IDH mutation in glioma: molecular mechanisms and potential therapeutic targets

Akyerli C, K. Yüksel Ş, E. Danyeli A, Tihan T, Sezerman OU, Yakıcıer MC, Pamir MN, Özduman K. Mutations and Copy Number Alterations in IDH Wild-Type Glioblastomas Are Shaped by Different Oncogenic Mechanisms

Little is known about the mutational processes that shape the genetic landscape of gliomas. Numerous mutational processes leave marks on the genome in the form of mutations, copy number alterations, rearrangements or their combinations. To explore gliomagenesis, we hypothesized that gliomas with different underlying oncogenic mechanisms would have differences in the burden of various forms of these genomic alterations. This was an analysis on adult diffuse gliomas, but IDH-mutant gliomas as well as diffuse midline gliomas H3-K27M were excluded to search for the possible presence of new entities among the very heterogenous group of IDH-WT glioblastomas. The cohort was divided into two molecular subsets: (1) Molecularly-defined GBM (mGBM) as those that carried molecular features of glioblastomas (including TERT promoter mutations, 7/10 pattern, or EGFR-amplification), and (2) those who did not (others). Whole exome sequencing was performed for 37 primary tumors and matched blood samples as well as 8 recurrences. Single nucleotide variations (SNV), short insertion or deletions (indels) and copy number alterations (CNA) were quantified using 5 quantitative metrics (SNV burden, indel burden, copy number alteration frequency-wGII, chromosomal arm event ratio-CAER, copy number amplitude) as well as 4 parameters that explored underlying oncogenic mechanisms (chromothripsis, double minutes, microsatellite instability and mutational signatures). Findings were validated in the TCGA pan-glioma cohort. mGBM and "Others" differed significantly in their SNV (only in the TCGA cohort) and CNA metrics but not indel burden. SNV burden increased with increasing age at diagnosis and at recurrences and was driven by mismatch repair deficiency. On the contrary, indel and CNA metrics remained stable over increasing age at diagnosis and with recurrences. Copy number alteration frequency (wGII) correlated significantly with chromothripsis while CAER and CN amplitude correlated significantly with the presence of double minutes, suggesting separate underlying mechanisms for different forms of CNA.

Current biomarker-associated procedures of cancer modeling-a reference in the context of IDH1 mutant glioma

Isocitrate dehydrogenases (IDH1/2) are central molecular markers for glioblastoma. Providing in vitro or in vivo models with mutated IDH1/2 can help prepare facilities to understand the biology of these mutated genes as glioma markers, as well as help, improve therapeutic strategies. In this review, we first summarize the biology principles of IDH and its mutations and outline the core primary findings in the clinical context of neuro-oncology. Given the extensive research interest and exciting developments in current stem cell biology and genome editing, the central part of the manuscript is dedicated to introducing various routes of disease modeling strategies of IDH mutation (IDHMut) glioma and comparing the scientific-technological findings from the field using different engineering methods. Lastly, by giving our perspective on the benefits and limitations of patient-derived and donor-derived disease modeling respectively, we aim to propose leading research questions to be answered in the context of IDH1 and glioma.

A Novel Four-Gene Signature Associated With Immune Checkpoint for Predicting Prognosis in Lower-Grade Glioma

The overall survival of patients with lower grade glioma (LGG) varies greatly, but the current histopathological classification has limitations in predicting patients’ prognosis. Therefore, this study aims to find potential therapeutic target genes and establish a gene signature for predicting the prognosis of LGG. CD44 is a marker of tumor stem cells and has prognostic value in various tumors, but its role in LGG is unclear. By analyzing three glioma datasets from Gene Expression Omnibus (GEO) database, CD44 was upregulated in LGG. We screened 10 CD44-related genes via protein–protein interaction (PPI) network; function enrichment analysis demonstrated that these genes were associated with biological processes and signaling pathways of the tumor; survival analysis showed that four genes (CD44, HYAL2, SPP1, MMP2) were associated with the overall survival (OS) and disease-free survival (DFS)of LGG; a novel four-gene signature was constructed. The prediction model showed good predictive value over 2-, 5-, 8-, and 10-year survival probability in both the development and validation sets. The risk score effectively divided patients into high- and low- risk groups with a distinct outcome. Multivariate analysis confirmed that the risk score and status of IDH were independent prognostic predictors of LGG. Among three LGG subgroups based on the presence of molecular parameters, IDH-mutant gliomas have a favorable OS, especially if combined with 1p/19q codeletion, which further confirmed the distinct biological pattern between three LGG subgroups, and the gene signature is able to divide LGG patients with the same IDH status into high- and low- risk groups. The high-risk group possessed a higher expression of immune checkpoints and was related to the activation of immunosuppressive pathways. Finally, this study provided a convenient tool for predicting patient survival. In summary, the four prognostic genes may be therapeutic targets and prognostic predictors for LGG; this four-gene signature has good prognostic prediction ability and can effectively distinguish high- and low-risk patients. High-risk patients are associated with higher immune checkpoint expression and activation of the immunosuppressive pathway, providing help for screening immunotherapy-sensitive patients.

