Isocitrate Dehydrogenase Gene Research Articles

Correlation of IDH1 gene expression error in breast tumor biopsy in patients with invasive ductal carcinoma.

One of the most important cancers in terms of worldwide prevalence is breast tumors, which have been less investigated in correlation with the enzyme Isocitrate Dehydrogenase 1 (IDH1) gene. The aim of this study was that expression of this gene could have significant effects on the progression of metastasis and invasive disease in breast cancer patients. We used the molecular method of RT-PCR with SYBR-Green to analyze breast tumor tissue from patients with metastasis and non-metastasis, the latter confirmed by the pathology department of Shohada-e Tajrish Hospital (serving as a control group). Also, patients population and its relationship with the degree of tumor in the IDH1 gene was investigated. The IDH1 gene has shown high expression in patients with metastatic breast cancer rather than in patients with non-metastatic breast cancer. The metastatic samples were compared with non-metastatic samples for IDH1 mRNA expression. In this research work, 72.5% (29 samples) were up-regulated in comparison to 27.5% of samples (11 samples) that did not exhibit high expression (P=0.000). This study examined the IDH1 gene expression, suggesting that changes in this gene's expression could impact the prognosis of breast cancer. However, further research is needed to draw definitive conclusions.

Potato glycoside alkaloids exhibit antifungal activity by regulating the tricarboxylic acid cycle pathway of Fusarium solani.

Fusarium solani is a pathogenic fungus that causes significant harm, leading to crop yield reduction, fruit quality reduction, postharvest decay, and other diseases. This study used potato glycoside alkaloids (PGA) as inhibitors to investigate their effects on the mitochondrial structure and tricarboxylic acid (TCA) cycle pathway of F. solani. The results showed that PGA could inhibit the colony growth of F. solani (54.49%), resulting in the disappearance of the mitochondrial membrane and the loss of contents. PGA significantly decreased the activities of aconitase (ACO), isocitrate dehydrogenase (IDH), α-ketoglutarate dehydrogenase (α-KGDH), succinate dehydrogenase (SDH), fumarase (FH), malate dehydrogenase (MDH), succinyl-CoA synthetase (SCS), and increased the activity of citrate synthase (CS) in F. solani. After PGA treatment, the contents of acetyl coenzyme A (CoA), citric acid (CA), malic acid (L-MA), and α-ketoglutaric acid (α-KG) in F. solani were significantly decreased. The contents of isocitric acid (ICA), succinyl coenzyme A (S-CoA), succinic acid (SA), fumaric acid (FA), and oxaloacetic acid (OA) were significantly increased. Transcriptomic analysis showed that PGA could significantly affect the expression levels of 19 genes related to TCA cycle in F. solani. RT-qPCR results showed that the expression levels of ACO, IDH, α-KGDH, and MDH-related genes were significantly down-regulated, and the expression levels of SDH and FH-related genes were significantly up-regulated, which was consistent with the results of transcriptomics. In summary, PGA can achieve antifungal effects by reducing the tricarboxylic acid cycle's flow and regulating key genes' expression levels. This study reveals the antifungal mechanism of PGA from the perspective of TCA cycle, and provides a theoretical basis for the development and application of PGA as a biopesticide.

Abstract LB193: Enhanced single cell DNA methylation analysis using combinatorial indexing

Abstract The epigenetic landscape of the human brain undergoes a plethora of changes during malignant transformation. In recent years, DNA methylation-based epigenetic modifications have been widely studied using traditional techniques like bisulfite sequencing and enzymatic methyl sequencing (EM-seq). However, these methods analyze bulk cell populations and lack the granularity of single-cell analysis. Although advances in single-cell analysis have revolutionized our understanding of cellular heterogeneity and functional diversity within complex biological systems, they are still costly, low throughput, and laborious. To address these challenges, ScaleBio has pioneered combinatorial indexing technology, enabling a significant increase in cell throughput. This method utilizes the cell itself as a compartment to perform 2-3 rounds of sequential barcoding in a plate-based workflow, eliminating the need for complex instrumentation. This technology has been successfully adapted to assess DNA methylation at the single-cell level offering a robust, affordable, high-throughput protocol that enhances yield, diversity, and coverage. In this study we used ScaleBio's single-cell methylation kit to investigate DNA methylation patterns during oncogenesis using cancer cells with widespread DNA methylation changes, such as human isocitrate dehydrogenase (IDH) mutant glioma cells at the single-cell level. The IDH gene family, comprising of IDH1, IDH2, and IDH3, encodes enzymes involved in the tricarboxylic acid (TCA) cycle. IDH1/2 mutations are present in over 80% of low-grade gliomas while IDH-mutant gliomas constitute about 1/5th of all adult diffuse gliomas, thus making them one of the most common brain tumor subtypes. As such, IDH mutations have emerged as attractive therapeutic targets for glioma treatment. By uncovering DNA methylation patterns at the single cell level, we provide here an epigenetic map to better understand this complex disease and better inform clinical discoveries. We achieved high cell recovery and robust cytosine coverage throughout our analysis of single cell methylomes isolated from human glioma tumor tissue. Using this data we generated a ranked list of the top hypo- and hypermethylated genomic regions and identified cell type specific clusters seen in different pathological states by looking at Differentially Methylated Regions (DMR) uncovering unique single-cell methylation profiles that may be obscured by bulk or pseudo-bulk analysis. These data show that the ScaleBio single-cell methylation workflow offers increased sensitivity, specificity, and accuracy in identifying DNA methylation sites when compared to other techniques while offering a comprehensive view of methylomes and providing insights into cellular heterogeneity and trajectories. Citation Format: Sanika Khare, Dominic Skinner, Maggie Nakamoto, Hosu Sin, Ashley Woodfin, Eric Pu, Lin Lin, Jason Koth, Beth Walczak. Enhanced single cell DNA methylation analysis using combinatorial indexing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB193.

