Glutamate-Weighted Chemical Exchange Saturation Transfer Magnetic Resonance Imaging Detects Glutaminase Inhibition in a Mouse Model of Triple-Negative Breast Cancer

An Update on MR Spectroscopy in Cancer Management: Advances in Instrumentation, Acquisition, and Analysis

MR spectroscopy (MRS) is a noninvasive imaging method enabling chemical and molecular profiling of tissues in a localized, multiplexed, and nonionizing manner. As metabolic reprogramming is a hallmark of cancer, MRS provides valuable metabolic and molecular information for cancer diagnosis, prognosis, treatment monitoring, and patient management. This review provides an update on the use of MRS for clinical cancer management. The first section includes an overview of the principles of MRS, current methods, and conventional metabolites of interest. The remainder of the review is focused on three key areas: advances in instrumentation, specifically ultrahigh-field-strength MRI scanners and hybrid systems; emerging methods for acquisition, including deuterium imaging, hyperpolarized carbon 13 MRI and MRS, chemical exchange saturation transfer, diffusion-weighted MRS, MR fingerprinting, and fast acquisition; and analysis aided by artificial intelligence. The review concludes with future recommendations to facilitate routine use of MRS in cancer management. Keywords: MR Spectroscopy, Spectroscopic Imaging, Molecular Imaging in Oncology, Metabolic Reprogramming, Clinical Cancer Management © RSNA, 2024.

Exploration of Imaging Biomarkers for Metabolically-Targeted Osteosarcoma Therapy in a Murine Xenograft Model

Background: Osteosarcoma (OS) is an aggressive pediatric cancer with unmet therapeutic needs. Glutaminase 1 (GLS1) inhibition, alone and in combination with metformin, disrupts the bioenergetic demands of tumor progression and metastasis, showing promise for clinical translation. Materials and Methods: Three positron emission tomography (PET) clinical imaging agents, [18F]fluoro-2-deoxy-2-D-glucose ([18F]FDG), 3'-[18F]fluoro-3'-deoxythymidine ([18F]FLT), and (2S, 4R)-4-[18F]fluoroglutamine ([18F]GLN), were evaluated in the MG63.3 human OS xenograft mouse model, as companion imaging biomarkers after treatment for 7 d with a selective GLS1 inhibitor (CB-839, telaglenastat) and metformin, alone and in combination. Imaging and biodistribution data were collected from tumors and reference tissues before and after treatment. Results: Drug treatment altered tumor uptake of all three PET agents. Relative [18F]FDG uptake decreased significantly after telaglenastat treatment, but not within control and metformin-only groups. [18F]FLT tumor uptake appears to be negatively affected by tumor size. Evidence of a flare effect was seen with [18F]FLT imaging after treatment. Telaglenastat had a broad influence on [18F]GLN uptake in tumor and normal tissues. Conclusions: Image-based tumor volume quantification is recommended for this paratibial tumor model. The performance of [18F]FLT and [18F]GLN was affected by tumor size. [18F]FDG may be useful in detecting telaglenastat's impact on glycolysis. Exploration of kinetic tracer uptake protocols is needed to define clinically relevant patterns of [18F]GLN uptake in patients receiving telaglenastat.

Cerebral Glutamate Alterations Using Chemical Exchange Saturation Transfer Imaging in a Rat Model of Lipopolysaccharide-Induced Sepsis

Glutamate-weighted chemical exchange saturation transfer (GluCEST) is a useful imaging tool to detect glutamate signal alterations caused by neuroinflammation. This study aimed to visualize and quantitatively evaluate hippocampal glutamate alterations in a rat model of sepsis-induced brain injury using GluCEST and proton magnetic resonance spectroscopy (¹H-MRS). Twenty-one Sprague Dawley rats were divided into three groups (sepsis-induced groups (SEP05, n = 7 and SEP10, n = 7) and controls (n = 7)). Sepsis was induced through a single intraperitoneal injection of lipopolysaccharide (LPS) at a dose of 5 mg/kg (SEP05) or 10 mg/kg (SEP10). GluCEST values and ¹H-MRS concentrations in the hippocampal region were quantified using conventional magnetization transfer ratio asymmetry and a water scaling method, respectively. In addition, we examined immunohistochemical and immunofluorescence staining to observe the immune response and activity in the hippocampal region after LPS exposure. The GluCEST and ¹H-MRS results showed that GluCEST values and glutamate concentrations were significantly higher in sepsis-induced rats than those in controls as the LPS dose increased. GluCEST imaging may be a helpful technique for defining biomarkers to estimate glutamate-related metabolism in sepsis-associated diseases.

