Oncogenic IDH mutations increase heterochromatin-related replication stress without impacting homologous recombination.

Oncogenic mutations in isocitrate dehydrogenases 1 and 2 (IDH1/2) produce 2-hydroxyglutarate (2HG), which inhibits dioxygenases that modulate chromatin dynamics. The effects of 2HG have been reported to sensitize IDH tumors to poly-(ADP-ribose) polymerase (PARP) inhibitors. However, unlike PARP-inhibitor-sensitive BRCA1/2 tumors, which exhibit impaired homologous recombination, IDH-mutant tumors have a silent mutational profile and lack signatures associated with impaired homologous recombination. Instead, 2HG-producing IDH mutations lead to a heterochromatin-dependent slowing of DNA replication accompanied by increased replication stress and DNA double-strand breaks. This replicative stress manifests as replication fork slowing, but the breaks are repaired without a significant increase in mutation burden. Faithful resolution of replicative stress in IDH-mutant cells is dependent on poly-(ADP-ribosylation). Treatment with PARP inhibitors increases DNA replication but results in incomplete DNA repair. These findings demonstrate a role for PARP in the replication of heterochromatin and further validate PARP as a therapeutic target in IDH-mutant tumors.

IDH2 stabilizes HIF-1α-induced metabolic reprogramming and promotes chemoresistance in urothelial cancer.

Drug resistance contributes to poor therapeutic response in urothelial carcinoma (UC). Metabolomic analysis suggested metabolic reprogramming in gemcitabine-resistant urothelial carcinoma cells, whereby increased aerobic glycolysis and metabolic stimulation of the pentose phosphate pathway (PPP) promoted pyrimidine biosynthesis to increase the production of the gemcitabine competitor deoxycytidine triphosphate (dCTP) that diminishes its therapeutic effect. Furthermore, we observed that gain-of-function of isocitrate dehydrogenase 2 (IDH2) induced reductive glutamine metabolism to stabilize Hif-1α expression and consequently stimulate aerobic glycolysis and PPP bypass in gemcitabine-resistant UC cells. Interestingly, IDH2-mediated metabolic reprogramming also caused cross resistance to CDDP, by elevating the antioxidant defense via increased NADPH and glutathione production. Downregulation or pharmacological suppression of IDH2 restored chemosensitivity. Since the expression of key metabolic enzymes, such as TIGAR, TKT, and CTPS1, were affected by IDH2-mediated metabolic reprogramming and related to poor prognosis in patients, IDH2 might become a new therapeutic target for restoring chemosensitivity in chemo-resistant urothelial carcinoma.

NADP(H)-dependent biocatalysis without adding NADP(H).

Isocitrate dehydrogenase 1 (IDH1) naturally copurifies and crystallizes in a resting state with a molecule of its exchangeable cofactor, NADP+/NADPH, bound in each monomer of the homodimer. We report electrochemical studies with IDH1 that exploit this property to reveal the massive advantage of nanoconfinement to increase the efficiency of multistep enzyme-catalyzed cascade reactions. When coloaded with ferredoxin NADP+ reductase in a nanoporous conducting indium tin oxide film, IDH1 carries out the complete electrochemical oxidation of 6 mM isocitrate (in 4mL) to 2-oxoglutarate (2OG), using only the NADP(H) that copurified with IDH1 and was carried into the electrode pores as cargo-the system remains active for days. The entrapped cofactor, now quantifiable by cyclic voltammetry, undergoes ~160,000 turnovers during the process. The results from a variety of electrocatalysis experiments imply that the local concentrations of the two nanoconfined enzymes lie around the millimolar range. The combination of crowding and entrapment results in a 102 to 103-fold increase in the efficiency of NADP(H) redox cycling. The ability of the method to drive cascade catalysis in either direction (oxidation or reduction) and remove and replace substrates was exploited to study redox-state dependent differences in cofactor binding between wild-type IDH1 and the cancer-linked R132H variant that catalyzes the "gain of function" reduction of 2OG to 2-hydroxyglutarate instead of isocitrate oxidation. The combined results demonstrate the power of nanoconfinement for facilitating multistep enzyme catalysis (in this case energized and verified electrochemically) and reveal insights into the dynamic role of nicotinamide cofactors as redox (hydride) carriers.

Isocitrate lyase promotes Puccinia striiformis f. sp. tritici susceptibility in wheat (Triticum aestivum) by suppressing accumulation of glyoxylate cycle intermediates.

