Gene expression profile of T cells from Isocitrate Dehydrogenase (IDH) stratified human gliomas at single cell level
Ontology highlight
ABSTRACT: The brain tumor immune microenvironment (TIME) continuously evolves during glioma progression, but only a limited view of a highly complex glioma associated immune contexture across isocitrate dehydrogenase mutation (IDH) classified gliomas is known. Herein, we present an unprecedentedly comprehensive view of T cells from brain TIME at single cell resolution, which served as part of our pan-cancer T cell atlas analysis.
Project description:The brain tumor immune microenvironment (TIME) continuously evolves during glioma progression, but only a limited view of a highly complex glioma associated immune contexture across isocitrate dehydrogenase mutation (IDH) classified gliomas is known. Herein, we present an unprecedentedly comprehensive view of myeloid and lymphoid cell type diversity with our m-RNA sequencing interrogation.
Project description:The brain tumor immune microenvironment (TIME) continuously evolves during glioma progression, but only a limited view of a highly complex glioma associated immune contexture across isocitrate dehydrogenase mutation (IDH) classified gliomas is known. Herein, we present an unprecedentedly comprehensive view of myeloid and lymphoid cell type diversity with our single cell RNA sequencing interrogation.
Project description:DJ-1 is one of the causative genes for early onset familiar Parkinson's disease (PD) and is also considered to influence the pathogenesis of sporadic PD. DJ-1 has various physiological functions which converge on controlling intracellular reactive oxygen species (ROS) levels. In RNA-sequencing analyses searching for novel anti-oxidant genes downstream of DJ-1, a gene encoding NADP+-dependent isocitrate dehydrogenase (IDH), which converts isocitrate into ?-ketoglutarate, was detected. Loss of IDH induced hyper-sensitivity to oxidative stress accompanying age-dependent mitochondrial defects and dopaminergic (DA) neuron degeneration in Drosophila, indicating its critical roles in maintaining mitochondrial integrity and DA neuron survival. Further genetic analysis suggested that DJ-1 controls IDH gene expression through nuclear factor-E2-related factor2 (Nrf2). Using Drosophila and mammalian DA models, we found that IDH suppresses intracellular and mitochondrial ROS level and subsequent DA neuron loss downstream of DJ-1. Consistently, trimethyl isocitrate (TIC), a cell permeable isocitrate, protected mammalian DJ-1 null DA cells from oxidative stress in an IDH-dependent manner. These results suggest that isocitrate and its derivatives are novel treatments for PD associated with DJ-1 dysfunction.
Project description:BackgroundThere is considerable interest in defining the metabolic abnormalities of IDH mutant tumors to exploit for therapy. While most studies have attempted to discern function by using cell lines transduced with exogenous IDH mutant enzyme, in this study, we perform unbiased metabolomics to discover metabolic differences between a cohort of patient-derived IDH1 mutant and IDH wildtype gliomaspheres.MethodsUsing both our own microarray and the TCGA datasets, we performed KEGG analysis to define pathways differentially enriched in IDH1 mutant and IDH wildtype cells and tumors. Liquid chromatography coupled to mass spectrometry analysis with labeled glucose and deoxycytidine tracers was used to determine differences in overall cellular metabolism and nucleotide synthesis. Radiation-induced DNA damage and repair capacity was assessed using a comet assay. Differences between endogenous IDH1 mutant metabolism and that of IDH wildtype cells transduced with the IDH1 (R132H) mutation were also investigated.ResultsOur KEGG analysis revealed that IDH wildtype cells were enriched for pathways involved in de novo nucleotide synthesis, while IDH1 mutant cells were enriched for pathways involved in DNA repair. LC-MS analysis with fully labeled 13C-glucose revealed distinct labeling patterns between IDH1 mutant and wildtype cells. Additional LC-MS tracing experiments confirmed increased de novo nucleotide synthesis in IDH wildtype cells relative to IDH1 mutant cells. Endogenous IDH1 mutant cultures incurred less DNA damage than IDH wildtype cultures and sustained better overall growth following X-ray radiation. Overexpression of mutant IDH1 in a wildtype line did not reproduce the range of metabolic differences observed in lines expressing endogenous mutations, but resulted in depletion of glutamine and TCA cycle intermediates, an increase in DNA damage following radiation, and a rise in intracellular ROS.ConclusionsThese results demonstrate that IDH1 mutant and IDH wildtype cells are easily distinguishable metabolically by analyzing expression profiles and glucose consumption. Our results also highlight important differences in nucleotide synthesis utilization and DNA repair capacity that could be exploited for therapy. Altogether, this study demonstrates that IDH1 mutant gliomas are a distinct subclass of glioma with a less malignant, but also therapy-resistant, metabolic profile that will likely require distinct modes of therapy.