Cancer insights from magnetic resonance spectroscopy of cells and excised tumors

Multinuclear ex vivo magnetic resonance spectroscopy (MRS) of cancer cells, xenografts, human cancer tissue, and biofluids is a rapidly expanding field that is providing unique insights into cancer. Starting from the 1970s, the field has continued to evolve as a stand-alone technology or as a complement to in vivo MRS to characterize the metabolome of cancer cells, cancer-associated stromal cells, immune cells, tumors, biofluids and, more recently, changes in the metabolome of organs induced by cancers. Here, we review some of the insights into cancer obtained with ex vivo MRS and provide a perspective of future directions. Ex vivo MRS of cells and tumors provides opportunities to understand the role of metabolism in cancer immune surveillance and immunotherapy. With advances in computational capabilities, the integration of artificial intelligence to identify differences in multinuclear spectral patterns, especially in easily accessible biofluids, is providing exciting advances in detection and monitoring response to treatment. Metabolotheranostics to target cancers and to normalize metabolic changes in organs induced by cancers to prevent cancer-induced morbidity are other areas of future development.

Monitoring longitudinal disease progression in a novel murine Kit tumor model using high-field MRI

Animal models are an indispensable platform used in various research disciplines, enabling, for example, studies of basic biological mechanisms, pathological processes and new therapeutic interventions. In this study, we applied magnetic resonance imaging (MRI) to characterize the clinical picture of a novel N-ethyl-N-nitrosourea-induced Kit-mutant mouse in vivo. Seven C3H KitN824K/WT mutant animals each of both sexes and their littermates were monitored every other month for a period of twelve months. MRI relaxometry data of hematopoietic bone marrow and splenic tissue as well as high-resolution images of the gastrointestinal organs were acquired. Compared with controls, the mutants showed a dynamic change in the shape and volume of the cecum and enlarged Peyer´s patches were identified throughout the entire study. Mammary tumors were observed in the majority of mutant females and were first detected at eight months of age. Using relaxation measurements, a substantial decrease in longitudinal relaxation times in hematopoietic tissue was detected in mutants at one year of age. In contrast, transverse relaxation time of splenic tissue showed no differences between genotypes, except in two mutant mice, one of which had leukemia and the other hemangioma. In this study, in vivo MRI was used for the first time to thoroughly characterize the evolution of systemic manifestations of a novel Kit-induced tumor model and to document the observable organ-specific disease cascade.

Comparisons of Glutamate in the Brains of Alzheimer’s Disease Mice Under Chemical Exchange Saturation Transfer Imaging Based on Machine Learning Analysis

Chemical exchange saturation transfer (CEST) is one of the molecular magnetic resonance imaging (MRI) techniques that indirectly measures low-concentration metabolite or free protein signals that are difficult to detect by conventional MRI techniques. We applied CEST to Alzheimer’s disease (AD) and analyzed both region of interest (ROI) and pixel dimensions. Through the analysis of the ROI dimension, we found that the content of glutamate in the brains of AD mice was higher than that of normal mice of the same age. In the pixel-dimensional analysis, we obtained a map of the distribution of glutamate in the mouse brain. According to the experimental data of this study, we designed an algorithm framework based on data migration and used Resnet neural network to classify the glutamate distribution images of AD mice, with an accuracy rate of 75.6%. We evaluate the possibility of glutamate imaging as a biomarker for AD detection for the first time, with important implications for the detection and treatment of AD.