Plant fungal parasites manipulate host metabolism to support their own survival. Among the many central metabolic pathways altered during infection, the glyoxylate cycle is frequently upregulated in both fungi and their host plants. Here, we examined the response of the glyoxylate cycle in bread wheat (Triticum aestivum) to infection by the obligate biotrophic fungal pathogen Puccinia striiformis f. sp. tritici (Pst). Gene expression analysis revealed that wheat genes encoding the two unique enzymes of the glyoxylate cycle, isocitrate lyase (TaICL) and malate synthase, diverged in their expression between susceptible and resistant Pst interactions. Focusing on TaICL, we determined that the TaICL B homoeolog is specifically upregulated during early stages of a successful Pst infection. Furthermore, disruption of the B homoeolog alone was sufficient to significantly perturb Pst disease progression. Indeed, Pst infection of the TaICL-B disruption mutant (TaICL-BY400*) was inhibited early during initial penetration, with the TaICL-BY400* line also accumulating high levels of malic acid, citric acid, and aconitic acid. Exogenous application of malic acid or aconitic acid also suppressed Pst infection, with trans-aconitic acid treatment having the most pronounced effect by decreasing fungal biomass 15-fold. Thus, enhanced TaICL-B expression during Pst infection may lower accumulation of malic acid and aconitic acid to promote Pst proliferation. As exogenous application of aconitic acid and malic acid has previously been shown to inhibit other critical pests and pathogens, we propose TaICL as a potential target for disruption in resistance breeding that could have wide-reaching protective benefits for wheat and beyond.

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.

Natural and synthetic 2-oxoglutarate derivatives are substrates for oncogenic variants of human isocitrate dehydrogenase 1 and 2.

Variants of isocitrate dehydrogenase (IDH) 1 and 2 (IDH1/2) alter metabolism in cancer cells by catalyzing the NADPH-dependent reduction of 2-oxoglutarate (2OG) to (2R)-hydroxyglutarate. However, it is unclear how derivatives of 2OG can affect cancer cell metabolism. Here, we used synthetic C3- and C4-alkylated 2OG derivatives to investigate the substrate selectivities of the most common cancer-associated IDH1 variant (R132H IDH1), of two cancer-associated IDH2 variants (R172K IDH2, R140Q IDH2), and of WT IDH1/2. Absorbance-based, NMR, and electrochemical assays were employed to monitor WT IDH1/2 and IDH1/2 variant-catalyzed 2OG derivative turnover in the presence and absence of 2OG. Our results reveal that 2OG derivatives can serve as substrates of the investigated IDH1/2 variants, but not of WT IDH1/2, and have the potential to act as 2OG-competitive inhibitors. Kinetic parameters reveal that some 2OG derivatives, including the natural product 3-methyl-2OG, are equally or even more efficient IDH1/2 variant substrates than 2OG. Furthermore, NMR and mass spectrometry studies confirmed IDH1/2 variant-catalyzed production of alcohols in the cases of the 3-methyl-, 3-butyl-, and 3-benzyl-substituted 2OG derivatives; a crystal structure of 3-butyl-2OG with an IDH1 variant (R132C/S280F IDH1) reveals active site binding. The combined results highlight the potential for (i) IDH1/2 variant-catalyzed reduction of 2-oxoacids other than 2OG in cells, (ii) modulation of IDH1/2 variant activity by 2-oxoacid natural products, including some present in common foods, (iii) inhibition of IDH1/2 variants via active site binding rather than the established allosteric mode of inhibition, and (iv) possible use of IDH1/2 variants as biocatalysts.

Region-specific DNA hydroxymethylation along the malignant progression of IDH-mutant gliomas.

The majority of low-grade isocitrate dehydrogenase-mutant (IDHmt) gliomas undergo malignant progression (MP), but their underlying mechanism remains unclear. IDHmt gliomas exhibit global DNA methylation, and our previous report suggested that MP could be partly attributed to passive demethylation caused by accelerated cell cycles. However, during MP, there is also active demethylation mediated by ten-eleven translocation, such as DNA hydroxymethylation. Hydroxymethylation is reported to potentially contribute to gene expression regulation, but its role in MP remains under investigation. Therefore, we conducted a comprehensive analysis of hydroxymethylation during MP of IDHmt astrocytoma. Five primary/malignantly progressed IDHmt astrocytoma pairs were analyzed with oxidative bisulfite and the Infinium EPIC methylation array, detecting 5-hydroxymethyl cytosine at over 850,000 locations for region-specific hydroxymethylation assessment. Notably, we observed significant sharing of hydroxymethylated genomic regions during MP across the samples. Hydroxymethylated CpGs were enriched in open sea and intergenic regions (p < 0.001), and genes undergoing hydroxymethylation were significantly associated with cancer-related signaling pathways. RNA sequencing data integration identified 91 genes with significant positive/negative hydroxymethylation-expression correlations. Functional analysis suggested that positively correlated genes are involved in cell-cycle promotion, while negatively correlated ones are associated with antineoplastic functions. Analyses of The Cancer Genome Atlas clinical data on glioma were in line with these findings. Motif-enrichment analysis suggested the potential involvement of the transcription factor KLF4 in hydroxymethylation-based gene regulation. Our findings shed light on the significance of region-specific DNA hydroxymethylation in glioma MP and suggest its potential role in cancer-related gene expression and IDHmt glioma malignancy.