Project description:Mutations in isocitrate dehydrogenase genes IDH1 and IDH2 are frequently found in diffuse and anaplastic astrocytic and oligodendroglial tumours as well as in secondary glioblastomas. As IDH is a very important prognostic, diagnostic and therapeutic biomarker for glioma, it is of paramount importance to determine its mutational status. The haematoxylin and eosin (H&E) staining is a valuable tool in precision oncology as it guides histopathology-based diagnosis and proceeding patient's treatment. However, H&E staining alone does not determine the IDH mutational status of a tumour. Deep learning methods applied to MRI data have been demonstrated to be a useful tool in IDH status prediction, however the effectiveness of deep learning on H&E slides in the clinical setting has not been investigated so far. Furthermore, the performance of deep learning methods in medical imaging has been practically limited by small sample sizes currently available. Here we propose a data augmentation method based on the Generative Adversarial Networks (GAN) deep learning methodology, to improve the prediction performance of IDH mutational status using H&E slides. The H&E slides were acquired from 266 grade II-IV glioma patients from a mixture of public and private databases, including 130 IDH-wildtype and 136 IDH-mutant patients. A baseline deep learning model without data augmentation achieved an accuracy of 0.794 (AUC = 0.920). With GAN-based data augmentation, the accuracy of the IDH mutational status prediction was improved to 0.853 (AUC = 0.927) when the 3,000 GAN generated training samples were added to the original training set (24,000 samples). By integrating also patients' age into the model, the accuracy improved further to 0.882 (AUC = 0.931). Our findings show that deep learning methodology, enhanced by GAN data augmentation, can support physicians in gliomas' IDH status prediction.
Project description:BackgroundConflicting data exist regarding the prognostic impact of the isocitrate dehydrogenase (IDH) mutation in intrahepatic cholangiocarcinoma (ICC), and limited data exist in patients with advanced-stage disease. Similarly, the clinical phenotype of patients with advanced IDH mutant (IDHm) ICC has not been characterized. In this study, we report the correlation of IDH mutation status with prognosis and clinicopathologic features in patients with advanced ICC.MethodsPatients with histologically confirmed advanced ICC who underwent tumor mutational profiling as a routine part of their care between 2009 and 2014 were evaluated. Clinical and pathological data were collected by retrospective chart review for patients with IDHm versus IDH wild-type (IDHwt) ICC. Pretreatment tumor volume was calculated on computed tomography or magnetic resonance imaging.ResultsOf the 104 patients with ICC who were evaluated, 30 (28.8%) had an IDH mutation (25.0% IDH1, 3.8% IDH2). The median overall survival did not differ significantly between IDHm and IDHwt patients (15.0 vs. 20.1 months, respectively; p = .17). The pretreatment serum carbohydrate antigen 19-9 (CA19-9) level in IDHm and IDHwt patients was 34.5 and 118.0 U/mL, respectively (p = .04). Age at diagnosis, sex, histologic grade, and pattern of metastasis did not differ significantly by IDH mutation status.ConclusionThe IDH mutation was not associated with prognosis in patients with advanced ICC. The clinical phenotypes of advanced IDHm and IDHwt ICC were similar, but patients with IDHm ICC had a lower median serum CA19-9 level at presentation.Implications for practicePrevious studies assessing the prognostic impact of the isocitrate dehydrogenase (IDH) gene mutation in intrahepatic cholangiocarcinoma (ICC) mainly focused on patients with early-stage disease who have undergone resection. These studies offer conflicting results. The target population for clinical trials of IDH inhibitors is patients with unresectable or metastatic disease, and the current study is the first to focus on the prognosis and clinical phenotype of this population and reports on the largest cohort of patients with advanced IDH mutant ICC to date. The finding that the IDH mutation lacks prognostic significance in advanced ICC is preliminary and needs to be confirmed prospectively in a larger study.