Spectroscopic imaging of D-2-hydroxyglutarate and other metabolites in pre-surgical patients with IDH-mutant lower-grade gliomas.

PURPOSE: Prognostically favorable IDH-mutant gliomas are known to produce oncometabolite D-2-hydroxyglutarate (2HG). In this study, we investigated metabolite-based features of patients with grade 2 and 3 glioma using 2HG-specific in vivo MR spectroscopy, to determine their relationship with image-guided tissue pathology and predictive role in progression-free survival (PFS). METHODS: Forty-five patients received pre-operative MRIs that included 3-D spectroscopy optimized for 2HG detection. Spectral data were reconstructed and quantified to compare metabolite levels according to molecular pathology (IDH1R132H, 1p/19q, and p53); glioma grade; histological subtype; and T2 lesion versus normal-appearing white matter (NAWM) ROIs. Levels of 2HG were correlated with other metabolites and pathological parameters (cellularity, MIB-1) from image-guided tissue samples using Pearson's correlation test. Metabolites predictive of PFS were evaluated with Cox proportional hazards models. RESULTS: Quantifiable levels of 2HG in 39/42 (93%) IDH+ and 1/3 (33%) IDH- patients indicated a 91.1% apparent detection accuracy. Myo-inositol/total choline (tCho) showed reduced values in astrocytic (1p/19q-wildtype), p53-mutant, and grade 3 (vs. 2) IDH-mutant gliomas (p < 0.05), all of which exhibited higher proportions of astrocytomas. Compared to NAWM, T2 lesions displayed elevated 2HG+ γ-aminobutyric acid (GABA)/total creatine (tCr) (p < 0.001); reduced glutamate/tCr (p < 0.001); increased myo-inositol/tCr (p < 0.001); and higher tCho/tCr (p < 0.001). Levels of 2HG at sampled tissue locations were significantly associated with tCho (R = 0.62; p = 0.002), total NAA (R = - 0.61; p = 0.002) and cellularity (R = 0.37; p = 0.04) but not MIB-1. Increasing levels of 2HG/tCr (p = 0.0007, HR 5.594) and thresholding (≥ 0.905, median value; p = 0.02) predicted adverse PFS. CONCLUSION: In vivo 2HG detection can reasonably be achieved on clinical scanners and increased levels may signal adverse PFS.

Relationship of In Vivo MR Parameters to Histopathological and Molecular Characteristics of Newly Diagnosed, Nonenhancing Lower-Grade Gliomas.

The goal of this research was to elucidate the relationship between WHO 2016 molecular classifications of newly diagnosed, nonenhancing lower grade gliomas (LrGG), tissue sample histopathology, and magnetic resonance (MR) parameters derived from diffusion, perfusion, and 1H spectroscopic imaging from the tissue sample locations and the entire tumor. A total of 135 patients were scanned prior to initial surgery, with tumor cellularity scores obtained from 88 image-guided tissue samples. MR parameters were obtained from corresponding sample locations, and histograms of normalized MR parameters within the T2 fluid-attenuated inversion recovery lesion were analyzed in order to evaluate differences between subgroups. For tissue samples, higher tumor scores were related to increased normalized apparent diffusion coefficient (nADC), lower fractional anisotropy (nFA), lower cerebral blood volume (nCBV), higher choline (nCho), and lower N-acetylaspartate (nNAA). Within the T2 lesion, higher tumor grade was associated with higher nADC, lower nFA, and higher Cho to NAA index. Pathological analysis confirmed that diffusion and metabolic parameters increased and perfusion decreased with tumor cellularity. This information can be used to select targets for tissue sampling and to aid in making decisions about treating residual disease.

Genomic analysis of the origins and evolution of multicentric diffuse lower-grade gliomas.