Differential isocitrate dehydrogenase 1 and isocitrate dehydrogenase 2 mutation-related landscape in intrahepatic cholangiocarcinoma.

BACKGROUND: Patients with intrahepatic cholangiocarcinoma (ICC) are prone to recurrence and poor survival. Targeted therapy related to isocitrate dehydrogenase (IDH) is an extremely important treatment. IDH1 and IDH2 mutations are generally thought to have similar effects on the tumor landscape. However, it is doubtful whether these 2 mutations have exactly the same effects on tumor cells and the tumor microenvironment. METHODS: All collected tumor samples were subjected to simultaneous whole-exon sequencing and proteome sequencing. RESULTS: IDH1 mutations accounted for 12.2%, and IDH2 mutations accounted for 5.5%, all missense mutations. Tumors with IDH mutations had lower proportions of KRAS and TP53 mutations. Mutated genes were obviously enriched in the kinase pathway in the tumors with IDH2 mutations. The signaling pathways were mainly enriched in the activation of cellular metabolic activities and an increase of inhibitory immune cells in the tumors with IDH mutations. Moreover, tumors had unique enrichment in DNA repair in IDH1 mutants and secretion of biological molecules in IDH2 mutants. Inhibitory immune cells might be more prominent in IDH2 mutants, and the expression of immune checkpoints PVR and HLA-DQB1 was more prominent in IDH1 mutants. IDH mutants were more related to metabolism-related and inflammation-immune response clusters, and some belonged to the DNA replication and repair cluster. CONCLUSIONS: These results revealed the differential IDH1 and IDH2 mutation-related landscapes, and we have provided an important reference database to guide ICC treatment.

13C-labeling reveals non-conventional pathways providing carbon for hydroxy fatty acid synthesis in Physaria fendleri.

Physaria fendleri is a member of the Brassicaceae that produces in its embryos hydroxy fatty acids, constituents of oils that are very valuable and widely used by industry for cosmetics, lubricants, biofuels, etc. Free of toxins and rich in hydroxy fatty acids, Physaria provides a promising alternative to imported castor oil and is on the verge of being commercialized. This study aims to identify important biochemical step(s) for oil synthesis in Physaria, which may serve as target(s) for future crop improvement. To advance towards this goal, the endosperm composition was analysed by LC-MS/MS to develop and validate culture conditions that mimic the development of the embryos in planta. Using developing Physaria embryos in culture and 13C-labeling, our studies revealed that: (i) Physaria embryos metabolize carbon into biomass with an efficiency significantly lower than other photosynthetic embryos; (ii) the plastidic malic enzyme provides 42% of the pyruvate used for de novo fatty acid synthesis, which is the highest measured so far in developing 'green' oilseed embryos; and (iii) Physaria uses non-conventional pathways to channel carbon into oil, namely the Rubisco shunt, which fixes CO2 released in the plastid, and the reversibility of isocitrate dehydrogenase, which provides additional carbon for fatty acid elongation.

Development and validation of clinical-radiomics analysis for preoperative prediction of IDH mutation status and WHO grade in diffuse gliomas: a consecutive L-[methyl-11C] methionine cohort study with two PET scanners.

