Isocitrate Dehydrogenase Mutation Research Articles

MODERN IMAGING TECHNIQUES IN THE ASSESSMENT
 OF MALIGNANCY IN GLIAL BRAIN TUMORS:
 LITERATURE REVIEW

Relevance: Gliomas represent a major group of primary central nervous system tumors, accounting for approximately 80% of all
 malignant brain neoplasms. Recent advances in molecular diagnostics, including the identification of mutations in the isocitrate dehydrogenase(IDH) gene, offer new opportunities to improve the classification of gliomas and to understand the mechanisms of their development. IDH
 mutations, which are found in a large proportion of gliomas, are associated with a better prognosis and represent an important biomarker
 for the development of targeted therapeutic strategies. Diagnostic techniques, particularly magnetic resonance imaging (MRI), also play
 an important role, providing additional ways to assess the morphological and biological characteristics of gliomas, contributing to a more
 accurate determination of tumor malignancy and molecular profile, which is key to treatment decisions.
 The purpose: To study the possibilities of magnetic resonance imaging in assessing the degree of malignancy of glial brain tumors.
 Method: A literature review was performed using the keywords: glioma, IDH mutation, IDH wild-type, MRI, magnetic resonance
 spectroscopy (MRS), apparent diffusion coefficient (ADC), diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), diffusion kurtosis
 image (DKI), Susceptibility Weighted Imaging (SWI) in PubMed, BMC Medicine, and Google Scholar databases. The review includes the results
 of an analysis of 45 literature reviews on the diagnostic capabilities of molecular diagnostics and MRI to assess the malignancy of gliomas.
 Results: This review highlights the importance of current approaches to the diagnosis of gliomas, demonstrating that different grades of
 malignancy and IDH mutation status are associated with unique features on MR imaging, including differences in localization, signal, and
 enhancement patterns. DTI and DWI extend the ability of MRI to assess tissue microstructure, allowing for more precise tumor characterization.
 Studies combining MRI morphologic features, ADC and DTI parameters offer a non-invasive approach to glioma prognosis, highlighting the
 importance of integrated use of imaging modalities to improve diagnosis and therapy.
 Conclusion: The use of magnetic resonance imaging allows for more accurate morphologic and metabolic characterization of gliomas
 in assessing the degree of malignancy, allowing physicians to make more accurate prognostic assessments and select the most appropriate
 treatment strategy.
 Keywords: Glioma, IDH mutation, wild-type IDH, MRI, magnetic resonance spectroscopy, ADC, DWI, DTI, DKI, SWI

Clinical impact of IDH1 mutations and MGMT methylation in adult glioblastoma

BackgroundImpact of Isocitrate dehydrogenase1 (IDH1) and O6-methylguanine-DNA methyltransferase (MGMT) in glioblastoma (GBM) have been of great interest due to their implications in prediction of prognosis of several types of cancer. It was aimed to investigate the clinical role of IDH1 mutation and MGMT methylation pattern among GBM patients versus non-neuro-oncological diseases (NND) patients and their impact on survival criteria.MethodsFormalin-fixed paraffin-embedded (FFPE) tissue sections of 58 GBM and 20 non-neuro-oncological diseases patients were recruited and IDH1 mutation and MGMT methylation was detected using Cast-PCR technology and Methyl II quantitative PCR approach, respectively. Results were assessed with other clinicopathological criteria and survival patterns.ResultsIDH1 mutation was detected among 15 GBM cases (15/58) and it was not reported among NND (P = 0.011). Receiver operating characteristic (ROC) curve was plotted to discriminate between MGMT methylation among studied groups. Patients with MGMT methylation ≥ 66% were reported as high methylation, which was recorded significantly in 51.7% and 100% of GBM cases and NND, respectively. Both showed significant difference with performance status, while MGMT methylation was significantly related with tumor size and tumor location. IDH1 mutation and MGMT methylation reported significant increase with GB patients revealed complete response to treatment. Survival pattern was better for IDH1 mutation and MGMT high methylation as compared to IDH1 wild type or MGMT low–moderate methylation, respectively, and favorable survival was detected when both were combined than using either of them alone.ConclusionDetection of IDH1 mutation and MGMT methylation among GB patients could aid in prediction of their response to treatment and their survival patterns, and their combination is better than using any of them alone.

A Promising Breakthrough: The Potential of VORASIDENIB in the Treatment of Low-grade Glioma.