Efficacy of Personalized Postoperative Epilepsy Management in Patients with Glioblastoma Utilizing IDH1 Gene Assessment.

We explored the correlation between the presence of isocitrate dehydrogenase-1 (IDH1) mutations and the incidence of postoperative epilepsy in patients with glioblastoma, as well as assessed the efficacy of preemptive administration of antiepileptic medications in mitigating the occurrence of postoperative epilepsy. Fifty-three patients who received a postoperative pathological diagnosis of glioblastoma, were enrolled in this study. Tumor specimens were subjected to IDH1 gene analysis. The patient cohort was stratified based on their IDH1 mutation status and the administration of prophylactic antiepileptic drugs during the postoperative phase. We subsequently conducted a comparative analysis of postoperative epileptic complications within each patient subgroup. In the cohort of 53 patients under study, the occurrence of epilepsy was observed in 10 out of 21 patients carrying IDH1 mutations, while 5 out of 32 patients with wild-type IDH1 also experienced epilepsy, revealing a statistically significant difference (P < 0.05). Among the 27 patients who received prophylactic antiepileptic drugs, 6 of them developed epilepsy, whereas 9 out of 26 patients who did not receive prophylactic antiepileptic drugs exhibited concurrent epilepsy, with no statistically significant difference (P > 0.05). However, when performing a subgroup analysis, it was found that 3 out of 12 patients with IDH1 mutations who received prophylactic antiepileptic drugs experienced epilepsy, whereas 7 out of 9 patients who did not receive prophylactic antiepileptic drugs developed epilepsy, demonstrating a statistically significant difference (P < 0.05). Furthermore, within the group of 15 patients with wild-type IDH1, 3 patients who received prophylactic antiepileptic drugs developed epilepsy, while 2 cases of epilepsy occurred among the 17 patients who did not receive prophylactic antiepileptic drugs, with no statistically significant difference (P > 0.05). In individuals with IDH1 mutant glioblastoma who have undergone surgical resection, the implementation of preventive antiepileptic therapy demonstrates a potential to diminish the occurrence of postoperative epilepsy.

MODERN IMAGING TECHNIQUES IN THE ASSESSMENT&#x0D; OF MALIGNANCY IN GLIAL BRAIN TUMORS:&#x0D; LITERATURE REVIEW

Relevance: Gliomas represent a major group of primary central nervous system tumors, accounting for approximately 80% of all&#x0D; 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&#x0D; mutations, which are found in a large proportion of gliomas, are associated with a better prognosis and represent an important biomarker&#x0D; for the development of targeted therapeutic strategies. Diagnostic techniques, particularly magnetic resonance imaging (MRI), also play&#x0D; an important role, providing additional ways to assess the morphological and biological characteristics of gliomas, contributing to a more&#x0D; accurate determination of tumor malignancy and molecular profile, which is key to treatment decisions.&#x0D; The purpose: To study the possibilities of magnetic resonance imaging in assessing the degree of malignancy of glial brain tumors.&#x0D; Method: A literature review was performed using the keywords: glioma, IDH mutation, IDH wild-type, MRI, magnetic resonance&#x0D; spectroscopy (MRS), apparent diffusion coefficient (ADC), diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), diffusion kurtosis&#x0D; image (DKI), Susceptibility Weighted Imaging (SWI) in PubMed, BMC Medicine, and Google Scholar databases. The review includes the results&#x0D; of an analysis of 45 literature reviews on the diagnostic capabilities of molecular diagnostics and MRI to assess the malignancy of gliomas.&#x0D; Results: This review highlights the importance of current approaches to the diagnosis of gliomas, demonstrating that different grades of&#x0D; malignancy and IDH mutation status are associated with unique features on MR imaging, including differences in localization, signal, and&#x0D; enhancement patterns. DTI and DWI extend the ability of MRI to assess tissue microstructure, allowing for more precise tumor characterization.&#x0D; Studies combining MRI morphologic features, ADC and DTI parameters offer a non-invasive approach to glioma prognosis, highlighting the&#x0D; importance of integrated use of imaging modalities to improve diagnosis and therapy.&#x0D; Conclusion: The use of magnetic resonance imaging allows for more accurate morphologic and metabolic characterization of gliomas&#x0D; in assessing the degree of malignancy, allowing physicians to make more accurate prognostic assessments and select the most appropriate&#x0D; treatment strategy.&#x0D; Keywords: Glioma, IDH mutation, wild-type IDH, MRI, magnetic resonance spectroscopy, ADC, DWI, DTI, DKI, SWI

Abstract 5585: Genetic variants of IDH and EGFR as diagnostic and prognostic biomarkers in glioblastoma multiforme: A case-control study in the Jordanian Arab population