Background: Rare multicentric lower-grade gliomas (LGGs) represent a unique opportunity to study the heterogeneity among distinct tumor foci in a single patient and to infer their origins and parallel patterns of evolution. Methods: In this study, we integrate clinical features, histology, and immunohistochemistry for 4 patients with multicentric LGG, arising both synchronously and metachronously. For 3 patients we analyze the phylogeny of the lesions using exome sequencing, including one case with a total of 8 samples from the 2 lesions. Results: One patient was diagnosed with multicentric isocitrate dehydrogenase 1 (IDH1) mutated diffuse astrocytomas harboring distinct IDH1 mutations, R132H and R132C; the latter mutation has been associated with Li-Fraumeni syndrome, which was subsequently confirmed in the patient's germline DNA and shown in additional cases with The Cancer Genome Atlas data. In another patient, phylogenetic analysis of synchronously arising grade II and grade III diffuse astrocytomas demonstrated a single shared mutation, IDH1 R132H, and revealed convergent evolution via non-overlapping mutations in ATRX and TP53. In 2 cases, there was divergent evolution of IDH1-mutated and 1p/19q-codeleted oligodendroglioma and IDH1-mutated and 1p/19q-intact diffuse astrocytoma, occurring synchronously in one case and metachronously in a second. Conclusions: Each tumor in multicentric LGG cases may arise independently or may diverge very early in their development, presenting as genetically and histologically distinct tumors. Comprehensive sampling of these lesions can therefore significantly alter diagnosis and management. Additionally, somatic IDH1 R132C mutation in either multicentric or solitary LGG identifies unsuspected germline TP53 mutation, validating the limited number of published cases.

Clonal expansion and epigenetic reprogramming following deletion or amplification of mutant IDH1.

IDH1 mutation is the earliest genetic alteration in low-grade gliomas (LGGs), but its role in tumor recurrence is unclear. Mutant IDH1 drives overproduction of the oncometabolite d-2-hydroxyglutarate (2HG) and a CpG island (CGI) hypermethylation phenotype (G-CIMP). To investigate the role of mutant IDH1 at recurrence, we performed a longitudinal analysis of 50 IDH1 mutant LGGs. We discovered six cases with copy number alterations (CNAs) at the IDH1 locus at recurrence. Deletion or amplification of IDH1 was followed by clonal expansion and recurrence at a higher grade. Successful cultures derived from IDH1 mutant, but not IDH1 wild type, gliomas systematically deleted IDH1 in vitro and in vivo, further suggestive of selection against the heterozygous mutant state as tumors progress. Tumors and cultures with IDH1 CNA had decreased 2HG, maintenance of G-CIMP, and DNA methylation reprogramming outside CGI. Thus, while IDH1 mutation initiates gliomagenesis, in some patients mutant IDH1 and 2HG are not required for later clonal expansions.

Metabolic Profiling of IDH Mutation and Malignant Progression in Infiltrating Glioma.

Infiltrating low grade gliomas (LGGs) are heterogeneous in their behavior and the strategies used for clinical management are highly variable. A key factor in clinical decision-making is that patients with mutations in the isocitrate dehydrogenase 1 and 2 (IDH1/2) oncogenes are more likely to have a favorable outcome and be sensitive to treatment. Because of their relatively long overall median survival, more aggressive treatments are typically reserved for patients that have undergone malignant progression (MP) to an anaplastic glioma or secondary glioblastoma (GBM). In the current study, ex vivo metabolic profiles of image-guided tissue samples obtained from patients with newly diagnosed and recurrent LGG were investigated using proton high-resolution magic angle spinning spectroscopy (1H HR-MAS). Distinct spectral profiles were observed for lesions with IDH-mutated genotypes, between astrocytoma and oligodendroglioma histologies, as well as for tumors that had undergone MP. Levels of 2-hydroxyglutarate (2HG) were correlated with increased mitotic activity, axonal disruption, vascular neoplasia, and with several brain metabolites including the choline species, glutamate, glutathione, and GABA. The information obtained in this study may be used to develop strategies for in vivo characterization of infiltrative glioma, in order to improve disease stratification and to assist in monitoring response to therapy.