Gliomas are common malignant brain tumors characterized by diffuse brain infiltration. World Health Organization grade II and grade III diffuse gliomas are considered lower-grade gliomas (LGGs) and have isocitrate dehydrogenase (IDH) mutations. LGGs are challenging due to their infiltrative nature, making them capable of progressing into higher-grade malignancies. Vorasidenib is a novel therapeutic agent targeting mutant IDH1/2, sparking interest in the field. Vorasidenib inhibits mutant IDH1/2 through a unique mechanism, reducing the production of the oncometabolite 2-hydroxyglutarate (2-HG). This alteration affects key enzymes and DNA methylation, impacting tumor growth and invasion. Preclinical Evidence: Preclinical studies show vorasidenib's efficacy in inhibiting mutant IDH1/2 and 2-HG production in glioma models. It suppresses tumor growth, making it a potential treatment option. Early clinical trials demonstrate vorasidenib's clinical activity in non-enhancing gliomas. It reduces 2-hydroxyglutarate levels and tumor cell proliferation, with an objective response rate and prolonged progression-free survival. The drug's safety profile is favorable. Challenges and Future Directions: Challenges include identifying predictive biomarkers and optimizing sequencing or combinations with existing therapies. Further research is needed to establish long-term effectiveness, evaluate side effects, and explore combinations with immunotherapy. orasidenib significantly advances LGG treatment, targeting a prevalent mutation and slowing tumor growth. Promising preclinical and clinical evidence and manageable side effects suggest its potential impact on LGG management. However, more research, including large trials, is needed to confirm its efficacy and role in treatment.

Olutasidenib in post-venetoclax patients with mutant isocitrate dehydrogenase 1 (mIDH1) acute myeloid leukemia (AML)

Olutasidenib, a potent, selective, oral, mutant isocitrate dehydrogenase 1 (mIDH1) inhibitor, is FDA-approved for relapsed/refractory (R/R) acute myeloid leukemia (AML). Here we report efficacy and safety of olutasidenib in 18 patients with mIDH1 AML who were relapsed (10), refractory (6) or had complete remission with incomplete hematologic recovery (CRi; 2) to a venetoclax combination. Of the 16 patients who were R/R, 4 (25%) achieved complete remission (CR), one (6.3%) achieved CR with partial hematologic recovery (CRh), and 7 (43.8%) achieved a composite complete remission (CRc). Median time to CRc was 1.9 months (range 1–2.8). As of data cutoff (18 June 2021), median duration of CRc was not reached (range, 1.2-NR, ongoing at 30.4+ months). Both patients with CRi at study entry achieved a CR. Safety was consistent with the overall profile of olutasidenib. Olutasidenib offers a valuable treatment option for patients with mIDH1 AML previously treated with venetoclax.

A personalized medicine approach identifies enasidenib as an efficient treatment for IDH2 mutant chondrosarcoma

Sarcomas represent an extensive group of malignant diseases affecting mesodermal tissues. Among sarcomas, the clinical management of chondrosarcomas remains a complex challenge, as high-grade tumours do not respond to current therapies. Mutations in the isocitrate dehydrogenase (IDH) 1 and 2 genes are among the most common mutations detected in chondrosarcomas and may represent a therapeutic opportunity. The presence of mutated IDH (mIDH) enzymes results in the accumulation of the oncometabolite 2-HG leading to molecular alterations that contribute to drive tumour growth. We developed a personalized medicine strategy based on the targeted NGS/Sanger sequencing of sarcoma samples (n= 6) and the use of matched patient-derived cell lines as a drug-testing platform. The anti-tumour potential of IDH mutations found in two chondrosarcoma cases was analysed invitro, invivo and molecularly (transcriptomic and DNA methylation analyses). We treated several chondrosarcoma models with specific mIDH1/2 inhibitors. Among these treatments, only the mIDH2 inhibitor enasidenib was able to decrease 2-HG levels and efficiently reduce the viability of mIDH2 chondrosarcoma cells. Importantly, oral administration of enasidenib in xenografted mice resulted in a complete abrogation of tumour growth. Enasidenib induced a profound remodelling of the transcriptomic landscape not associated to changes in the 5mC methylation levels and its anti-tumour effects were associated with the repression of proliferative pathways such as those controlled by E2F factors. Overall, this work provides preclinical evidence for the use of enasidenib to treat mIDH2 chondrosarcomas. Supported by the Spanish Research Agency/FEDER (grants PID2022-142020OB-I00; PID2019-106666RB-I00), the ISC III/FEDER (PI20CIII/00020; DTS18CIII/00005; CB16/12/00390; CB06/07/1009; CB19/07/00057); the GEIS group (GEIS-62); and the PCTI (Asturias)/FEDER (IDI/2021/000027).

Comparison of MRI Sequences to Predict IDH Mutation Status in Gliomas Using Radiomics-Based Machine Learning.