Abstract Background: Glioblastoma multiforme (GBM) represents a highly aggressive primary brain tumor with poor prognosis. Mutation in the Isocitrate dehydrogenase (IDH1) gene and epidermal growth factor (EGFR) amplification are key diagnostic markers for GBM. However, the prognostic role of genetic variants of these genes remains unclear. Therefore, we aimed to investigate the association between specific single nucleotide polymorphisms (SNPs) for IDH and EGFR genes, and their impact on the risk and prognosis of GBM patients within the Jordanian Arab population. Methods: We carried out a case-control study involving 63 GBM patients and 226 healthy controls at King Abdullah University Hospital in Jordan. Genomic DNA was extracted from formalin-fixed and paraffin-embedded tissue for GBM patients and blood samples for controls. IDH1 (rs121913500C&amp;gt;T), IDH2 (rs11540478G&amp;gt;A), EGFR (rs231677G&amp;gt;A), and EGFR (rs1468727C&amp;gt;T) SNPs were genotyped and analyzed using the Sequenom iPLEX assay sequencing technique. Overall survival (OS) was analyzed between SNPs using the univariable Cox proportional hazard model. The Cancer Genome Atlas (TCGA-GBM) cohort of 585 patients were analyzed for IDH1, IDH2, and EGFR alterations with OS, disease-free survival (DFS), and progression-free survival (PFS). Single-cell RNA analysis was performed on the following scRNA datasets from the Gene Expression Omnibus (GEO): GSE163108 (n=25,013 cells), and GSE102130 (n=3,321 cells) . Results: Our study revealed a significant difference in genotype frequency between GBM cases and controls for IDH1 rs121913500C&amp;gt;T, and EGFR rs1468727C&amp;gt;T SNPs. Univariable Cox model showed that the G/G genotype of rs231677G&amp;gt;A (EGFR) SNP was associated with better OS in the codominant model (HR: 0.24, 95% CI: 0.08-0.73, p-value=0.012), and rs11540478G&amp;gt;A (IDH2) SNP (HR: 0.02, 95% CI: 0.0-0.29, p-value=0.005) showing significantly better prognosis compared to the A/G genotype. In the TCGA validation cohort, the altered group of IDH1 were significantly associated with better OS (HR: 0.35, 95% CI: 0.24-0.50, p-value&amp;lt;0.001), DFS (HR: 0.34, 95% CI: 0.23-0.50, p-value&amp;lt;0.001) , and PFS (HR: 0.43, 95% CI: 0.30-0.62, p-value&amp;lt;0.001). The scRNA analysis showed predominant expression of IDH1, IDH2, and EGFR by malignant cells, oligodendrocyte precursor cells, and macrophages. Conclusion: Our investigation into the genetic landscape of GBM within the Jordanian population suggest that specific genetic variants, particularly in IDH1 genes and EGFR, may serve as diagnostic and prognostic biomarkers for GBM. Additionally, IDH1 alterations were associated with better prognostic outcomes. Single-cell RNA analysis further illuminates the predominant expression of IDH1, IDH2, and EGFR by malignant cells which can be used as potential avenues for targeted therapies based on genetic profiles. Citation Format: Ayah N. Al-Bzour, Sohaib M. Al-Khatib, Mohammad N. Almajali, Tariq A. Jarrad. Genetic variants of IDH and EGFR as diagnostic and prognostic biomarkers in glioblastoma multiforme: A case-control study in the Jordanian Arab population [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 5585.

Machine Learning-Based Prediction of Glioma IDH Gene Mutation Status Using Physio-Metabolic MRI of Oxygen Metabolism and Neovascularization (A Bicenter Study).

The mutational status of the isocitrate dehydrogenase (IDH) gene plays a key role in the treatment of glioma patients because it is known to affect energy metabolism pathways relevant to glioma. Physio-metabolic magnetic resonance imaging (MRI) enables the non-invasive analysis of oxygen metabolism and tissue hypoxia as well as associated neovascularization and microvascular architecture. However, evaluating such complex neuroimaging data requires computational support. Traditional machine learning algorithms and simple deep learning models were trained with radiomic features from clinical MRI (cMRI) or physio-metabolic MRI data. A total of 215 patients (first center: 166 participants + 16 participants for independent internal testing of the algorithms versus second site: 33 participants for independent external testing) were enrolled using two different physio-metabolic MRI protocols. The algorithms trained with physio-metabolic data demonstrated the best classification performance in independent internal testing: precision, 91.7%; accuracy, 87.5%; area under the receiver operating curve (AUROC), 0.979. In external testing, traditional machine learning models trained with cMRI data exhibited the best IDH classification results: precision, 84.9%; accuracy, 81.8%; and AUROC, 0.879. The poor performance for the physio-metabolic MRI approach appears to be explainable by site-dependent differences in data acquisition methodologies. The physio-metabolic MRI approach potentially supports reliable classification of IDH gene status in the presurgical stage of glioma patients. However, non-standardized protocols limit the level of evidence and underlie the need for a reproducible framework of data acquisition techniques.

Multi-scale feature fusion for prediction of IDH1 mutations in glioma histopathological images

Background and objectiveMutations in isocitrate dehydrogenase 1 (IDH1) play a crucial role in the prognosis, diagnosis, and treatment of gliomas. However, current methods for determining its mutation status, such as immunohistochemistry and gene sequencing, are difficult to implement widely in routine clinical diagnosis. Recent studies have shown that using deep learning methods based on pathological images of glioma can predict the mutation status of the IDH1 gene. However, our research focuses on utilizing multi-scale information in pathological images to improve the accuracy of predicting IDH1 gene mutations, thereby providing an accurate and cost-effective prediction method for routine clinical diagnosis. MethodsIn this paper, we propose a multi-scale fusion gene identification network (MultiGeneNet). The network first uses two feature extractors to obtain feature maps at different scale images, and then by employing a bilinear pooling layer based on Hadamard product to realize the fusion of multi-scale features. Through fully exploiting the complementarity among features at different scales, we are able to obtain a more comprehensive and rich representation of multi-scale features. ResultsBased on the Hematoxylin and Eosin stained pathological section dataset of 296 patients, our method achieved an accuracy of 83.575 % and an AUC of 0.886, thus significantly outperforming other single-scale methods. ConclusionsOur method can be deployed in medical aid systems at very low cost, serving as a diagnostic or prognostic tool for glioma patients in medically underserved areas.