The Value of Enhanced MR Radiomics in Estimating the IDH1 Genotype in High-Grade Gliomas

Background

The prognosis of IDH1-mutant glioma is significantly better than that of wild-type glioma, and the preoperative identification of IDH mutations in glioma is essential for the formulation of surgical procedures and prognostic assessment.

Purpose

To explore the value of a radiomic model based on preoperative-enhanced MR images in the assessment of the IDH1 genotype in high-grade glioma.

Materials and Methods

A retrospective analysis was performed on 182 patients with high-grade glioma confirmed by surgical pathology between December 2012 and January 2019 in our hospital with complete preoperative brain-enhanced MR images, including 79 patients with an IDH1 mutation (45 patients with WHO grade III and 34 patients with WHO grade IV) and 103 patients with wild-type IDH1 (33 patients with WHO grade III and 70 patients with WHO grade IV). Patients were divided into a primary dataset and a validation dataset at a ratio of 7 : 3 using a stratified random sampling; radiomic features were extracted using A.K. (Analysis Kit, GE Healthcare) software and were initially reduced using the Kruskal-Wallis and Spearman analyses. Lasso was finally conducted to obtain the optimized subset of the feature to build the radiomic model, and the model was then tested with cross-validation. ROC (receiver operating characteristic curve) analysis was performed to evaluate the performance of the model.

Results

The radiomic model showed good discrimination in both the primary dataset (AUC = 0.87, 95% CI: 0.754 to 0.855, ACC = 0.798, sensitivity = 85.5%, specificity = 75.4%, positive predictive value = 0.734, and negative predictive value = 0.867) and the validation dataset (AUC = 0.86, 95% CI: 0.690 to 0.913, ACC = 0.789, sensitivity = 91.3%, specificity = 69.0%, positive predictive value = 0.700, and negative predictive value = 0.909).

Conclusion

The radiomic model, based on the preoperative-enhanced MR, can effectively predict the IDH1 genotype in high-grade glioma.

Present and Future of Anti-Glioblastoma Therapies: A Deep Look into Molecular Dependencies/Features

Glioblastoma (GBM) is aggressive malignant tumor residing within the central nervous system. Although the standard treatment options, consisting of surgical resection followed by combined radiochemotherapy, have long been established for patients with GBM, the prognosis is still poor. Despite recent advances in diagnosis, surgical techniques, and therapeutic approaches, the increased patient survival after such interventions is still sub-optimal. The unique characteristics of GBM, including highly infiltrative nature, hard-to-access location (mainly due to the existence of the blood brain barrier), frequent and rapid recurrence, and multiple drug resistance mechanisms, pose challenges to the development of an effective treatment. To overcome current limitations on GBM therapy and devise ideal therapeutic strategies, efforts should focus on an improved molecular understanding of GBM pathogenesis. In this review, we summarize the molecular basis for the development and progression of GBM as well as some emerging therapeutic approaches.

Vessel Size Imaging is Associated with IDH Mutation and Patient Survival in Diffuse Lower-Grade Glioma

Background

Patients with isocitrate dehydrogenase (IDH) mutant gliomas have better survival and appear to be more sensitive to chemotherapy than their IDH wild-type counterparts. We attempted to assess the correlations of vessel size imaging (VSI) values with IDH mutation status and patient survival in diffuse lower-grade glioma (LGG).

Methods

We enrolled 60 patients with diffuse LGGs, among which 43 had IDH-mutant tumors. All patients underwent VSI examination and VSI values for active tumors were calculated. Receiver operating characteristic (ROC) curves were established to evaluate the detection efficiency. Logistic regression was employed to determine the ability of variables to discriminate IDH mutational status. Kaplan–Meier survival analysis and Cox proportional hazards models were utilized to estimate the correlations of VSI values and other risk factors with patient survival.