Regarding the 2021 World Health Organization (WHO) classification of central nervous system (CNS) tumors, the isocitrate dehydrogenase (IDH) mutation status is one of the most important factors for CNS tumor classification. The aim of our study is to analyze which of the commonly used magnetic resonance imaging (MRI) sequences is best suited to obtain this information non-invasively using radiomics-based machine learning models. We developed machine learning models based on different MRI sequences and determined which of the MRI sequences analyzed yields the highest discriminatory power in predicting the IDH mutation status. In our retrospective IRB-approved study, we used the MRI images of 106 patients with histologically confirmed gliomas. The MRI images were acquired using the T1 sequence with and without administration of a contrast agent, the T2 sequence, and the Fluid-Attenuated Inversion Recovery (FLAIR) sequence. To objectively compare performance in predicting the IDH mutation status as a function of the MRI sequence used, we included only patients in our study cohort for whom MRI images of all four sequences were available. Seventy-one of the patients had an IDH mutation, and the remaining 35 patients did not have an IDH mutation (IDH wild-type). For each of the four MRI sequences used, 107 radiomic features were extracted from the corresponding MRI images by hand-delineated regions of interest. Data partitioning into training data and independent test data was repeated 100 times to avoid random effects associated with the data partitioning. Feature preselection and subsequent model development were performed using Random Forest, Lasso regression, LDA, and Naïve Bayes. The performance of all models was determined with independent test data. Among the different approaches we examined, the T1-weighted contrast-enhanced sequence was found to be the most suitable for predicting IDH mutations status using radiomics-based machine learning models. Using contrast-enhanced T1-weighted MRI images, our seven-feature model developed with Lasso regression achieved a mean area under the curve (AUC) of 0.846, a mean accuracy of 0.792, a mean sensitivity of 0.847, and a mean specificity of 0.681. The administration of contrast agents resulted in a significant increase in the achieved discriminatory power. Our analyses show that for the prediction of the IDH mutation status using radiomics-based machine learning models, among the MRI images acquired with the commonly used MRI sequences, the contrast-enhanced T1-weighted images are the most suitable.

Abstract 4731: Targeting Lon protease as novel strategy to treat aggressive IDH mutant diffuse malignant astrocytoma

Abstract While isocitrate dehydrogenase (IDH) wild-type and mutant malignant astrocytoma (IDHwt, IDHmt) are diffuse CNS tumors that have a high degree of parallelism with one another, including microvascular proliferation and necrosis, the IDHwt tumors clinically presents with a higher tumor grade and thus poorer prognosis and survival rate. Isocitrate dehydrogenase mutation (IDH) hinders the hypoxia response in gliomas and promotes an advantageous reduction in both tumor growth and treatment resistance. Since recurrence is high, adequate characterization and identification of potential novel molecular targets in IDHmt mutant diffuse glioma is integral for developing new therapeutic strategies for better control of tumor burden and, thus, improved outcomes. Our previous published work has shown that the hypoxia responsive LONP1 mitochondrial protease is involved in glioma growth and treatment resistance and that LONP1 inhibitors can augment the effect of chemotherapy in IDHwt models. Here, we highlight the downstream activity of LONP1 via the NRF2 pathway and how synergistically, along with the IDH mutation, LONP1 overexpression can promote the subsequent proneural to mesenchymal transition (PMT) induced by stress and other tumor microenvironment signals. By characterizing the interplay between LONP1 and IDH mutation in in-vitro models, we demonstrate that oxidative stress modulates both PMT and TMZ drug resistance. When translated to an in-vivo patient-derived, intracranial orthotopic xenograft model, LONP1 overexpression is associated with decreased survival.Based on our findings, future clinical translation includes the possibility of using LONP1 as a novel target to optimize the standard of care treatment in IDH mutant diffuse astrocytoma. Citation Format: Christopher Douglas, Shashi Jain, Naomi Lomeli, Thao Vu, James Pham, Daniela A. Bota. Targeting Lon protease as novel strategy to treat aggressive IDH mutant diffuse malignant astrocytoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4731.