Molecular detection and characterization of Coxiella burnetii in aborted samples of livestock in China

Coxiella burnetii is the causative agent of zoonotic Q fever. Animals are the natural reservoirs of C. burnetii, and domestic livestock represent the major sources of human infection. C. burnetii infection in pregnant females may causes abortion during late pregnancy, whereby massive shedding of C. burnetii with abortion products becomes aerosolized and persists in the environment. Therefore, monitoring and surveillance of this infection in livestock is important for the prevention of the C. burnetii transmission. Previous serological surveys have shown that C. burnetii infection is endemic in livestock in China. However, few data are available on the diagnosis of C. burnetii as a cause of abortion by molecular methods in livestock. To get a better understanding of the impact of C. burnetii infection on domestic livestock in China, a real-time PCR investigation was carried out on collected samples from different domestic livestock suffering abortion during 2021–2023. A total of 338 samples collected from eight herds of five livestock species were elected. The results showed that 223 (66 %) of the collected samples were positive for C. burnetii DNA using real-time PCR. For the aborted samples, 82 % (128/15) of sheep, 81 % (34/42) of goats, 44 % (15/34) of cattle, 69 % (18/26) of camels, and 50 % (17/34) of donkeys were positive for C. burnetii. Besides, 44 % (8/18) and 4 % (1/25) of asymptomatic individuals of sheep and donkey were also positive for C. burnetii. In addition, the positive samples were further confirmed by amplification and sequencing of the C. burnetii-specific isocitrate dehydrogenase (icd) gene. Phylogenetic analysis based on specific gene fragments of icd genes revealed that the obtained sequences in this study were clustered into two different groups associated with different origin of hosts and geographic regions. This is the first report confirming that C. burnetii exists in aborted samples of sheep, goats, cattle, donkeys and camels in China. Further studies are needed to fully elucidate the epidemiology of this pathogen in livestock as well as the potential risks to public health.

Enhancing predictability of IDH mutation status in glioma patients at initial diagnosis: a comparative analysis of radiomics from MRI, [18F]FET PET, and TSPO PET.

According to the World Health Organization classification for tumors of the central nervous system, mutation status of the isocitrate dehydrogenase (IDH) genes has become a major diagnostic discriminator for gliomas. Therefore, imaging-based prediction of IDH mutation status is of high interest for individual patient management. We compared and evaluated the diagnostic value of radiomics derived from dual positron emission tomography (PET) and magnetic resonance imaging (MRI) data to predict the IDH mutation status non-invasively. Eighty-seven glioma patients at initial diagnosis who underwent PET targeting the translocator protein (TSPO) using [18F]GE-180, dynamic amino acid PET using [18F]FET, and T1-/T2-weighted MRI scans were examined. In addition to calculating tumor-to-background ratio (TBR) images for all modalities, parametric images quantifying dynamic [18F]FET PET information were generated. Radiomic features were extracted from TBR and parametric images. The area under the receiver operating characteristic curve (AUC) was employed to assess the performance of logistic regression (LR) classifiers. To report robust estimates, nested cross-validation with five folds and 50 repeats was applied. TBRGE-180 features extracted from TSPO-positive volumes had the highest predictive power among TBR images (AUC 0.88, with age as co-factor 0.94). Dynamic [18F]FET PET reached a similarly high performance (0.94, with age 0.96). The highest LR coefficients in multimodal analyses included TBRGE-180 features, parameters from kinetic and early static [18F]FET PET images, age, and the features from TBRT2 images such as the kurtosis (0.97). The findings suggest that incorporating TBRGE-180 features along with kinetic information from dynamic [18F]FET PET, kurtosis from TBRT2, and age can yield very high predictability of IDH mutation status, thus potentially improving early patient management.

Distinguishing IDH mutation status in gliomas using FTIR-ATR spectra of peripheral blood plasma indicating clear traces of protein amyloid aggregation

BackgroundGlioma is a primary brain tumor and the assessment of its molecular profile in a minimally invasive manner is important in determining treatment strategies. Among the molecular abnormalities of gliomas, mutations in the isocitrate dehydrogenase (IDH) gene are strong predictors of treatment sensitivity and prognosis. In this study, we attempted to non-invasively diagnose glioma development and the presence of IDH mutations using multivariate analysis of the plasma mid-infrared absorption spectra for a comprehensive and sensitive view of changes in blood components associated with the disease and genetic mutations. These component changes are discussed in terms of absorption wavenumbers that contribute to differentiation.MethodsPlasma samples were collected at our institutes from 84 patients with glioma (13 oligodendrogliomas, 17 IDH-mutant astrocytoma, 7 IDH wild-type diffuse glioma, and 47 glioblastomas) before treatment initiation and 72 healthy participants. FTIR-ATR spectra were obtained for each plasma sample, and PLS discriminant analysis was performed using the absorbance of each wavenumber in the fingerprint region of biomolecules as the explanatory variable. This data was used to distinguish patients with glioma from healthy participants and diagnose the presence of IDH mutations.ResultsThe derived classification algorithm distinguished the patients with glioma from healthy participants with 83% accuracy (area under the curve (AUC) in receiver operating characteristic (ROC) = 0.908) and diagnosed the presence of IDH mutation with 75% accuracy (AUC = 0.752 in ROC) in cross-validation using 30% of the total test data. The characteristic changes in the absorption spectra suggest an increase in the ratio of β-sheet structures in the conformational composition of blood proteins of patients with glioma. Furthermore, these changes were more pronounced in patients with IDH-mutant gliomas.ConclusionsThe plasma infrared absorption spectra could be used to diagnose gliomas and the presence of IDH mutations in gliomas with a high degree of accuracy. The spectral shape of the protein absorption band showed that the ratio of β-sheet structures in blood proteins was significantly higher in patients with glioma than in healthy participants, and protein aggregation was a distinct feature in patients with glioma with IDH mutations.