Quantitative multi-modal MR imaging as a non-invasive prognostic tool for patients with recurrent low-grade glioma.

Low-grade gliomas can vary widely in disease course and therefore patient outcome. While current characterization relies on both histological and molecular analysis of tissue resected during surgery, there remains high variability within glioma subtypes in terms of response to treatment and outcome. In this study we hypothesized that parameters obtained from magnetic resonance data would be associated with progression-free survival for patients with recurrent low-grade glioma. The values considered were derived from the analysis of anatomic imaging, diffusion weighted imaging, and 1H magnetic resonance spectroscopic imaging data. Metrics obtained from diffusion and spectroscopic imaging presented strong prognostic capability within the entire population as well as when restricted to astrocytomas, but demonstrated more limited efficacy in the oligodendrogliomas. The results indicate that multi-parametric imaging data may be applied as a non-invasive means of assessing prognosis and may contribute to developing personalized treatment plans for patients with recurrent low-grade glioma.

Magnetic resonance analysis of malignant transformation in recurrent glioma.

BACKGROUND: Patients with low-grade glioma (LGG) have a relatively long survival, and a balance is often struck between treating the tumor and impacting quality of life. While lesions may remain stable for many years, they may also undergo malignant transformation (MT) at the time of recurrence and require more aggressive intervention. Here we report on a state-of-the-art multiparametric MRI study of patients with recurrent LGG. METHODS: One hundred and eleven patients previously diagnosed with LGG were scanned at either 1.5 T or 3 T MR at the time of recurrence. Volumetric and intensity parameters were estimated from anatomic, diffusion, perfusion, and metabolic MR data. Direct comparisons of histopathological markers from image-guided tissue samples with metrics derived from the corresponding locations on the in vivo images were made. A bioinformatics approach was applied to visualize and interpret these results, which included imaging heatmaps and network analysis. Multivariate linear-regression modeling was utilized for predicting transformation. RESULTS: Many advanced imaging parameters were found to be significantly different for patients with tumors that had undergone MT versus those that had not. Imaging metrics calculated at the tissue sample locations highlighted the distinct biological significance of the imaging and the heterogeneity present in recurrent LGG, while multivariate modeling yielded a 76.04% accuracy in predicting MT. CONCLUSIONS: The acquisition and quantitative analysis of such multiparametric MR data may ultimately allow for improved clinical assessment and treatment stratification for patients with recurrent LGG.

Changes in pyruvate metabolism detected by magnetic resonance imaging are linked to DNA damage and serve as a sensor of temozolomide response in glioblastoma cells.

Recent findings show that exposure to temozolomide (TMZ), a DNA-damaging drug used to treat glioblastoma (GBM), can suppress the conversion of pyruvate to lactate. To understand the mechanistic basis for this effect and its potential utility as a TMZ response biomarker, we compared the response of isogenic GBM cell populations differing only in expression of the DNA repair protein methyltransferase (MGMT), a TMZ-sensitivity determinant, after exposure to TMZ in vitro and in vivo. Hyperpolarized [1-((13))C]-pyruvate-based MRI was used to monitor temporal effects on pyruvate metabolism in parallel with DNA-damage responses and tumor cell growth. TMZ exposure decreased conversion of pyruvate to lactate only in MGMT-deficient cells. This effect coincided temporally with TMZ-induced increases in levels of the DNA-damage response protein pChk1. Changes in pyruvate to lactate conversion triggered by TMZ preceded tumor growth suppression and were not associated with changes in levels of NADH or lactate dehydrogenase activity in tumors. Instead, they were associated with a TMZ-induced decrease in the expression and activity of pyruvate kinase PKM2, a glycolytic enzyme that indirectly controls pyruvate metabolism. PKM2 silencing decreased PK activity, intracellular lactate levels, and conversion of pyruvate to lactate in the same manner as TMZ, and Chk1 silencing blocked the TMZ-induced decrease in PKM2 expression. Overall, our findings showed how TMZ-induced DNA damage is linked through PKM2 to changes in pyruvate metabolism, and how these changes can be exploited by MRI methods as an early sensor of TMZ therapeutic response.