Abstract 4333: Identification of glucose-6-phosphate dehydrogenase dependency in IDH1 mutant glioma cells using functional genomics

Abstract Astrocytoma and oligodendroglioma are most commonly initiated by missense mutations at the arginine 132 codon of isocitrate dehydrogenase 1 (IDH1). Biochemically the mutant IDH1 protein acquires neomorphic activity: reductive NADPH-dependent catalysis of α-ketoglutarate (αKG) to (R)-2-hydroxyglutarate [(R)-2-HG]. (R)-2-HG interferes with the function of αKG-dependent epigenetic modifiers, resulting in extensive epigenetic remodeling that impairs cellular differentiation and promotes gliomagenesis. Strategies for selectively targeting IDH1-mutant cells offer promise for improved treatment over the standard modalities of surgery, chemotherapy and radiotherapy. Whole-genome CRISPR/Cas9 knockout screens were conducted to identify gene dependencies in isogenic IDH1-mutant and wild-type (WT) U-87 MG cells. Cells were transduced with the Brunello single guide RNA (sgRNA) library, grown for 21 days, then sgRNA distributions were assessed by amplicon sequencing. Gene dependencies were identified using CRISPRcleanR and BAGELR pipelines. We discovered that glucose-6-phosphate dehydrogenase (G6PD), a pentose phosphate pathway (PPP) enzyme, was needed for viability of IDH1-mutant cells, but was dispensable for U-87 MG WT cells. The PPP is the main producer of cytosolic NADPH that is required for de novo lipogenesis, maintenance of antioxidants and production of (R)-2-HG by mutant IDH1. Previous reports demonstrated that IDH1-mutant cells increase PPP flux to support these processes. We have validated this dependency using G6PDi-1, a cell-active inhibitor of G6PD. Growth inhibition (IC50) assays demonstrated that IDH1-mutant U-87 MG cells were threefold more sensitive to G6PDi-1 with IC50 of 23 μM and enhanced cell death (increased propidium iodide uptake), compared with WT U-87 MG cells with IC50 of 67 μM. G6PD knockout was then conducted to further validate this dependency. Nucleofection of IDH1 WT U-87 MG cells with G6PD multi guide RNA-Cas9 ribonucleoproteins resulted in highly efficient knockout of G6PD at day 5 (99-100%), which was maintained at day 21 (96-98%). In contrast, efficient G6PD knockout in IDH1-mutant U-87 MG cells at day 5 (98-100%) was lost following 21 days culture (0-5%), indicating death of almost all edited cells within the culture. Finally, Kaplan-Meier analysis of IDH1-mutant patients in the TCGA lower grade glioma dataset demonstrated that higher G6PD expression correlated with worse median overall survival (7.3 versus 9.5 years; log-rank p=0.01), but was not prognostic in the IDH1 WT TCGA glioblastoma multiforme dataset. These findings demonstrate that a cell line model of IDH1-mutant glioma is highly dependent on G6PD for survival. This observation builds on the recognized importance of the PPP in the metabolic biology of IDH1-mutant malignancy by establishing G6PD as a targetable dependency in this disease. Citation Format: Kim M. Paras, Pooja Patel, Paul Choi, William R. Wilson, Tet-Woo Lee, Stephen M. Jamieson, Dean C. Singleton. Identification of glucose-6-phosphate dehydrogenase dependency in IDH1 mutant glioma cells using functional genomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4333.

Integrative analysis of metabolism subtypes and identification of prognostic metabolism-related genes for glioblastoma.

Increasing evidence has demonstrated that cancer cell metabolism is a critical factor in tumor development and progression; however, its role in glioblastoma (GBM) remains limited. In the present study, we classified GBM into three metabolism subtypes (MC1, MC2, and MC3) through cluster analysis of 153 GBM samples from the RNA-sequencing data of The Cancer Genome Atlas (TCGA) based on 2752 metabolism-related genes (MRGs). We further explored the prognostic value, metabolic signatures, immune infiltration, and immunotherapy sensitivity of the three metabolism subtypes. Moreover, the metabolism scoring model was established to quantify the different metabolic characteristics of the patients. Results showed that MC3, which is associated with a favorable survival outcome, had higher proportions of isocitrate dehydrogenase (IDH) mutations and lower tumor purity and proliferation. The MC1 subtype, which is associated with the worst prognosis, shows a higher number of segments and homologous recombination defects and significantly lower mRNA expression-based stemness index (mRNAsi) and epigenetic-regulation-based mRNAsi. The MC2 subtype has the highest T-cell exclusion score, indicating a high likelihood of immune escape. The results were validated using an independent dataset. Five MRGs (ACSL1, NDUFA2, CYP1B1, SLC11A1, and COX6B1) correlated with survival outcomes were identified based on metabolism-related co-expression module analysis. Laboratory-based validation tests further showed the expression of these MRGs in GBM tissues and how their expression influences cell function. The results provide a reference for developing clinical management approaches and treatments for GBM.