Computational Pathology for Prediction of Isocitrate Dehydrogenase Gene Mutation from Whole Slide Images in Adult Patients with Diffuse Glioma

Isocitrate dehydrogenase gene (IDH) mutation is one of the most important molecular markers of glioma. Accurate detection of IDH status is a crucial step for integrated diagnosis of adult-type diffuse gliomas. Herein, a clustering-based hybrid of a convolutional neural network and a vision transformer deep learning model was developed to detect IDH mutation status from annotation-free hematoxylin and eosin-stained whole slide pathologic images of 2275 adult patients with diffuse gliomas. For comparison, a pure convolutional neural network, a pure vision transformer, and a classic multiple-instance learning model were also assessed. The hybrid model achieved an area under the receiver operating characteristic curve of 0.973 in the validation set and 0.953 in the external test set, outperforming the other models. The hybrid model's ability in IDH detection between difficult subgroups with different IDH status but shared histologic features, achieving areas under the receiver operating characteristic curve ranging from 0.850 to 0.985 in validation and test sets. These data suggest that the proposed hybrid model has a potential to be used as a computational pathology tool for preliminary rapid detection of IDH mutation from whole slide images in adult patients with diffuse gliomas.

Gene expression changes of isocitrate dehydrogenase 1 and isocitrate dehydrogenase 2 affect carcinogenesis and survival probability

Isocitrate dehydrogenase (IDH) is an essential metabolic enzyme in the regulation of cellular metabolism. IDH gene encodes three protein isoforms, IDH1, IDH2, and IDH3, and the expression level of isoforms is altered in human cancer types. Examining the gene expression level of IDH is a therapeutic advantage that could help find a new target to use in cancer metabolism. The present study aimed to explore the gene expression level of IDH1 and IDH2 isoforms in the ten common human cancers using bioinformatic tools. In addition, the effect of gene expression changes on IDH1 and IDH2 on carcinogenesis and survival probability was examined in publicly available data deposited in the TCGA database. The results showed that the expression of IDH isoforms showed tissue-specific differences. IDH1 expression increased in esophageal and lung squamous cell carcinoma and lung and stomach adenocarcinoma tumors. Bladder urothelial, breast urothelial, and lung squamous cell carcinoma, colon, and lung adenocarcinoma displayed a significant upregulation of IDH2 expression. There was a direct relationship between the expression of IDH isoforms and the progression of various cancer types. High IDH1 expression led to decreased survival probability in esophageal carcinoma, lung, and stomach adenocarcinoma. Elevated IDH2 expression level led to decreased survival probability in bladder urothelial, breast urothelial, and lung squamous cell carcinoma and colon adenocarcinoma. In conclusion, all data showed that IDH1 could be a biomarker for esophageal carcinoma, lung and stomach adenocarcinoma, and IDH2 for bladder urothelial, breast urothelial, and lung squamous cell carcinoma, and colon adenocarcinoma.

Isocitrate Dehydrogenase and Alpha Thalassemia/Mental Retardation, X-linked Mutation Status in Human Gliomas at a Tertiary Care Hospital in Southern India: A Cross-sectional Study

Introduction: The molecular subtyping of human gliomas in the current World Health Organisation (WHO) 2021 classification highlights the diagnostic and prognostic significance of neoplastic entities. This subsequently contributes to a better understanding of immunohistochemistry markers in various glioma patients. Aim: The study aimed to determine the Isocitrate Dehydrogenase (IDH1) gene mutation and Alpha Thalessemia/Mental retardation X-linked (ATRX) mutation in gliomas through immunohistochemistry and clinically categorise them into various subgroups. Materials and Methods: The present cross-sectional study was conducted in the Department of Pathology and Neurosurgery on 50 glioma samples collected from patients who underwent surgery at ESIC Medical College and Super Speciality Hospital in Hyderabad, Telangana, India from June 2018 to June 2023. Histopathological evaluation and Immunohistochemistry (IHC) study for IDH1 and Alpha Thalessemia/Mental retardation X-linked were performed on all patients. Clinical variables such as age, gender, duration of symptoms, and clinical presentation were collected from medical records and tabulated. Results: Total 50 cases of glioma were studied. The expression of IDH1 wild type was observed in 30 (60%) cases, which was more common than IDH1 mutation observed in 20 (40%) cases. The mean age in the study was 41.9 years, with a majority of male patients 33 (66%). IDH1 mutation was commonly observed in diffuse fibrillary astrocytomas (34%) followed by 12% of cases in anaplastic Astrocytomas. Glioblastoma was the most common histopathological diagnosis in 40% of cases, but the observed IDH mutation was least frequent in glioblastomas. Out of the 20 glioblastoma cases, only one tested positive for IDH mutation. In contrast, ATRX loss was predominantly seen in glioblastomas, with three out of the five positive cases. IDH1 mutation was more common in adults than in children, and a female preponderance (60%) was noted. ATRX mutation was observed in only 10% of cases. Conclusion: The IDH1 and ATRX are reliable prognostic markers, and their analysis through immunohistochemistry provides a practical and dependable method for categorising gliomas compared to molecular analysis, thus assisting clinicians in achieving promising treatment outcomes.