Characterization of metabolites in infiltrating gliomas using ex vivo ¹H high-resolution magic angle spinning spectroscopy.

Gliomas are routinely graded according to histopathological criteria established by the World Health Organization. Although this classification can be used to understand some of the variance in the clinical outcome of patients, there is still substantial heterogeneity within and between lesions of the same grade. This study evaluated image-guided tissue samples acquired from a large cohort of patients presenting with either new or recurrent gliomas of grades II-IV using ex vivo proton high-resolution magic angle spinning spectroscopy. The quantification of metabolite levels revealed several discrete profiles associated with primary glioma subtypes, as well as secondary subtypes that had undergone transformation to a higher grade at the time of recurrence. Statistical modeling further demonstrated that these metabolomic profiles could be differentially classified with respect to pathological grading and inter-grade conversions. Importantly, the myo-inositol to total choline index allowed for a separation of recurrent low-grade gliomas on different pathological trajectories, the heightened ratio of phosphocholine to glycerophosphocholine uniformly characterized several forms of glioblastoma multiforme, and the onco-metabolite D-2-hydroxyglutarate was shown to help distinguish secondary from primary grade IV glioma, as well as grade II and III from grade IV glioma. These data provide evidence that metabolite levels are of interest in the assessment of both intra-grade and intra-lesional malignancy. Such information could be used to enhance the diagnostic specificity of in vivo spectroscopy and to aid in the selection of the most appropriate therapy for individual patients.

Mutational analysis reveals the origin and therapy-driven evolution of recurrent glioma.

Tumor recurrence is a leading cause of cancer mortality. Therapies for recurrent disease may fail, at least in part, because the genomic alterations driving the growth of recurrences are distinct from those in the initial tumor. To explore this hypothesis, we sequenced the exomes of 23 initial low-grade gliomas and recurrent tumors resected from the same patients. In 43% of cases, at least half of the mutations in the initial tumor were undetected at recurrence, including driver mutations in TP53, ATRX, SMARCA4, and BRAF; this suggests that recurrent tumors are often seeded by cells derived from the initial tumor at a very early stage of their evolution. Notably, tumors from 6 of 10 patients treated with the chemotherapeutic drug temozolomide (TMZ) followed an alternative evolutionary path to high-grade glioma. At recurrence, these tumors were hypermutated and harbored driver mutations in the RB (retinoblastoma) and Akt-mTOR (mammalian target of rapamycin) pathways that bore the signature of TMZ-induced mutagenesis.

Identifying malignant transformations in recurrent low grade gliomas using high resolution magic angle spinning spectroscopy.