Abstract 4659: A genome-wide CRISPR screen identifies ARID1A as a potential resistance marker of IDH1 inhibitor in IDH1-mutant cholangiocarcinoma cell

Abstract Background: Isocitrate dehydrogenase 1 (IDH1) mutations have been identified in approximately 20% of intrahepatic cholangiocarcinoma cases. These predominant gain-of-function mutations at codon 132 lead to abnormal production of the oncometabolite D-2-hydroxyglutarate. Targeted pharmacological disruption of the IDH1 mutation demonstrates tumor growth inhibition in IDH1-mutated cholangiocarcinoma. However, the efficacy of an IDH1 inhibitor (AG-120) as monotherapy for IDH1-mutated cholangiocarcinoma has been proven clinically insufficient, suggesting a need for investigating predictive biomarkers. In this study, we employed a genome-wide CRISPR screen to pursue resistance mechanisms to pharmacological IDH1 inhibition. Methods: The screening utilized SNU1079 cells harboring the IDH1 R132C mutation and the Brunello genome-wide CRISPR knockout (KO) pooled library (Addgene #73178, Broad Institute GPP, 4 guides/gene). The read couns of sgRNAs were normalized to reads per million, and then log2 was transformed. The log fold change (LFC) of each sgRNA of the AG-120-treated group was determined relative to that of the DMSO-treated group. Hypergeometric distribution was used to determine statistical significance. P values per gene were calculated as the average -log10(P value) of individual sgRNAs. We validated the CRISPR screening outcomes in vitro using both IDH1R132C mutant (SNU1079) and IDH1R132S mutant (RBE) cells by WST-1 assays, clonogenic assay and competition assay. (Tsujino T et al. Nat Commun. 2023) In competition assay, GFP was constitutively expressed in ARID1A-knockout cells and cultured together with ARID1A intact cells, under treatment with 1 µM AG120 or DMSO for 21 days. Relative cell numbers of GFP-positive (ARID1A-KO) cells in comparison with GFP-negative (ARID1A intact) cells were quantified using a BD LSRFortessa Analyzer (BD Biosciences). Results: Based on a volcano plot analysis, we identified three genes (SMCHD1, ARID1A, and PGP) with LFC > 1.5. Following a recent report of frequent ARID1A alteration (20%; 84/412) in a clinical study (Boerner, et al. Hepatology. 2021), we focused our research on ARID1A (LFC = 1.531; −log10 P = 3.75). WST-1 assays and clonogenic assays as short-term (3-7 days) assays failed to validate the results of CRISPR screening; however, in competition assays under treatment with AG120, cells with ARID1A-KO exhibited significantly greater proliferation in comparison with ARID1A intact cells in two different cell lines (SNU1079, RBE). Conclusions: The results demonstrated that ARID1A disruption reduced the efficacy of the IDH1 inhibitor against IDH1-mutatedcholangiocarcinoma cells. Based on these findings, we are planning comprehensive analyses employing in vivo models and clinical data to substantiate these observations. Citation Format: Tomohiro Kondo, Osamu Kikuchi, Yafeng Wang, Yukie Nakai, Tomomi Ida, Yang Cao, Trang H. Vu, Yuki Kondo, Tomohiko Sunami, Yoshihiro Yamamoto, Tomoki Saito, Shigeki Kataoka, Atsushi Yamada, Masashi Kanai, Shinya Ohashi, Manabu Muto. A genome-wide CRISPR screen identifies ARID1A as a potential resistance marker of IDH1 inhibitor in IDH1-mutant cholangiocarcinoma cell [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4659.

Abstract 5803: Tumor treating fields alter PDGFR-β localization in immortalized human pericytes in an in vitro model of the blood-brain barrier

Abstract Background: Tumor Treating Fields (TTFields) are alternating electric fields of intermediate frequency (100-500 kHz) and low intensity (1-3 V/cm). TTFields at 200 kHz, together with adjuvant chemotherapy, increased progression-free and overall survival of newly diagnosed Isocitrate dehydrogenase (IDH) wildtype and IDH mutant glioblastoma (GBM, WHO CNS 2016) patients in a randomized controlled trial and were therefore approved for the treatment of these patients. We recently demonstrated that TTFields at lower frequencies transiently increase the permeability of blood-brain barrier (BBB) models of murine and human origin by delocalizing junctional proteins such as claudin-5, ZO-1, and occludin in endothelial cells. The interaction between pericytes and endothelial cells contributes to the rigorous integrity of the BBB and is driven by endothelial cells releasing the platelet-derived growth factor β-subunit (PDGF-β), which binds to the receptor PDGFR-β on the surface of pericytes. Here, we investigated the effects of TTFields on pericytes in a human cell-based in vitro BBB model in order to gain a better understanding of the effects of TTFields on BBB integrity. Methods: We prepared an in vitro BBB model composed of human brain microvascular endothelial cells and human pericytes. The model was subjected to TTFields at 100-300 kHz for 24 to 72 h. Afterwards, pericytes were incubated with Alexa Fluor 488-labeled anti-PDGFR-β antibody in order to visualize PDGFR-β localization and cell morphology under the microscope. To make sure that no cell loss occurred due to TTFields treatment, the nuclei of pericytes were counted. Results: TTFields treatment altered the distribution of PDGFR-β staining after treatment, with fewer, less distinct and more punctate PDGFR-β foci. These changes were most prominent after 72 h of TTFields treatment at 300 kHz. We also observed larger nuclei in the pericytes after treatment but no significant loss of cells could be observed as per the nuclei count. Conclusion: Together with the previously observed delocalization of tight junctional proteins in endothelial cells, the altered distribution of PDGFR-β pericytes could reveal new mechanistic insights into the effects of TTFields on BBB integrity. Citation Format: Ellaine Salvador, Theresa Koeppl, Almuth F. Kessler, Malgorzata Burek, Ralf-Ingo Ernestus, Mario Löhr, Carsten Hagemann. Tumor treating fields alter PDGFR-β localization in immortalized human pericytes in an in vitro model of the blood-brain barrier [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5803.

