microarray analysis, we identified a natural small molecule, scutellarin (Scu), which activates IDH1 and inhibits the growth of HCC cells. By selectively modifying Cys297, Scu promotes IDH1 active dimer formation and increases α-KG production, leading to ubiquitination and degradation of HIF1a. The loss of HIF1a further leads to the inhibition of glycolysis in HCC cells. The activation of IDH1 by Scu can significantly increase the level of α-KG in tumor tissue, downregulate the HIF1a signaling pathway, and activate the tumor immune microenvironment in vivo. This study demonstrated the inhibitory effect of IDH1-α-KG-HIF1a on the growth of HCC cells and evaluated the inhibitory effect of Scu, the first IDH1 small molecule agonist, which provides a reference for cancer immunotherapy involving activated IDH1.

Molecular characterization and survival analysis of a cohort of glioblastoma, IDH-wildtype.

Glioblastoma, IDH-wild type, the most common malignant primary central nervous system tumor, represents a formidable challenge in clinical management due to its poor prognosis and limited therapeutic responses. With an evolving understanding of its underlying biology, there is an urgent need to identify prognostic molecular groups that can be subject to targeted therapy. This study established a cohort of 124 sequential glioblastomas from a tertiary hospital and aimed to find correlations between molecular features and survival outcomes. Comprehensive molecular characterization of the cohort revealed prevalent alterations as previously described, such as TERT promoter mutations and involvement of the PI3K-Akt-mTOR, CK4/6-CDKN2A/B-RB1, and p14ARF-MDM2-MDM4-p53 pathways. MGMT promoter methylation is a significant predictor of improved overall survival, aligned with previous data. Conversely, age showed a marginal association with higher mortality. Multivariate analysis to account for the effect of MGMT promoter methylation and age showed that, in contrast to other published series, this cohort demonstrated improved survival for tumors harboring PTEN mutations, and that there was no observed difference for most other molecular alterations, including EGFR amplification, RB1 loss, or the coexistence of EGFR amplification and deletion/exon skipping (EGFRvIII). Despite limitations in sample size, this study contributes data to the molecular landscape of glioblastomas, prompting further investigations to examine these findings more closely in larger cohorts.

A multi-omics analysis-based model to predict the prognosis of low-grade gliomas.

Lower-grade gliomas (LGGs) exhibit highly variable clinical behaviors, while classic histology characteristics cannot accurately reflect the authentic biological behaviors, clinical outcomes, and prognosis of LGGs. In this study, we carried out analyses of whole exome sequencing, RNA sequencing and DNA methylation in primary vs. recurrent LGG samples, and also combined the multi-omics data to construct a prognostic prediction model. TCGA-LGG dataset was searched for LGG samples. 523 samples were used for whole exome sequencing analysis, 532 for transcriptional analysis, and 529 for DNA methylation analysis. LASSO regression was used to screen genes with significant association with LGG survival from the frequently mutated genes, differentially expressed genes, and differentially methylated genes, whereby a prediction model for prognosis of LGG was further constructed and validated. The most frequently mutated diver genes in LGGs were IDH1 (77%), TP53 (48%), ATRX (37%), etc. Top significantly up-regulated genes were C6orf15, DAO, MEOX2, etc., and top significantly down-regulated genes were DMBX1, GPR50, HMX2, etc. 2077 genes were more and 299 were less methylated in recurrent vs. primary LGG samples. Thirty-nine genes from the above analysis were included to establish a prediction model of survival, which showed that the high-score group had a very significantly shorter survival than the low-score group in both training and testing sets. ROC analysis showed that AUC was 0.817 for the training set and 0.819 for the testing set. This study will be beneficial to accurately predict the survival of LGGs to identify patients with poor prognosis to take specific treatment as early, which will help improve the treatment outcomes and prognosis of LGG.