OBJECTIVE: The objective of this study was to determine whether metabolic parameters derived from ex vivo analysis of tissue samples are predictive of biologic characteristics of recurrent low grade gliomas (LGGs). This was achieved by exploring the use of multivariate pattern recognition methods to generate statistical models of the metabolic characteristics of recurrent LGGs that correlate with aggressive biology and poor clinical outcome. METHODS: Statistical models were constructed to distinguish between patients with recurrent gliomas that had undergone malignant transformation to a higher grade and those that remained grade 2. The pattern recognition methods explored in this paper include three filter-based feature selection methods (chi-square, gain ratio, and two-way conditional probability), a genetic search wrapper-based feature subset selection algorithm, and five classification algorithms (linear discriminant analysis, logistic regression, functional trees, support vector machines, and decision stump logit boost). The accuracy of each pattern recognition framework was evaluated using leave-one-out cross-validation and bootstrapping. MATERIALS: The population studied included fifty-three patients with recurrent grade 2 gliomas. Among these patients, seven had tumors that transformed to grade 4, twenty-four had tumors that transformed to grade 3, and twenty-two had tumors that remained grade 2. Image-guided tissue samples were obtained from these patients using surgical navigation software. Part of each tissue sample was examined by a pathologist for histological features and for consistency with the tumor grade diagnosis. The other part of the tissue sample was analyzed with ex vivo nuclear magnetic resonance (NMR) spectroscopy. RESULTS: Distinguishing between recurrent low grade gliomas that transformed to a higher grade and those that remained grade 2 was achieved with 96% accuracy, using areas of the ex vivo NMR spectrum corresponding to myoinositol, 2-hydroxyglutarate, hypo-taurine, choline, glycerophosphocholine, phosphocholine, glutathione, and lipid. Logistic regression and decision stump boosting models were able to distinguish between recurrent gliomas that transformed to a higher grade and those that did not with 100% training accuracy (95% confidence interval [93-100%]), 96% leave-one-out cross-validation accuracy (95% confidence interval [87-100%]), and 96% bootstrapping accuracy (95% confidence interval [95-97%]). Linear discriminant analysis, functional trees, and support vector machines were able to achieve leave-one-out cross-validation accuracy above 90% and bootstrapping accuracy above 85%. The three feature ranking methods were comparable in performance. CONCLUSIONS: This study demonstrates the feasibility of using quantitative pattern recognition methods for the analysis of metabolic data from brain tissue obtained during the surgical resection of gliomas. All pattern recognition techniques provided good diagnostic accuracies, though logistic regression and decision stump boosting slightly outperform the other classifiers. These methods identified biomarkers that can be used to detect malignant transformations in individual low grade gliomas, and can lead to a timely change in treatment for each patient.

Magnetic resonance of 2-hydroxyglutarate in IDH1-mutated low-grade gliomas.

Recent studies have indicated that a significant survival advantage is conferred to patients with gliomas whose lesions harbor mutations in the genes isocitrate dehydrogenase 1 and 2 (IDH1/2). IDH1/2 mutations result in aberrant enzymatic production of the potential oncometabolite D-2-hydroxyglutarate (2HG). Here, we report on the ex vivo detection of 2HG in IDH1-mutated tissue samples from patients with recurrent low-grade gliomas using the nuclear magnetic resonance technique of proton high-resolution magic angle spinning spectroscopy. Relative 2HG levels from pathologically confirmed mutant IDH1 tissues correlated with levels of other ex vivo metabolites and histopathology parameters associated with increases in mitotic activity, relative tumor content, and cellularity. Ex vivo spectroscopic measurements of choline-containing species and in vivo magnetic resonance measurements of diffusion parameters were also correlated with 2HG levels. These data provide extensive characterization of mutant IDH1 lesions while confirming the potential diagnostic value of 2HG as a surrogate marker of patient survival. Such information may augment the ability of clinicians to monitor therapeutic response and provide criteria for stratifying patients to specific treatment regimens.

Evaluation of diffusion parameters as early biomarkers of disease progression in glioblastoma multiforme.

The purpose of this study was to evaluate diffusion parameters at pre-, mid-, and post-radiation therapy (RT) in contrast-enhancing and nonenhancing lesions of postsurgical glioblastoma multiforme patients treated with the standard of care RT concurrently with temozolomide (TMZ) followed by adjuvant TMZ and an antiangiogenic drug. The diffusion parameters explored include baseline and short-term changes in apparent diffusion coefficient, fractional anisotropy, and eigenvalues. These diffusion parameters were examined as early markers for disease progression by relating them to clinical outcome of 6-month progression-free survival. The results indicated that changes from mid- to post-RT were significantly different between patients who progressed within 6 months vs those who were free of progression for 6 months after initiation of therapy. The study also showed that the changes in diffusion parameters from the mid- to post-RT scan may be more significant than those from pre- to mid-RT and pre- to post-RT. This is important because the mid-RT scan is currently not performed as part of the standard clinical care.