PURPOSE: Determination of isocitrate dehydrogenase (IDH) genotype is crucial in the stratification of diagnosis and prognostication in diffuse gliomas. We sought to build and validate radiomics models and clinical features incorporated nomogram for preoperative prediction of IDH mutation status and WHO grade of diffuse gliomas with L-[methyl-11C] methionine ([11C]MET) PET/CT imaging according to the 2016 WHO classification of tumors of the central nervous system. METHODS: Consecutive 178 preoperative [11C]MET PET/CT images were retrospectively studied for radiomics analysis. One hundred six patients from PET scanner 1 were used as training dataset, and 72 patients from PET scanner 2 were used for validation dataset. [11C]MET PET and integrated CT radiomics features were extracted, respectively; three independent predictive models were built based on PET features, CT features, and combined PET/CT features, respectively. The SelectKBest method, Spearman correlation analysis, Least Absolute Shrinkage and Selection Operator (LASSO) regression, and machine learning algorithms were applied for feature selection and model building. After filtering the satisfactory predictive model, key clinical features were incorporated for the nomogram establishment. RESULTS: The combined [11C]MET PET/CT radiomics model, which consisted of four PET features and eight integrated CT features, was significantly associated with IDH genotype (p < 0.0001 for both training and validation datasets). Nomogram based on the [11C]MET PET/CT radiomics score, patients' age, and dichotomous tumor location status showed satisfactory discrimination capacity, and the AUC was 0.880 (95% CI, 0.726-0.998) in the training dataset and 0.866 (95% CI, 0.777-0.956) in the validation dataset. In IDH stratified WHO grade prediction, the final radiomics model consists of four PET features and two CT features had reasonable and stable differential efficacy of WHO grade II and III patients from grade IV patients in IDH-wildtype patients, and the AUC was 0.820 (95% CI, 0.541-1.000) in the training dataset and 0.766 (95% CI, 0.612-0.921) in the validation dataset. CONCLUSION: [11C]MET PET radiomics features could benefit non-invasive IDH genotype prediction, and integrated CT radiomics features could enhance the efficacy. Radiomics and clinical features incorporation could establish satisfactory nomogram for clinical application. This non-invasive predictive investigation based on our consecutive cohort from two PET scanners could provide the perspective to observe the differential efficacy and the stability of radiomics-based investigation in untreated diffuse gliomas.

Recursive partitioning analysis for survival stratification and early imaging prediction of molecular biomarker in glioma patients.

BACKGROUND: Glioma is the most common primary brain tumor with high mortality and disability rates. Recent studies have highlighted the significant prognostic consequences of subtyping molecular pathological markers using tumor samples, such as IDH, 1p/19q, and TERT. However, the relative importance of individual markers or marker combinations in affecting patient survival remains unclear. Moreover, the high cost and reliance on postoperative tumor samples hinder the widespread use of these molecular markers in clinical practice, particularly during the preoperative period. We aim to identify the most prominent molecular biomarker combination that affects patient survival and develop a preoperative MRI-based predictive model and clinical scoring system for this combination. METHODS: A cohort dataset of 2,879 patients was compiled for survival risk stratification. In a subset of 238 patients, recursive partitioning analysis (RPA) was applied to create a survival subgroup framework based on molecular markers. We then collected MRI data and applied Visually Accessible Rembrandt Images (VASARI) features to construct predictive models and clinical scoring systems. RESULTS: The RPA delineated four survival groups primarily defined by the status of IDH and TERT mutations. Predictive models incorporating VASARI features and clinical data achieved AUC values of 0.85 for IDH and 0.82 for TERT mutations. Nomogram-based scoring systems were also formulated to facilitate clinical application. CONCLUSIONS: The combination of IDH-TERT mutation status alone can identify the most distinct survival differences in glioma patients. The predictive model based on preoperative MRI features, supported by clinical assessments, offers a reliable method for early molecular mutation prediction and constitutes a valuable scoring tool for clinicians in guiding treatment strategies.

Evaluation of Key Molecular Markers in Adult Diffuse Gliomas Based on a Novel Combination of Diffusion and Perfusion MRI and MR Spectroscopy.

BACKGROUND: Preoperative identification of isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status could help clinicians select the optimal therapy in patients with diffuse glioma. Although, the value of multimodal intersection was underutilized. PURPOSE: To evaluate the value of quantitative MRI biomarkers for the identification of IDH mutation and 1p/19q codeletion in adult patients with diffuse glioma. STUDY TYPE: Retrospective. POPULATION: Two hundred sixteen adult diffuse gliomas with known genetic test results, divided into training (N = 130), test (N = 43), and validation (N = 43) groups. SEQUENCE/FIELD STRENGTH: Diffusion/perfusion-weighted-imaging sequences and multivoxel MR spectroscopy (MRS), all 3.0 T using three different scanners. ASSESSMENT: The apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) of the core tumor were calculated to identify IDH-mutant and 1p/19q-codeleted statuses and to determine cut-off values. ADC models were built based on the 30th percentile and lower, CBV models were built based on the 75th centile and higher (both in five centile steps). The optimal tumor region was defined and the metabolite concentrations of MRS voxels that overlapped with the ADC/CBV optimal region were calculated and added to the best-performing diagnostic models. STATISTICAL TESTS: DeLong's test, diagnostic test, and decision curve analysis were performed. A P value <0.05 was considered to be statistically significant. RESULTS: Almost all ADC models achieved good performance in identifying IDH mutation status, among which ADC_15th was the most valuable parameter (threshold = 1.186; Youden index = 0.734; AUC_train = 0.896). The differential power of CBV histogram metrics for predicting 1p/19q codeletion outperformed ADC histogram metrics, and the CBV_80th-related model performed best (threshold = 1.435; Youden index = 0.458; AUC_train = 0.724). The AUCs of ADC_15th and CBV_80th models in the validation set were 0.857 and 0.733. These models tended to improve after incorporation of N-acetylaspartate/total_creatine and glutamate-plus-glutamine/total_creatine, respectively. DATA CONCLUSION: The intersection of ADC-, CBV-based histogram and MRS provide a reliable paradigm for identifying the key molecular markers in adult diffuse gliomas. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 3.