Prognostic Value of ATRX and p53 Status in High-Grade Glioma Patients in Morocco.

Glioblastoma and astrocytoma, grade 4, are the most common and aggressive brain tumors. Several biomarkers, such as the isocitrate dehydrogenase mutation (IDH-1), alpha-thalassemia/mental retardation, and the X-linked mutation (ATRX), enable more accurate glioma classification and facilitate patient management. This study aimed to determine the prognostic value of clinical and molecular factors (IDH, TP53, and ATRX mutations). We also studied the relationship between these molecular markers and the overall survival (OS) of 126 patients with grade 4 glioblastoma/astrocytoma. The immunohistochemical study was conducted using antibodies namely, IDH1, R132H, p53, and ATRX. Statistical tests were used to investigate factors that might influence overall survival using IBM SPSS Statistics, version 25.0 (IBM Corp., Armonk, NY). The median age at diagnosis was 51.5 years. Patients with a Karnofsky performance score (KPS) <70 presented less favorable survival outcomes compared to those with a KPS ≥70. The median OSfor patients was found to be 11.17 months. Expression ofIDH1 R132H was found in 13.5% of patients, p53 overexpression was identified in 55.6% of cases, and loss of ATRX expression was detected in 11.9%. The group of patients with IDH mutant/ATRX mutant/p53 wild-typehad the best prognosis (OS= 27.393 months; p = 0.015). Our results were in line with previous studies. The clinical value of IDH and ATRX mutations in prognostic assessment was confirmed (p ≤0.05). The overexpression of p53 had no significant impact on OS (p = 0.726). Therefore, p53 alone cannot predict survival in glioblastoma patients. Based on the results, these biomarkers may be a potential therapeutic target to prolong patient survival, hence the need for further investigations.

Integrating Full Bayesian Inference and Student's t-Distribution Method for Enhanced Outlier Handling in Caffeine Population Pharmacokinetics: Assessing Drug-Drug Interactions with Enasidenib in Relapsed or Refractory AML and MDS Patients.

As the first-in-class, selective, and potent inhibitor of the isocitrate dehydrogenase-2 (IDH2) mutant protein, enasidenib was approved by the US Food and Drug Administration (FDA) in 2017 for the treatment of adult patients with relapsed or refractory acute myeloid leukemia (AML) with an IDH2 mutation. Known for its interactions with various cytochrome P450 (CYP)enzymes and transporters in vitro, a clinical pharmacokinetics (PK) trial was initiated to assess the impact of multiple doses of enasidenib on the single-dose PK of sensitive probe substrates of several cytochrome P450 enzymes and transporters. In this study, a population pharmacokinetic analysis approach was employed to address challenges posed by high, nonzero baseline caffeine concentrations. Moreover, we integrated full Bayesian inference into this approach innovatively for a more detailed understanding of parameter uncertainty and greater modeling flexibility, alongside Student's t-distribution for robust error modeling in handling the abnormal outlier caffeine concentration data observed in this trial. Our analyses demonstrated that multiple doses of enasidenib altered caffeine clearance to a clinically meaningful extent, as evidenced by an approximate 8-fold decrease. This finding led to a specific recommendation in the package insert to avoid the concurrent use of certain CYP1A2 substrates with enasidenib, unless directed otherwise in the prescribing information. Furthermore, this research underlines the technical benefits of integrating full Bayesian inference and incorporating Student's t-distribution for residual error modeling in the PK field.

Identification and Validation of a PEX5-Dependent Signature for Prognostic Prediction in Glioma.