Development of a Closed System qPCR Assay to Detect Mutations in IDH1/IDH2 in Patients with Acute Myeloid Leukemia (AML)

Background: Acute myeloid leukemia (AML) is a heterogenous disease characterized by clonal proliferation of poorly differentiated myeloid cells and is associated with mutations in several genes including the isocitrate dehydrogenase (IDH) genes IDH1 and IDH2. It has been reported that 20% of AML patients carry IDH1/IDH2 mutations (IDH1 - 8%, IDH2 - 12%) which are strongly associated with disease progression and relapse. Additionally, several IDH1/IDH2 inhibitors such as ivosidenib and enasidenib have been approved by the FDA for treatment of AML patients with IDH1 and IDH2 mutations respectively. Therefore, identification of these single nucleotide polymorphism (SNP) mutations in IDH1/IDH2 can help in disease classification and selection of effective targeted inhibitors. Objectives: Our goal is to develop a rapid and user-friendly cartridge-based qPCR assay that can detect 7 IDH1 and 10 IDH2 mutations in human genomic DNA from EDTA whole blood lysate. Using a single cartridge, any of the four codons (IDH1 R132/R100 or IDH2 R140/R172) will be called out when a mutation is detected. This reporting style is more than sufficient in deciding a course of treatment as current therapies only differ between a mutation in either IDH1 or IDH2. Methods: Six levels of custom generated plasmids (64%, 16%, 4%, 1%, 0.25%, and 0.0625%) for the four most prevalent IDH1/IDH2 mutations were spiked-into EDTA whole blood lysate and tested with prototype IDH1/IDH2 mutation assay. Standard curves of Ct vs. log % mutation were generated for R132C, R132H, R140Q, and R172K. Custom generated plasmids were also made for the remaining 13 mutations and have been tested around the LoD (1%). In addition to plasmids, human cell line DNA with 14 of the 17 mutations were also spiked into EDTA whole blood lysate and tested around the LoD (1%). A standard curve of Ct vs Log % mutation was generated with R132H human cell line DNA. The remaining 3 mutations were not commercially available as cell line DNA. Specificity of the IDH1/IDH2 mutation assay was assessed by testing EDTA whole blood lysate from 20 individual donors in quadruplicate. Results: The prototype IDH1/IDH2 assay demonstrated a dynamic range from 64% to 0.0625% with a limit of detection at 1% for all the mutations that were tested. Figure 1 shows the dynamic range curves for the most prevalent mutations: IDH1 R132C &amp; R132H, and IDH2 R140Q &amp; R172K. These dynamic range curves include data points for both plasmid DNA (pDNA in red) and human cell line DNA (gDNA in blue) to show equivalency between the two test materials. The performance of the remaining 13 mutations in plasmid DNA perform similarly in their respective codons with no more than 2Ct difference at 1% levels. The remaining 10 human cell line DNA mutations perform similarly to plasmid DNA. Conclusions: We have prototyped 18-plex assay designed to detect 7 IDH1 and 10 IDH2 mutations and call out its corresponding codon in EDTA whole blood samples using a single cartridge at an estimated LoD of 1%.