CEBPB upregulates P4HA2 to promote the malignant biological behavior in IDH1 wildtype glioma.

Temozolomide (TMZ), the primary drug for glioma treatment, has limited treatment efficacy. Additionally, considerable evidence shows that isocitrate dehydrogenase 1 mutation-type (IDH1 mut) gliomas have a better response to TMZ than isocitrate dehydrogenase 1 wildtype (IDH1 wt) gliomas. Here, we aimed to identify potential mechanisms underlying this phenotype. Herein, the Cancer Genome Atlas bioinformatic data and 30 clinical samples from patients were analyzed to reveal the expression level of cytosine-cytosine-adenosine-adenosine-thymidine (CCAAT) Enhancer Binding Protein Beta (CEBPB) and prolyl 4-hydroxylase subunit alpha 2 (P4HA2) in gliomas. Next, cellular and animal experiments, including cell proliferation, colony formation, transwell, CCK-8, and xenograft assays, were performed to explore the tumor-promoting effects of P4HA2 and CEBPB. Then, chromatin immunoprecipitation (ChIP) assays were used to confirm the regulatory relationships between them. Finally, a co-immunoprecipitation (Co-IP) assay was performed to confirm the effect of IDH1-132H to CEBPB proteins. We found that CEBPB and P4HA2 expression was significantly upregulated in IDH1 wt gliomas and associated with poor prognosis. CEBPB knockdown inhibited the proliferation, migration, invasion, and temozolomide resistance of glioma cells and hindered the growth of glioma xenograft tumors. CEBPE, as a transcription factor, exerted its function by transcriptionally upregulating P4HA2 expression in glioma cells. Importantly, CEBPB is prone to ubiquitin-proteasomal degradation in IDH1 R132H glioma cells. We also demonstrated that both genes are related to collagen synthesis, as confirmed by in vivo experiments. Thus, CEBPE promotes proliferation and TMZ resistance by inducing P4HA2 expression in glioma cells and offers a potential therapeutic target for glioma treatment.

Endothelial cell-derived extracellular vesicles modulate the therapeutic efficacy of mesenchymal stem cells through IDH2/TET pathway in ARDS.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a severe and fatal disease. Although mesenchymal stem cell (MSC)-based therapy has shown remarkable efficacy in treating ARDS in animal experiments, clinical outcomes have been unsatisfactory, which may be attributed to the influence of the lung microenvironment during MSC administration. Extracellular vesicles (EVs) derived from endothelial cells (EC-EVs) are important components of the lung microenvironment and play a crucial role in ARDS. However, the effect of EC-EVs on MSC therapy is still unclear. In this study, we established lipopolysaccharide (LPS) - induced acute lung injury model to evaluate the impact of EC-EVs on the reparative effects of bone marrow-derived MSC (BM-MSC) transplantation on lung injury and to unravel the underlying mechanisms. METHODS: EVs were isolated from bronchoalveolar lavage fluid of mice with LPS - induced acute lung injury and patients with ARDS using ultracentrifugation. and the changes of EC-EVs were analysed using nanoflow cytometry analysis. In vitro assays were performed to establish the impact of EC-EVs on MSC functions, including cell viability and migration, while in vivo studies were performed to validate the therapeutic effect of EC-EVs on MSCs. RNA-Seq analysis, small interfering RNA (siRNA), and a recombinant lentivirus were used to investigate the underlying mechanisms. RESULTS: Compared with that in non-ARDS patients, the quantity of EC-EVs in the lung microenvironment was significantly greater in patients with ARDS. EVs derived from lipopolysaccharide-stimulated endothelial cells (LPS-EVs) significantly decreased the viability and migration of BM-MSCs. Furthermore, engrafting BM-MSCs pretreated with LPS-EVs promoted the release of inflammatory cytokines and increased pulmonary microvascular permeability, aggravating lung injury. Mechanistically, LPS-EVs reduced the expression level of isocitrate dehydrogenase 2 (IDH2), which catalyses the formation of α-ketoglutarate (α-KG), an intermediate product of the tricarboxylic acid (TCA) cycle, in BM-MSCs. α-KG is a cofactor for ten-eleven translocation (TET) enzymes, which catalyse DNA hydroxymethylation in BM-MSCs. CONCLUSIONS: This study revealed that EC-EVs in the lung microenvironment during ARDS can affect the therapeutic efficacy of BM-MSCs through the IDH2/TET pathway, providing potential strategies for improving the therapeutic efficacy of MSC-based therapy in the clinic.