Gliomas, the most prevalent and lethal form of brain cancer, are known to exhibit metabolic alterations that facilitate tumor growth, invasion, and resistance to therapies. Peroxisomes, essential organelles responsible for fatty acid oxidation and reactive oxygen species (ROS) homeostasis, rely on the receptor PEX5 for the import of metabolic enzymes into their matrix. However, the prognostic significance of peroxisomal enzymes for glioma patients remains unclear. In this study, we elucidate that PEX5 is indispensable for the cell growth, migration, and invasion of glioma cells. We establish a robust prognosis model based on the expression of peroxisomal enzymes, whose localization relies on PEX5. This PEX5-dependent signature not only serves as a robust prognosis model capable of accurately predicting outcomes for glioma patients, but also effectively distinguishes several clinicopathological features, including the grade, isocitrate dehydrogenase (IDH) mutation, and 1p19q codeletion status. Furthermore, we developed a nomogram that integrates the prognostic model with other clinicopathological factors, demonstrating highly accurate performance in estimating patient survival. Patients classified into the high-risk group based on our prognostic model exhibited an immunosuppressive microenvironment. Finally, our validation reveals that the elevated expression of GSTK1, an antioxidant enzyme within the signature, promotes the cell growth and migration of glioma cells, with this effect dependent on the peroxisomal targeting signal recognized by PEX5. These findings identify the PEX5-dependent signature as a promising prognostic tool for gliomas.

Identification of mIDH1 R132C/S280F Inhibitors from Natural Products by Integrated Molecular Docking, Pharmacophore Modeling and Molecular Dynamics Simulations.

Mutant isocitrate dehydrogenase 1 (mIDH1) is a common driving factor in acute myeloid leukemia (AML), with the R132 mutation accounting for a high proportion. The U.S. Food and Drug Administration (FDA) approved Ivosidenib, a molecular entity that targets IDH1 with R132 mutations, as a promising therapeutic option for AML with mIDH1 in 2018. It was of concern that the occurrence of disease resistance or recurrence, attributed to the IDH1 R132C/S280F second site mutation, was observed in certain patients treated with Ivosidenib within the same year. Furthermore, it should be noted that most mIDH1 inhibitors demonstrated limited efficacy against mutations at this specific site. Therefore, there is an urgent need to investigate novel inhibitors targeting mIDH1 for combating resistance caused by IDH1 R132C/S280F mutations in AML. This study aimed to identify novel mIDH1 R132C/S280F inhibitors through an integrated strategy of combining virtual screening and dynamics simulations. First, 2000 hits were obtained through structure-based virtual screening of the COCONUT database, and hits with better scores than -10.67 kcal/mol were obtained through molecular docking. A total of 12 potential small molecule inhibitors were identified through pharmacophore modeling screening and Prime MM-GBSA. Dynamics simulations were used to study the binding modes between the positive drug and the first three hits and IDH1 carrying the R132C/S280F mutation. RMSD showed that the four dynamics simulation systems remained stable, and RMSF and Rg showed that the screened molecules have similar local flexibility and tightness to the positive drug. Finally, the lowest energy conformation, hydrogen bond analysis, and free energy decomposition results indicate that in the entire system the key residues LEU120, TRP124, TRP267, and VAL281 mainly contribute van der Waals forces to the interaction, while the key residues VAL276 and CYS379 mainly contribute electrostatic forces.

A novel prognostic risk-scoring system based on m5C methylation regulator-mediated patterns for glioma patients

N5-methylcytosine (m5C) methylation modification plays a crucial role in the epigenetic mechanisms underlying tumorigenesis, aggressiveness, and malignancy in diffuse glioma. Our study aimed to develop a novel prognostic risk-scoring system to assess the impact of m5C modification in glioma patients. Initially, we identified two distinct m5C clusters based on the expression level of m5C regulators in The Cancer Genome Atlas glioblastoma (TCGA-GBM) dataset. Differentially expressed genes (DEGs) between the two m5C cluster groups were determined. Utilizing these m5C regulation-related DEGs, we classified glioma patients into three gene cluster groups: A, B, and C. Subsequently, an m5C scoring system was developed through a univariate Cox regression model, quantifying the m5C modification patterns utilizing six DEGs associated with disease prognosis. The resulting scoring system allowed us to categorize patients into high- or low-risk groups based on their m5C scores. In test (TCGA-GBM) and validation (Chinese Glioma Genome Atlas [CGGA]-1018 and CGGA-301) datasets, glioma patients with a higher m5C score consistently exhibited shorter survival durations, fewer isocitrate dehydrogenase (IDH) mutations, less 1p/19q codeletion and higher World Health Organization (WHO) grades. Additionally, distinct immune cell infiltration characteristics were observed among different m5C cluster groups and risk groups. Our study developed a novel prognostic scoring system based on m5C modification patterns for glioma patients, complementing existing molecular classifications and providing valuable insights into prognosis for glioma patients.