Glutamine Imaging: A New Avenue for Glioma Management

The glutamine pathway is emerging as an important marker of cancer prognosis and a target for new treatments. In gliomas, the most common type of brain tumors, metabolic reprogramming leads to abnormal consumption of glutamine as an energy source, and increased glutamine concentrations are associated with treatment resistance and proliferation. A key challenge in the development of glutamine-based biomarkers and therapies is the limited number of in vivo tools to noninvasively assess local glutamine metabolism and monitor its changes. In this review, we describe the importance of glutamine metabolism in gliomas and review the current landscape of translational and emerging imaging techniques to measure glutamine in the brain. These techniques include MRS, PET, SPECT, and preclinical methods such as fluorescence and mass spectrometry imaging. Finally, we discuss the roadblocks that must be overcome before incorporating glutamine into a personalized approach for glioma management.

Kinetic Modeling of 18F-(2S,4R)4-Fluoroglutamine in Mouse Models of Breast Cancer to Estimate Glutamine Pool Size as an Indicator of Tumor Glutamine Metabolism

The PET radiotracer 18F-(2S,4R)4-fluoroglutamine (18F-Gln) reflects glutamine transport and can be used to infer glutamine metabolism. Mouse xenograft studies have demonstrated that 18F-Gln uptake correlates directly with glutamine pool size and is inversely related to glutamine metabolism through the glutaminase enzyme. To provide a framework for the analysis of 18F-Gln-PET, we have examined 18F-Gln uptake kinetics in mouse models of breast cancer at baseline and after inhibition of glutaminase. We describe results of the preclinical analysis and computer simulations with the goal of model validation and performance assessment in anticipation of human breast cancer patient studies. Methods: Triple-negative breast cancer and receptor-positive xenografts were implanted in athymic mice. PET mouse imaging was performed at baseline and after treatment with a glutaminase inhibitor or a vehicle solution for 4 mouse groups. Dynamic PET images were obtained for 1 h beginning at the time of intravenous injection of 18F-Gln. Kinetic analysis and computer simulations were performed on representative time-activity curves, testing 1- and 2-compartment models to describe kinetics. Results: Dynamic imaging for 1 h captured blood and tumor time-activity curves indicative of largely reversible uptake of 18F-Gln in tumors. Consistent with this observation, a 2-compartment model indicated a relatively low estimate of the rate constant of tracer trapping, suggesting that the 1-compartment model is preferable. Logan plot graphical analysis demonstrated late linearity, supporting reversible kinetics and modeling with a single compartment. Analysis of the mouse data and simulations suggests that estimates of glutamine pool size, specifically the distribution volume (VD) for 18F-Gln, were more reliable using the 1-compartment reversible model than the 2-compartment irreversible model. Tumor-to-blood ratios, a more practical potential proxy of VD, correlated well with volume of distribution from single-compartment models and Logan analyses. Conclusion: Kinetic analysis of dynamic 18F-Gln-PET images demonstrated the ability to measure VD to estimate glutamine pool size, a key indicator of cellular glutamine metabolism, by both a 1-compartment model and Logan analysis. Changes in VD with glutaminase inhibition support the ability to assess response to glutamine metabolism-targeted therapy. Concordance of kinetic measures with tumor-to-blood ratios provides a clinically feasible approach to human imaging.

Glutamate Chemical Exchange Saturation Transfer Imaging and Functional Alterations of Hippocampus in Rat Depression Model: A Pilot Study

BACKGROUND

Adjusting abnormal glutamate neurotransmission is a crucial mechanism in the treatment of depression. However, few non-invasive techniques could effectively detect changes in glutamate neurotransmitters, and no consensus exists on whether glutamate could affect resting-state function changes in depression.

PURPOSE

To study the changes in glutamate chemical exchange saturation transfer (GluCEST) value in the hippocampus of rat model exposed to chronic unpredictable mild stress (CUMS), and to explore the effect of this change on the activity of hippocampal glutamatergic neurons.

STUDY TYPE

Prospective animal study.

ANIMAL MODEL

Twenty male Sprague-Dawley rats (200-300 g).

