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.

Multiband RF pulses with improved performance via convex optimization.

Selective RF pulses are commonly designed with the desired profile as a low pass filter frequency response. However, for many MRI and NMR applications, the spectrum is sparse with signals existing at a few discrete resonant frequencies. By specifying a multiband profile and releasing the constraint on "don't-care" regions, the RF pulse performance can be improved to enable a shorter duration, sharper transition, or lower peak B1 amplitude. In this project, a framework for designing multiband RF pulses with improved performance was developed based on the Shinnar-Le Roux (SLR) algorithm and convex optimization. It can create several types of RF pulses with multiband magnitude profiles, arbitrary phase profiles and generalized flip angles. The advantage of this framework with a convex optimization approach is the flexible trade-off of different pulse characteristics. Designs for specialized selective RF pulses for balanced SSFP hyperpolarized (HP) (13)C MRI, a dualband saturation RF pulse for (1)H MR spectroscopy, and a pre-saturation pulse for HP (13)C study were developed and tested.

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.

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.

Label-Free SERS Detection of Small Proteins Modified to Act as Bifunctional Linkers.

Two double-cysteine mutants of a small protein judiciously modified so that the cysteines appear at axially opposite sides of the native fold were prepared such that different axes were defined in the two mutants. Upon reduction, the disulfide bonds are broken, and the proteins act as bifunctional ligands toward Ag nanoparticles, encouraging their assembly into nanoparticle dimers and small aggregates such that, when excited with laser light, the proteins are automatically located at electromagnetic hot spots within the aggregates. Because the protein molecules are small (~2.3 nm) and because the electromagnetic energy at a hot spot tends to increase as the size of the interparticle gap decreases, this nanoparticle-protein-nanoparticle geometry significantly enhances the Raman emission at the metallic surface. Exploiting this effect, we have recorded surface-enhanced Raman spectra (SERS) of the proteins at near-single-molecule level. The observed SERS spectra were dominated by the vibrations of molecular groups near the anchor points of the proteins.