Abstract PR-008: Modeling epigenetic lesions that cause gliomas

Abstract PR-008: Modeling epigenetic lesions that cause gliomas

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.

Imaging Role in Diagnosis, Prognosis, and Treatment Response Prediction Associated with High-grade Glioma.

Glioma is one of the most drug and radiation-resistant tumors. Gliomas suffer from inter- and intratumor heterogeneity which makes the outcome of similar treatment protocols vary from patient to patient. This article is aimed to overview the potential imaging markers for individual diagnosis, prognosis, and treatment response prediction in malignant glioma. Furthermore, the correlation between imaging findings and biological and clinical information of glioma patients is reviewed. The search strategy in this study is to select related studies from scientific websites such as PubMed, Scopus, Google Scholar, and Web of Science published until 2022. It comprised a combination of keywords such as Biomarkers, Diagnosis, Prognosis, Imaging techniques, and malignant glioma, according to Medical Subject Headings. Some imaging parameters that are effective in glioma management include: ADC, FA, Ktrans, regional cerebral blood volume (rCBV), cerebral blood flow (CBF), ve, Cho/NAA and lactate/lipid ratios, intratumoral uptake of 18F-FET (for diagnostic application), RD, ADC, ve, vp, Ktrans, CBFT1, rCBV, tumor blood flow, Cho/NAA, lactate/lipid, MI/Cho, uptakes of 18F-FET, 11C-MET, and 18F-FLT (for prognostic and predictive application). Cerebral blood volume and Ktrans are related to molecular markers such as vascular endothelial growth factor (VEGF). Preoperative ADCmin value of GBM tumors is associated with O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. 2-hydroxyglutarate metabolite and dynamic 18F-FDOPA positron emission tomography uptake are related to isocitrate dehydrogenase (IDH) mutations. Parameters including ADC, RD, FA, rCBV, Ktrans, vp, and uptake of 18F-FET are useful for diagnosis, prognosis, and treatment response prediction in glioma. A significant correlation between molecular markers such as VEGF, MGMT, and IDH mutations with some diffusion and perfusion imaging parameters has been identified.

Whole-tumor histogram analysis of synthetic magnetic resonance imaging predicts isocitrate dehydrogenase mutation status in gliomas.

An accurate assessment of isocitrate dehydrogenase (IDH) status in patients with glioma is crucial for treatment planning and is a key factor in predicting patient outcomes. In this study, we investigated the potential value of whole-tumor histogram metrics derived from synthetic magnetic resonance imaging (MRI) in distinguishing IDH mutation status between astrocytoma and glioblastoma. In this prospective study, 80 glioma patients were enrolled from September 2019 to June 2022. All patients underwent pre- and post-contrast synthetic MRI scan protocol. Immunohistochemistry (IHC) staining or gene sequencing were used to assess IDH mutation status in tumor tissue samples. Whole-tumor histogram metrics, including T1, T2, proton density (PD), etc., were extracted from the quantitative maps, while radiological features were assessed by synthetic contrast-weighted maps. Basic clinical features of the patients were also evaluated. Differences in clinical, radiological, and histogram metrics between IDH-mutant astrocytoma and IDH-wildtype glioblastoma were analyzed using univariate analyses. Variables with statistical significance in univariate analysis were included in multivariate logistic regression analysis to develop the combined model. Receiver operating characteristic (ROC) and area under the curve (AUC) were used to assess the diagnostic performance of metrics and models. The histopathologic analysis revealed that of the 80 cases, 41 were classified as IDH-mutant astrocytoma and 39 as IDH-wildtype glioblastoma. Compared to IDH-wildtype glioblastoma, IDH-mutant astrocytoma showed significantly lower T1 [10th percentile (10th), mean, and median] and post-contrast PD (10th, 90th percentile, mean, median, and maximum) values as well as higher post-contrast T1 (cT1) (10th, mean, median, and minimum) values (all P<0.05). The combined model (T1-10th + cT1-10th + age) was developed by integrating the independent influencing factors of IDH-mutant astrocytoma using the multivariate logistic regression. The diagnostic performance of this model [AUC =0.872 (0.778-0.936), sensitivity =75.61%, and specificity =89.74%] was superior to the clinicoradiological model, which was constructed using age and enhancement degree (AUC =0.822 (0.870-0.898), P=0.035). The combined model constructed using histogram metrics derived from synthetic MRI could be a valuable preoperative tool to distinguish IDH mutation status between astrocytoma and glioblastoma, and subsequently, could assist in the decision-making process of pretreatment.