FIELD STRENGTH/SEQUENCE

7.0 T scanner. Fat rapid acquisition relaxation enhancement sequence for GluCEST, and echo planner imaging sequence for resting-state functional magnetic resonance imaging (rs_fMRI).

ASSESSMENT

Rats were divided into two groups: CUMS group (N = 10) and control group (CTRL, N = 10). The magnetization transfer ratio asymmetry analysis was used to quantify the GluCEST data, and evaluate the rs_fMRI data through the amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) analysis.

STATISTICAL TESTS

A t-test was used to compare the difference in GluCEST or rs_fMRI between CUMS and CTRL groups. Spearman's correlation was applied to explore the correlation between GluCEST values and abnormal fMRI values in hippocampus. Statistical significance was set at P < 0.05.

RESULTS

The GluCEST value in the left hippocampus has changed significantly (3.3 ± 0.3 [CUMS] vs. 3.9 ± 0.4 [CTRL], P < 0.05). In addition, the GluCEST value was significantly positively correlated with the ALFF values (r = 0.5, P < 0. 05, df = 7) and negatively correlated with the ReHo values (r = -0.6, P < 0.05, df = 7).

DATA CONCLUSION

GluCEST technique has the feasibility of mapping glutamate changes in rat depression. Glutamate neurotransmitters are important factors affecting the abnormal function of neural activity.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 1.

Amide Proton Transfer-weighted 7-T MRI Contrast of Myelination after Cuprizone Administration

Background Investigations of amide proton signal changes in the white matter of demyelinating diseases may provide important biophysical information for diagnostic and prognostic assessments. Purpose To evaluate amide proton signals in cuprizone-induced rats using amide proton transfer-weighted (APT_w) MRI, which provides in vivo image contrast by changing amide proton concentrations during demyelination (DEM) and subsequent remyelination (REM). Materials and Methods In this animal study, APT_w 7-T MRI was performed in 21 male Wistar rats divided into cuprizone-induced (n = 14) and control (n = 7) groups from February to August 2020. The cuprizone-induced group was further subdivided into DEM (n = 7) and REM (n = 7) groups. Seven weeks after cuprizone feeding, rats in the DEM group were killed prior to transmission electron microscopy and myelin staining, while rats in the REM group were changed to a normal chow diet and fed for 5 weeks. In each group, the APT_w signals were calculated using a conventional magnetization transfer ratio at 3.5 ppm based on regions of interest in the corpus callosum. Statistical differences in APT_w signals among the groups were analyzed with one-way analysis of variance followed by Tukey post hoc tests. Results The mean APT_w signals in the control and DEM groups were -4.42% ± 0.60 (standard deviation) (95% CI: -4.98, -3.86) and -2.57% ± 0.48 (95% CI: -3.01, -2.12), respectively, indicating higher in vivo APT_w signals in the DEM lesion (P < .001). After REM, mean APT_w signal in the REM group was -3.83% ± 0.67 (95% CI: -4.45, -3.22), similar to that in the control group (P = .18) and lower than that in the DEM group (P < .001). Conclusion Significant amide proton transfer-weighted (APT_w) metric changes coupled with the histologic characteristics of the demyelination and remyelination processes indicate the potential usefulness of APT_w 7-T MRI to monitor earlier myelination processes. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by van Zijl in this issue.

Temporal Changes in In Vivo Glutamate Signal during Demyelination and Remyelination in the Corpus Callosum: A Glutamate-Weighted Chemical Exchange Saturation Transfer Imaging Study

BACKGROUND

Glutamate-weighted chemical exchange saturation transfer (GluCEST) is a useful imaging tool that can be used to detect changes in glutamate levels in vivo and could also be helpful in the diagnosis of brain myelin changes. We investigated glutamate level changes in the cerebral white matter of a rat model of cuprizone-administered demyelination and remyelination using GluCEST.

METHOD

We used a 7 T pre-clinical magnetic resonance imaging (MRI) system. The rats were divided into the normal control (CTRL), cuprizone-administered demyelination (CPZ_DM), and remyelination (CPZ_RM) groups. GluCEST data were analyzed using the conventional magnetization transfer ratio asymmetry in the corpus callosum. Immunohistochemistry and transmission electron microscopy analyses were also performed to investigate the myelinated axon changes in each group.