IDH2/R140Q mutation confers cytokine-independent proliferation of TF-1 cells by activating constitutive STAT3/5 phosphorylation.

BACKGROUND: R140Q mutation in isocitrate dehydrogenase 2 (IDH2) promotes leukemogenesis. Targeting IDH2/R140Q yields encouraging therapeutic effects in the clinical setting. However, therapeutic resistance occurs in 12% of IDH2/R140Q inhibitor treated patients. The IDH2/R140Q mutant converted TF-1 cells to proliferate in a cytokine-independent manner. This study investigated the signaling pathways involved in TF-1(R140Q) cell proliferation conversion as alternative therapeutic strategies to improve outcomes in patients with acute myeloid leukemia (AML) harboring IDH2/R140Q. METHODS: The effects of IDH2/R140Q mutation on TF-1 cell survival induced by GM-CSF withdrawal were evaluated using flow cytometry assay. The expression levels of apoptosis-related proteins, total or phosphorylated STAT3/5, ERK, and AKT in wild-type TF-1(WT) or TF-1(R140Q) cells under different conditions were evaluated using western blot analysis. Cell viability was tested using MTT assay. The mRNA expression levels of GM-CSF, IL-3, IL-6, G-CSF, leukemia inhibitory factor (LIF), oncostatin M (OSM), and IL-11 in TF-1(WT) and TF-1(R140Q) cells were quantified via RT-PCR. The secretion levels of GM-CSF, OSM, and LIF were determined using ELISA. RESULTS: Our results showed that STAT3 and STAT5 exhibited aberrant constitutive phosphorylation in TF-1(R140Q) cells compared with TF-1(WT) cells. Inhibition of STAT3/5 phosphorylation suppressed the cytokine-independent proliferation of TF-1(R140Q) cells. Moreover, the autocrine GM-CSF, LIF and OSM levels increased, which is consistent with constitutive STAT5/3 activation in TF-1(R140Q) cells, as compared with TF-1(WT) cells. CONCLUSIONS: The autocrine cytokines, including GM-CSF, LIF, and OSM, contribute to constitutive STAT3/5 activation in TF-1(R140Q) cells, thereby modulating IDH2/R140Q-mediated malignant proliferation in TF-1 cells. Targeting STAT3/5 phosphorylation may be a novel strategy for the treatment of AML in patients harboring the IDH2/R140Q mutation. Video Abstract.

The effects of BMP2 and the mechanisms involved in the invasion and angiogenesis of IDH1 mutant glioma cells.

PURPOSE: This study investigated the effect of an isocitrate dehydrogenase 1 (IDH1) mutation (mutIDH1) on the invasion and angiogenesis of human glioma cells. METHODS: Doxycycline was used to induce the expression of mutIDH1 in glioma cells. Transwell and wound healing assays were conducted to assess glioma cell migration and invasion. Western blotting and cell immunofluorescence were used to measure the expression levels of various proteins. The influence of bone morphogenetic protein 2 (BMP2) on invasion, angiogenesis-related factors, BMP2-related receptor expression, and changes in Smad signaling pathway-related proteins were evaluated after treatment with BMP2. Differential gene expression and reference transcription analysis were performed. RESULTS: Successful infection with recombinant lentivirus expressing mutIDH1 was demonstrated. The IDH1 mutation promoted glioma cell migration and invasion while positively regulating the expression of vascularization-related factors and BMP2-related receptors. BMP2 exhibited a positive regulatory effect on the migration, invasion, and angiogenesis of mutIDH1-glioma cells, possibly mediated by BMP2-induced alterations in Smad signaling pathway-related factors.After BMP2 treatment, the differential genes of MutIDH1-glioma cells are closely related to the regulation of cell migration and cell adhesion, especially the regulation of Smad-related proteins. KEGG analysis confirmed that it was related to BMP signaling pathway and TGF-ß signaling pathway and cell adhesion. Enrichment analysis of gene ontology and genome encyclopedia further confirmed the correlation of these pathways. CONCLUSION: Mutation of isocitrate dehydrogenase 1 promotes the migration, invasion, and angiogenesis of glioma cells, through its effects on the BMP2-driven Smad signaling pathway. In addition, BMP2 altered the transcriptional patterns of mutIDH1 glioma cells, enriching different gene loci in pathways associated with invasion, migration, and angiogenesis.

The diagnostic efficiency of integration of 2HG MRS and IVIM versus individual parameters for predicting IDH mutation status in gliomas in clinical scenarios: A retrospective study.