Measurable Residual IDH1 before Allogeneic Transplant for Acute Myeloid Leukemia

Introduction: Detection of measurable residual disease (MRD) prior to allogeneic hematopoietic cell transplant (alloHCT) in patients with acute myeloid leukemia (AML) in remission is associated with increased relapse and inferior survival after transplant. We recently reported that next-generation sequencing (NGS) detection of mutated NPM1 or FLT3-ITD in first complete remission (CR1) blood prior to alloHCT is strongly associated with increased relapse and death (PMID: 36881031). However, the prognostic implications of detecting persistence of other common AML-associated mutations at this treatment landmark remain incompletely defined. Around 20% of patients diagnosed with AML have variants in isocitrate dehydrogenase ( IDH) genes (~7% for IDH1) and clinical outcomes are known to differ due to co-occurrence of other mutations, IDH subtypes, treatment strategies, and patient factors. Studies have examined the relationship between residual IDH1 variants ( IDH1m) in CR and subsequent clinical outcomes, but definitive standardized evidence to inform decision-making for the clinical utility of IDH1m as a target for AML MRD testing was not previously available. Methods: Adult patients undergoing alloHCT for IDH1 mutated AML in CR1 at CIBMTR sites in the USA between 2013-2019 were eligible for the study if remission blood sample collected within 100 days before alloHCT and outcome data were available. Ultrasensitive error-corrected NGS (NGS-MRD) targeting IDH1, NPM1, and FLT3 genes was performed on DNA from pre-conditioning blood to identify residual variants. Detected IDH1m were validated by digital droplet PCR (ddPCR). The day of transplant was considered as day 0. Median follow-up time was calculated for censored patients. Overall survival (OS) was estimated using Kaplan-Meier (log-rank tests) and Cox proportional hazards models (forward selection); cumulative incidence of relapse was examined using Fine-Gray regression models with non-relapse mortality as a competing risk. Results: A total of 148 patients were included in the study, with a median follow-up time of 24 months. Relapse was observed in 37 (25%) patients, with the majority occurring within 1 year after alloHCT (n = 28, 76%). Pre-transplant flow cytometry results were reported by the transplant centers for 97% of patients (n = 144), but no statistically significant differences in clinical outcomes were observed between the positive and negative groups (OS: p = 0.3; relapse: p = 0.07). 53 patients (36%) tested positive for IDH1m persistence in CR1, with a 100% validation rate by ddPCR for variants with an orthogonal assay available. Logistic regression indicated that IDH1m persistence in remission was more likely to occur in patients older than 40 years (OR: 1.02 with every 1-year increase after 40, p = 0.04). Clinical outcomes showed no statistically significant difference between the pre-alloHCT IDH1m positive and negative groups (Figure 1A), and this remained true after further subgroup analysis by age. The variant allele fraction (VAF) of the residual IDH1m ranged from 0.09% to 48.5% (median: 1.5%), and no differences in clinical outcomes were observed when stratifying by high (≥2.5%) or low VAF (&amp;lt;2.5%). Among patients with co-mutated NPM1 and/or FLT3-ITD at baseline (n=69), those with residual mutated NPM1 and/or FLT3-ITD in pre-transplant remission had significantly higher rates of relapse compared to those with residual IDH1m only or NGS-negative groups (p = 0.01, Figure 1B). The cohort excluding patients with co-mutated NPM1 and/or FLT3-ITD did not show any significant clinical outcome differences based on IDH1m persistence. Conditioning intensity did not show an association with clinical outcomes, and multivariable analysis for overall survival and relapse did not identify residual IDH1m as an important marker. Conclusion: Detection of persistent IDH1 variants in the blood of adult patients with AML in CR1 prior to first alloHCT is common, but not associated with increased relapse or death after transplant compared with those testing negative. For those patients with IDH1 mutated AML co-mutated with either NPM1 and/or FLT3-ITD, detection of persistent NPM1 and/or FLT3-ITD was associated with higher rates of relapse. These findings, from the largest study to date, do not support the detection of isolated IDH1 variants in CR1 blood prior to alloHCT as evidence of AML MRD or increased post-transplant relapse risk.

Despite High Rates of Remission, Treatment of IDH-Mutant AML with Hypomethylating Agents and Venetoclax Is Associated with Frequent Treatment Delays, Modifications, and Transfusions

Introduction: 25-30% of adult patients with AML have mutations in the isocitrate dehydrogenase (IDH) genes, IDH1 or IDH2. Hypomethylating agents (HMA) and venetoclax (Ven) is a widely used combination in induction-ineligible patients with IDH mutations. A subset analysis of VIALE-A data showed composite complete remission or complete remission with incomplete hematologic recovery (CR/CRi) rate of 79% and median overall survival (mOS) of 24.5 months with frontline azacitidine and Ven. IDH1-mutant and IDH2-mutant patients had CR/CRi rates of 66.7% and 86.0%, respectively. IDH1-mutant patients had mOS of 15.2 months and IDH2-mutant patients did not reach mOS. We report a single-center retrospective analysis of HMA/Ven in patients with IDH mutations. Methods: This single-center retrospective study examined all patients with IDH mutations who received HMA/Ven from January 1, 2018 to June 30, 2023 at Memorial Sloan Kettering Cancer Center and summarizes their characteristics and outcomes. Demographics, adverse events, treatment course, and laboratory and transfusion data were retrospectively reviewed with institutional IRB approval. Results: Ninety-four patients, 50 with newly diagnosed (ND) AML and 44 with relapsed/refractory (R/R) AML, were identified (Table 1). 32% (n=16) of ND patients and 41% (n=18) of R/R patients had IDH1 mutations and 68% (n=34) of ND patients and 59% (n=26) of R/R patients had IDH2 mutations. With median follow-up of 21.9 months, mOS was 29.2 months (95% CI 17.9, NA) for ND patients and 17.1 months (95% CI 12.1, 34.2) for R/R patients (Figure 1). The CR/CRi rate was 76% (n=38; 30% CR, n=15; 46% CRi, n=23) for ND patients and 52% (n=23; 32% CR, n=14; 20% CRi, n=9) for R/R patients. Patients received median of 3 cycles of HMA/Ven (range 1, 22) and experienced frequent treatment modifications and delays. Of 356 total cycles, 62% (n=218) were modified to have fewer than 28 days of venetoclax, 7 days of azacitidine, or 5 days of decitabine. In addition, 296 cycle holds or delays of at least one week occurred. 66.2% (n=196) of holds or delays were due to cytopenia and 11.5% (n=34) were due to infection. 77% (n=72) of patients had Common Terminology Criteria for Adverse Events (CTCAE) grade 3 pancytopenia and 47% (n=44) had febrile neutropenia. Through 356 cycles spanning 21,386 patient-days, 5,651 complete blood counts (CBCs, mean 15.9 per cycle), 986 red blood cell transfusions, (RBC, mean 2.8 per cycle) and 1,018 platelet transfusions (PLT, mean 2.9 per cycle) were recorded at our center. Additional CBCs or transfusions performed externally were not captured. After CR/CRi, dose adjustments, cycle holds or delays, and cytopenias remained frequent. The 63 patients that achieved CR/CRi underwent 198 cycles, 71% (n=141) of which were modified as above. There were 209 holds or delays (65%, n=136 for cytopenias, 10%, n=21 for infection). Median time between cycles was 7 weeks. Cycles given after CR/CRi frequently resulted in grade 3 cytopenias by CTCAE (neutropenia: 82%, n=163; anemia: 15%, n=29; thrombocytopenia: 37%, n=74). Through 198 cycles spanning 13,463 patient-days, 2,426 CBCs (mean 12.3 per cycle), 141 RBC transfusions, (mean 0.7 per cycle) and 236 PLT transfusions (mean 1.2 per cycle) were performed. At last follow-up, 28% (n=14) of ND AML patients continued HMA/Ven, whereas 28% (n=14) had proceeded to allogeneic stem cell transplantation (alloSCT), 28% (n=14) were relapsed or refractory to HMA/Ven, and 12% (n=6) were deceased. For R/R AML patients, 20% (n=9) continued HMA/Ven but 27% (n=12) had proceeded to alloSCT, 34% (n=15) were relapsed or refractory, and 14% (n=6) were deceased. Of the 68 patients who were no longer receiving HMA/Ven at end of follow-up, only 23.5% (n=16) of patients received an IDH-inhibitor in their next line of therapy, the rest primarily transitioning to alloSCT (38.2%, n=26), chemotherapy (8.8%, n=6), or supportive measures (20.6%, n=14). Conclusion: In a single-center retrospective setting, HMA/Ven is efficacious in achieving CR/CRi in ND and R/R IDH-mutant AML. However, its use, even in CR/CRi, is associated with significant cytopenias and infections that necessitate indefinite and frequent treatment modification, laboratory utilization, and transfusions. A strategy that incorporates HMA/Ven followed by non-myelosuppressive targeted therapy with IDH inhibition as maintenance should be explored to minimize these toxicities.