Results

We observed that VSI values were lower in IDH-mutant LGGs than IDH wild-type LGGs. The VSImax and VSImean values had AUC values of 0.7305 and 0.7401, respectively, in distinguishing IDH-mutant LGGs from IDH wild-type LGGs. Logistic regression showed that VSImean values, age and tumor location were associated with IDH-mutant status, and the formula integrating the three factors had an AUC value of 0.7798 when distinguishing IDH-mutant LGGs from IDH wild-type LGGs. Moreover, LGG patients with high VSI values exhibited worse survival rates than those with low VSI values for both progression-free survival (PFS) and overall survival (OS). Multivariate Cox proportional hazards regression analysis suggested that IDH mutation status, VSImean values and multiple lesions or lobes were risk factors for PFS of LGG patients.

Conclusion

VSI value is associated with IDH genotype and maybe an independent predictor of the survival of patients with LGGs.

A SEMA3 Signaling Pathway-Based Multi-Biomarker for Prediction of Glioma Patient Survival

Glioma is a lethal central nervous system tumor with poor patient survival prognosis. Because of the molecular heterogeneity, it is a challenge to precisely determine the type of the tumor and to choose the most effective treatment. Therefore, novel biomarkers are essential to improve the diagnosis and prognosis of glioma tumors. Class 3 semaphorin proteins (SEMA3) play an important role in tumor biology. SEMA3 transduce their signals by using neuropilin and plexin receptors, which functionally interact with the vascular endothelial growth factor-mediated signaling pathways. Therefore, the aim of this study was to explore the potential of SEMA3 signaling molecules for prognosis of glioma patient survival. The quantitative real-time PCR method was used to evaluate mRNA expression of SEMA3(A-G), neuropilins (NRP1 and NRP2), plexins (PLXNA2 and PLXND1), cadherins (CDH1 and CDH2), integrins (ITGB1, ITGB3, ITGA5, and ITGAV), VEGFA and KDR genes in 59 II-IV grade glioma tissues. Seven genes significantly associated with patient overall survival were used for multi-biomarker construction, which showed 64%, 75%, and 68% of accuracy of predicting the survival of 1-, 2-, and 3-year glioma patients, respectively. The results suggest that the seven-gene signature could serve as a novel multi-biomarker for more accurate prognosis of a glioma patient’s outcome.

The neural stem-cell marker CD24 is specifically upregulated in IDH-mutant glioma

BACKGROUND

Malignant gliomas have disproportionally high morbidity and mortality. Heterozygous mutations in the isocitrate dehydrogenase 1 (IDH1) gene are most common in glioma, resulting in predominantly arginine to histidine substitution at codon 132. Because IDH1R132H requires a wild-type allele to produce (D)-2-hydroxyglutarate for epigenetic reprogramming, loss of IDH1R132H heterozygosity is associated with glioma progression in an IDH1-wildtype-like phenotype. Although previous studies have reported that transgenic IDH1R132H induces the expression of nestin-a neural stem-cell marker, the underlying mechanism remains unclear. Furthermore, this finding seems at odds with better outcome of IDH1R132H glioma because of a negative association of nestin with overall survival.

METHODS

Gene expression was compared between IDH1R132H-hemizygous and IDH1R132H-heterozygous glioma cells under adherent and spheroid growth conditions. The results were validated for (D)-2-hydroxyglutarate responsiveness by pharmacologic agents, associations with DNA methylation by bioinformatic analysis, and associations with overall survival. Bisulfite DNA sequencing, chromatin immunoprecipitation, and pharmacological approach were used.

FINDINGS

Neural stem-cell marker genes, including CD44, NES, and PROM1, are generally downregulated in IDH-mutant gliomas and IDH1R132H-heterozygous spheroid growth compared respectively with IDH-wildtype gliomas and IDH1R132H-hemizygous spheroid growth, in agreement with their negative associations with patient outcome. In contrast, CD24 is specifically upregulated and apparently associated with better survival. CD24 and NES expression respond differentially to alteration of (D)-2-hydroxyglutarate levels. CD24 upregulation is associated with histone and DNA demethylation as opposed to hypermethylation in the downregulated genes.

INTERPRETATION

The better outcome of IDH-mutant glioma is orchestrated exquisitely through epigenetic reprogramming that directs bidirectional expression of neural stem-cell marker genes.