PURPOSE: Currently, there remains a scarcity of established preoperative tests to accurately predict the isocitrate dehydrogenase (IDH) mutation status in clinical scenarios, with limited research has explored the potential synergistic diagnostic performance among metabolite, perfusion, and diffusion parameters. To address this issue, we aimed to develop an imaging protocol that integrated 2-hydroxyglutarate (2HG) magnetic resonance spectroscopy (MRS) and intravoxel incoherent motion (IVIM) by comprehensively assessing metabolic, cellular, and angiogenic changes caused by IDH mutations, and explored the diagnostic efficiency of this imaging protocol for predicting IDH mutation status in clinical scenarios. METHODS: Patients who met the inclusion criteria were categorized into two groups: IDH-wild type (IDH-WT) group and IDH-mutant (IDH-MT) group. Subsequently, we quantified the 2HG concentration, the relative apparent diffusion coefficient (rADC), the relative true diffusion coefficient value (rD), the relative pseudo-diffusion coefficient (rD*) and the relative perfusion fraction value (rf). Intergroup differences were estimated using t-test and Mann-Whitney U test. Finally, we performed receiver operating characteristic (ROC) curve and DeLong's test to evaluate and compare the diagnostic performance of individual parameters and their combinations. RESULTS: 64 patients (female, 21; male, 43; age, 47.0 ± 13.7 years) were enrolled. Compared with IDH-WT gliomas, IDH-MT gliomas had higher 2HG concentration, rADC and rD (P < 0.001), and lower rD* (P = 0.013). The ROC curve demonstrated that 2HG + rD + rD* exhibited the highest areas under curve (AUC) value (0.967, 95%CI 0.889-0.996) for discriminating IDH mutation status. Compared with each individual parameter, the predictive efficiency of 2HG + rADC + rD* and 2HG + rD + rD* shows a statistically significant enhancement (DeLong's test: P < 0.05). CONCLUSIONS: The integration of 2HG MRS and IVIM significantly improves the diagnostic efficiency for predicting IDH mutation status in clinical scenarios.

Impact of signal intensity normalization of MRI on the generalizability of radiomic-based prediction of molecular glioma subtypes.

OBJECTIVES: Radiomic features have demonstrated encouraging results for non-invasive detection of molecular biomarkers, but the lack of guidelines for pre-processing MRI-data has led to poor generalizability. Here, we assessed the influence of different MRI-intensity normalization techniques on the performance of radiomics-based models for predicting molecular glioma subtypes. METHODS: Preoperative MRI-data from n = 615 patients with newly diagnosed glioma and known isocitrate dehydrogenase (IDH) and 1p/19q status were pre-processed using four different methods: no normalization (naive), N4 bias field correction (N4), N4 followed by either WhiteStripe (N4/WS), or z-score normalization (N4/z-score). A total of 377 Image-Biomarker-Standardisation-Initiative-compliant radiomic features were extracted from each normalized data, and 9 different machine-learning algorithms were trained for multiclass prediction of molecular glioma subtypes (IDH-mutant 1p/19q codeleted vs. IDH-mutant 1p/19q non-codeleted vs. IDH wild type). External testing was performed in public glioma datasets from UCSF (n = 410) and TCGA (n = 160). RESULTS: Support vector machine yielded the best performance with macro-average AUCs of 0.84 (naive), 0.84 (N4), 0.87 (N4/WS), and 0.87 (N4/z-score) in the internal test set. Both N4/WS and z-score outperformed the other approaches in the external UCSF and TCGA test sets with macro-average AUCs ranging from 0.85 to 0.87, replicating the performance of the internal test set, in contrast to macro-average AUCs ranging from 0.19 to 0.45 for naive and 0.26 to 0.52 for N4 alone. CONCLUSION: Intensity normalization of MRI data is essential for the generalizability of radiomic-based machine-learning models. Specifically, both N4/WS and N4/z-score approaches allow to preserve the high model performance, yielding generalizable performance when applying the developed radiomic-based machine-learning model in an external heterogeneous, multi-institutional setting. CLINICAL RELEVANCE STATEMENT: Intensity normalization such as N4/WS or N4/z-score can be used to develop reliable radiomics-based machine learning models from heterogeneous multicentre MRI datasets and provide non-invasive prediction of glioma subtypes. KEY POINTS: • MRI-intensity normalization increases the stability of radiomics-based models and leads to better generalizability. • Intensity normalization did not appear relevant when the developed model was applied to homogeneous data from the same institution. • Radiomic-based machine learning algorithms are a promising approach for simultaneous classification of IDH and 1p/19q status of glioma.

Medical image foundation models in assisting diagnosis of brain tumors: a pilot study.