Multi-Modal Learning for Predicting the Genotype of Glioma.

The isocitrate dehydrogenase (IDH) gene mutation is an essential biomarker for the diagnosis and prognosis of glioma. It is promising to better predict glioma genotype by integrating focal tumor image and geometric features with brain network features derived from MRI. Convolutional neural networks show reasonable performance in predicting IDH mutation, which, however, cannot learn from non-Euclidean data, e.g., geometric and network data. In this study, we propose a multi-modal learning framework using three separate encoders to extract features of focal tumor image, tumor geometrics and global brain networks. To mitigate the limited availability of diffusion MRI, we develop a self-supervised approach to generate brain networks from anatomical multi-sequence MRI. Moreover, to extract tumor-related features from the brain network, we design a hierarchical attention module for the brain network encoder. Further, we design a bi-level multi-modal contrastive loss to align the multi-modal features and tackle the domain gap at the focal tumor and global brain. Finally, we propose a weighted population graph to integrate the multi-modal features for genotype prediction. Experimental results on the testing set show that the proposed model outperforms the baseline deep learning models. The ablation experiments validate the performance of different components of the framework. The visualized interpretation corresponds to clinical knowledge with further validation. In conclusion, the proposed learning framework provides a novel approach for predicting the genotype of glioma.

Phospholipid metabolic adaptation promotes survival of IDH2 mutant acute myeloid leukemia cells.

Genetic mutations in the isocitrate dehydrogenase (IDH) gene that result in a pathological enzymatic activity to produce oncometabolite have been detected in acute myeloid leukemia (AML) patients. While specific inhibitors that target mutant IDH enzymes and normalize intracellular oncometabolite level have been developed, refractoriness and resistance has been reported. Since acquisition of pathological enzymatic activity is accompanied by the abrogation of the crucial WT IDH enzymatic activity in IDH mutant cells, aberrant metabolism in IDH mutant cells can potentially persist even after the normalization of intracellular oncometabolite level. Comparisons of isogenic AML cell lines with and without IDH2 gene mutations revealed two mutually exclusive signalings for growth advantage of IDH2 mutant cells, STAT phosphorylation associated with intracellular oncometabolite level and phospholipid metabolic adaptation. The latter came to light after the oncometabolite normalization and increased the resistance of IDH2 mutant cells to arachidonic acid-mediated apoptosis. The release of this metabolic adaptation by FDA-approved anti-inflammatory drugs targeting the metabolism of arachidonic acid could sensitize IDH2 mutant cells to apoptosis, resulting in their eradication invitro and invivo. Our findings will contribute to the development of alternative therapeutic options for IDH2 mutant AML patients who do not tolerate currently available therapies.

Tumor heterogeneity and tumor-microglia interactions in primary and recurrent IDH1-mutant gliomas

The isocitrate dehydrogenase (IDH) gene is recurrently mutated in adult diffuse gliomas. IDH-mutant gliomas are categorized into oligodendrogliomas and astrocytomas, each with unique pathological features. Here, we use single-nucleus RNA and ATAC sequencing to compare the molecular heterogeneity of these glioma subtypes. In addition to astrocyte-like, oligodendrocyte progenitor-like, and cycling tumor subpopulations, a tumor population enriched for ribosomal genes and translation elongation factors is primarily present in oligodendrogliomas. Longitudinal analysis of astrocytomas indicates that the proportion of tumor subpopulations remains stable in recurrent tumors. Analysis of tumor-associated microglia/macrophages (TAMs) reveals significant differences between oligodendrogliomas, with astrocytomas harboring inflammatory TAMs expressing phosphorylated STAT1, as confirmed by immunohistochemistry. Furthermore, inferred receptor-ligand interactions between tumor subpopulations and TAMs may contribute to TAM state diversity. Overall, our study sheds light on distinct tumor populations, TAM heterogeneity, TAM-tumor interactions in IDH-mutant glioma subtypes, and the relative stability of tumor subpopulations in recurrent astrocytomas.