XGBoost Improves Classification of MGMT Promoter Methylation Status in IDH1 Wildtype Glioblastoma

Approximately 96% of patients with glioblastomas (GBM) have IDH1 wildtype GBMs, characterized by extremely poor prognosis, partly due to resistance to standard temozolomide treatment. O6-Methylguanine-DNA methyltransferase (MGMT) promoter methylation status is a crucial prognostic biomarker for alkylating chemotherapy resistance in patients with GBM. However, MGMT methylation status identification methods, where the tumor tissue is often undersampled, are time consuming and expensive. Currently, presurgical noninvasive imaging methods are used to identify biomarkers to predict MGMT methylation status. We evaluated a novel radiomics-based eXtreme Gradient Boosting (XGBoost) model to identify MGMT promoter methylation status in patients with IDH1 wildtype GBM. This retrospective study enrolled 53 patients with pathologically proven GBM and tested MGMT methylation and IDH1 status. Radiomics features were extracted from multimodality MRI and tested by F-score analysis to identify important features to improve our model. We identified nine radiomics features that reached an area under the curve of 0.896, which outperformed other classifiers reported previously. These features could be important biomarkers for identifying MGMT methylation status in IDH1 wildtype GBM. The combination of radiomics feature extraction and F-core feature selection significantly improved the performance of the XGBoost model, which may have implications for patient stratification and therapeutic strategy in GBM.

Development of Autophagy Signature-Based Prognostic Nomogram for Refined Glioma Survival Prognostication

The current glioma classification could be optimized to cover such a separate and individualized prognosis ranging from a few months to over ten years. Considering its highly conserved role and potential in therapies, autophagy might be a promising element to be incorporated as a refinement for improved survival prognostication. The expression and RNA-seq data of 881 glioma patients from the Gene Expression Omnibus and The Cancer Genome Atlas were included, mapped with autophagy-related genes. Weighted gene coexpression network analysis and Cox regression analysis were used for the autophagy signature establishment, which composed of MUL1, NPC1, and TRIM13. Validations were represented by Kaplan-Meier plots and receiver operating curves (ROC). Cluster analysis suggested the IDH1 mutant involved in the favorable prognosis of the signature clusters. The signature was also immune-related shown by the Gene Ontology analysis and the Gene Set Enrichment Analysis. The high signature risk group held a higher ESTIMATE score (p = 2.6e - 11) and stromal score (p = 1.8e - 10). CD276 significantly correlated with the signature (r = 0.51, p < 0.05). The final nomogram integrated with the autophagy signature, IDH1 mutation, and pathological grade was built with accuracy and discrimination (1-year survival AUC = 0.812, 5-year survival AUC = 0.822, and 10-year survival AUC = 0.834). Its prognostic value and clinical utility were well-defined by the superiority in the comparisons with the current World Health Organization glioma classification in ROC (p < 0.05) and decision curve analysis. The autophagy signature-based IDH1 mutation and grade nomogram refined glioma classification for a more individualized and clinically applicable survival estimation and inspired potential autophagy-related therapies.

Isocitrate Dehydrogenase Mutations in Glioma: Genetics, Biochemistry, and Clinical Indications

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

IDH1 Targeting as a New Potential Option for Intrahepatic Cholangiocarcinoma Treatment-Current State and Future Perspectives

Cholangiocarcinoma is a primary malignancy of the biliary tract characterized by late and unspecific symptoms, unfavorable prognosis, and few treatment options. The advent of next-generation sequencing has revealed potential targetable or actionable molecular alterations in biliary tumors. Among several identified genetic alterations, the IDH1 mutation is arousing interest due to its role in epigenetic and metabolic remodeling. Indeed, some IDH1 point mutations induce widespread epigenetic alterations by means of a gain-of-function of the enzyme, which becomes able to produce the oncometabolite 2-hydroxyglutarate, with inhibitory activity on α-ketoglutarate-dependent enzymes, such as DNA and histone demethylases. Thus, its accumulation produces changes in the expression of several key genes involved in cell differentiation and survival. At present, small-molecule inhibitors of IDH1 mutated enzyme are under investigation in preclinical and clinical phases as promising innovative treatments for IDH1-mutated intrahepatic cholangiocarcinomas. This review examines the molecular rationale and the results of preclinical and early-phase studies on novel pharmacological agents targeting mutant IDH1 in cholangiocarcinoma patients. Contextually, it will offer a starting point for discussion on combined therapies with metabolic and epigenetic drugs, to provide molecular support to target the interplay between metabolism and epigenetics, two hallmarks of cancer onset and progression.