RESULTS

The quantified GluCEST signals differed significantly between the CPZ_DM and CTRL groups (-7.25 ± 1.42% vs. -2.84 ± 1.30%; p = 0.001). The increased GluCEST signals in the CPZ_DM group decreased after remyelination (-6.52 ± 1.95% in CPZ_RM) to levels that did not differ significantly from those in the CTRL group (p = 0.734).

CONCLUSION

The apparent temporal signal changes in GluCEST imaging during demyelination and remyelination demonstrated the potential usefulness of GluCEST imaging as a tool to monitor the myelination process.

Non-invasive biomarkers for monitoring the immunotherapeutic response to cancer

Immunotherapy is an efficient way to cure cancer by modulating the patient’s immune response. However, the immunotherapy response is heterogeneous and varies between individual patients and cancer subtypes, reinforcing the need for early benefit predictors. Evaluating the infiltration of immune cells in the tumor and changes in cell-intrinsic tumor characteristics provide potential response markers to treatment. However, this approach requires invasive sampling and may not be suitable for real-time monitoring of treatment response. The recent emergence of quantitative imaging biomarkers provides promising opportunities. In vivo imaging technologies that interrogate T cell responses, metabolic activities, and immune microenvironment could offer a powerful tool to monitor the cancer response to immunotherapy. Advances in imaging techniques to identify tumors' immunological characteristics can help stratify patients who are more likely to respond to immunotherapy. This review discusses the metabolic events that occur during T cell activation and differentiation, anti-cancer immunotherapy-induced T cell responses, focusing on non-invasive imaging techniques to monitor T cell metabolism in the search for novel biomarkers of response to cancer immunotherapy.

Regional Mapping of Brain Glutamate Distributions Using Glutamate-Weighted Chemical Exchange Saturation Transfer Imaging

PURPOSE

To investigate glutamate signal distributions in multiple brain regions of a healthy rat brain using glutamate-weighted chemical exchange saturation transfer (GluCEST) imaging.

METHOD

The GluCEST data were obtained using a 7.0 T magnetic resonance imaging (MRI) scanner, and all data were analyzed using conventional magnetization transfer ratio asymmetry in eight brain regions (cortex, hippocampus, corpus callosum, and rest of midbrain in each hemisphere). GluCEST data acquisition was performed again one month later in five randomly selected rats to evaluate the stability of the GluCEST signal. To evaluate glutamate level changes calculated by GluCEST data, we compared the results with the concentration of glutamate acquired from 1H magnetic resonance spectroscopy (1H MRS) data in the cortex and hippocampus.

RESULTS

GluCEST signals showed significant differences (all p ≤ 0.001) between the corpus callosum (-1.71 ± 1.04%; white matter) and other brain regions (3.59 ± 0.41%, cortex; 5.47 ± 0.61%, hippocampus; 4.49 ± 1.11%, rest of midbrain; gray matter). The stability test of GluCEST findings for each brain region was not significantly different (all p ≥ 0.263). In line with the GluCEST results, glutamate concentrations measured by 1H MRS also appeared higher in the hippocampus (7.30 ± 0.16 μmol/g) than the cortex (6.89 ± 0.72 μmol/g).

CONCLUSION

Mapping of GluCEST signals in the healthy rat brain clearly visualize glutamate distributions. These findings may yield a valuable database and insights for comparing glutamate signal changes in pre-clinical brain diseases.

Metabolic reprogramming and cancer progression

Metabolic reprogramming is a hallmark of malignancy. As our understanding of the complexity of tumor biology increases, so does our appreciation of the complexity of tumor metabolism. Metabolic heterogeneity among human tumors poses a challenge to developing therapies that exploit metabolic vulnerabilities. Recent work also demonstrates that the metabolic properties and preferences of a tumor change during cancer progression. This produces distinct sets of vulnerabilities between primary tumors and metastatic cancer, even in the same patient or experimental model. We review emerging concepts about metabolic reprogramming in cancer, with particular attention on why metabolic properties evolve during cancer progression and how this information might be used to develop better therapeutic strategies.