OBJECTIVES: To build self-supervised foundation models for multicontrast MRI of the whole brain and evaluate their efficacy in assisting diagnosis of brain tumors. METHODS: In this retrospective study, foundation models were developed using 57,621 enhanced head MRI scans through self-supervised learning with a pretext task of cross-contrast context restoration with two different content dropout schemes. Downstream classifiers were constructed based on the pretrained foundation models and fine-tuned for brain tumor detection, discrimination, and molecular status prediction. Metrics including accuracy, sensitivity, specificity, and area under the ROC curve (AUC) were used to evaluate the performance. Convolutional neural networks trained exclusively on downstream task data were employed for comparative analysis. RESULTS: The pretrained foundation models demonstrated their ability to extract effective representations from multicontrast whole-brain volumes. The best classifiers, endowed with pretrained weights, showed remarkable performance with accuracies of 94.9, 92.3, and 80.4%, and corresponding AUC values of 0.981, 0.972, and 0.852 on independent test datasets in brain tumor detection, discrimination, and molecular status prediction, respectively. The classifiers with pretrained weights outperformed the convolutional classifiers trained from scratch by approximately 10% in terms of accuracy and AUC across all tasks. The saliency regions in the correctly predicted cases are mainly clustered around the tumors. Classifiers derived from the two dropout schemes differed significantly only in the detection of brain tumors. CONCLUSIONS: Foundation models obtained from self-supervised learning have demonstrated encouraging potential for scalability and interpretability in downstream brain tumor-related tasks and hold promise for extension to neurological diseases with diffusely distributed lesions. CLINICAL RELEVANCE STATEMENT: The application of our proposed method to the prediction of key molecular status in gliomas is expected to improve treatment planning and patient outcomes. Additionally, the foundation model we developed could serve as a cornerstone for advancing AI applications in the diagnosis of brain-related diseases.

Ultra-high b-value DWI accurately identifies isocitrate dehydrogenase genotypes and tumor subtypes of adult-type diffuse gliomas.

OBJECTIVES: To distinguish isocitrate dehydrogenase (IDH) genotypes and tumor subtypes of adult-type diffuse gliomas based on the fifth edition of the World Health Organization classification of central nervous system tumors (WHO CNS5) in 2021 using standard, high, and ultra-high b-value diffusion-weighted imaging (DWI). MATERIALS AND METHODS: This prospective study enrolled 70 patients with adult-type diffuse gliomas who underwent multiple b-value DWI. Apparent diffusion coefficient (ADC) values including ADCb500/b1000, ADCb500/b2000, ADCb500/b3000, ADCb500/b4000, ADCb500/b6000, ADCb500/b8000, and ADCb500/b10000 in tumor parenchyma (TP) and contralateral normal-appearing white matter (NAWM) were calculated. The ADC ratios of TP/NAWM were assessed for correlations with IDH genotypes, tumor subtypes, and Ki-67 status; diagnostic performances were compared. RESULTS: All ADCs were significantly higher in IDH mutant gliomas than in IDH wild-type gliomas (p < 0.01 for all); ADCb500/b8000 had the highest area under the curve (AUC) of 0.866. All ADCs were significantly lower in glioblastoma than in astrocytoma (p < 0.01 for all). ADCs other than ADCb500/b1000 were significantly lower in glioblastoma than in oligodendroglioma (p < 0.05 for all). ADCb500/b8000 and ADCb500/b10000 were significantly higher in oligodendroglioma than in astrocytoma (p = 0.034 and 0.023). The highest AUCs were 0.818 for ADCb500/b6000 when distinguishing glioblastoma from astrocytoma, 0.979 for ADCb500/b8000 and ADCb500/b10000 when distinguishing glioblastoma from oligodendroglioma, and 0.773 for ADCb500/b10000 when distinguishing astrocytoma from oligodendroglioma. Additionally, all ADCs were negatively correlated with Ki-67 status (p < 0.05 for all). CONCLUSION: Ultra-high b-value DWI can reliably separate IDH genotypes and tumor subtypes of adult-type diffuse gliomas using WHO CNS5 criteria. CLINICAL RELEVANCE STATEMENT: Ultra-high b-value diffusion-weighted imaging can accurately distinguish isocitrate dehydrogenase genotypes and tumor subtypes of adult-type diffuse gliomas, which may facilitate personalized treatment and prognostic assessment for patients with glioma. KEY POINTS: • Ultra-high b-value diffusion-weighted imaging can accurately distinguish subtle differences in water diffusion among biological tissues. • Ultra-high b-value diffusion-weighted imaging can reliably separate isocitrate dehydrogenase genotypes and tumor subtypes of adult-type diffuse gliomas. • Compared with standard b-value diffusion-weighted imaging, high and ultra-high b-value diffusion-weighted imaging demonstrate better diagnostic performances.