A comparative pharmaco-metabolomic study of glutaminase inhibitors in glioma stem-like cells confirms biological effectiveness but reveals differences in target-specificity

Cancer cells upregulate anabolic processes to maintain high rates of cellular turnover. Limiting the supply of macromolecular precursors by targeting enzymes involved in biosynthesis is a promising strategy in cancer therapy. Several tumors excessively metabolize glutamine to generate precursors for nonessential amino acids, nucleotides, and lipids, in a process called glutaminolysis. Here we show that pharmacological inhibition of glutaminase (GLS) eradicates glioblastoma stem-like cells (GSCs), a small cell subpopulation in glioblastoma (GBM) responsible for therapy resistance and tumor recurrence. Treatment with small molecule inhibitors compound 968 and CB839 effectively diminished cell growth and in vitro clonogenicity of GSC neurosphere cultures. However, our pharmaco-metabolic studies revealed that only CB839 inhibited GLS enzymatic activity thereby limiting the influx of glutamine derivates into the TCA cycle. Nevertheless, the effects of both inhibitors were highly GLS specific, since treatment sensitivity markedly correlated with GLS protein expression. Strikingly, we found GLS overexpressed in in vitro GSC models as compared with neural stem cells (NSC). Moreover, our study demonstrates the usefulness of in vitro pharmaco-metabolomics to score target specificity of compounds thereby refining drug development and risk assessment.

Metabolic reprogramming in triple-negative breast cancer

Since triple-negative breast cancer (TNBC) was first defined over a decade ago, increasing studies have focused on its genetic and molecular characteristics. Patients diagnosed with TNBC, compared to those diagnosed with other breast cancer subtypes, have relatively poor outcomes due to high tumor aggressiveness and lack of targeted treatment. Metabolic reprogramming, an emerging hallmark of cancer, is hijacked by TNBC to fulfill bioenergetic and biosynthetic demands; maintain the redox balance; and further promote oncogenic signaling, cell proliferation, and metastasis. Understanding the mechanisms of metabolic remodeling may guide the design of metabolic strategies for the effective intervention of TNBC. Here, we review the metabolic reprogramming of glycolysis, oxidative phosphorylation, amino acid metabolism, lipid metabolism, and other branched pathways in TNBC and explore opportunities for new biomarkers, imaging modalities, and metabolically targeted therapies.

GPER-regulated lncRNA-Glu promotes glutamate secretion to enhance cellular invasion and metastasis in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a group of breast cancer with heterogeneity and poor prognosis and effective therapeutic targets are not available currently. TNBC has been recognized as estrogen-independent breast cancer, while the novel estrogen receptor, namely G protein-coupled estrogen receptor (GPER), was claimed to mediate estrogenic actions in TNBC tissues and cell lines. Through mRNA microarrays, lncRNA microarrays, and bioinformatics analysis, we found that GPER is activated by 17β-estradiol (E2) and GPER-specific agonist G1, which downregulates a novel lncRNA (termed as lncRNA-Glu). LncRNA-Glu can inhibit glutamate transport activity and transcriptional activity of its target gene VGLUT2 via specific binding. GPER-mediated reduction of lncRNA-Glu promotes glutamate transport activity and transcriptional activity of VGLUT2. Furthermore, GPER-mediated activation of cAMP-PKA signaling contributes to glutamate secretion. LncRNA-Glu-VGLUT2 signaling synergizes with cAMP-PKA signaling to increase autologous glutamate secretion in TNBC cells, which activates glutamate N-methyl-D-aspartate receptor (NMDAR) and its downstream CaMK and MEK-MAPK pathways, thus enhancing cellular invasion and metastasis in vitro and in vivo. Our data provide new insights into GPER-mediated glutamate secretion and its downstream signaling NMDAR-CaMK/MEK-MAPK during TNBC invasion. The mechanisms we discovered may provide new targets for clinical therapy of TNBC.