Research ArticleCancer

Glutamine-based PET imaging facilitates enhanced metabolic evaluation of gliomas in vivo

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Science Translational Medicine  11 Feb 2015:
Vol. 7, Issue 274, pp. 274ra17
DOI: 10.1126/scitranslmed.aaa1009

Abstract

Glucose and glutamine are the two principal nutrients that cancer cells use to proliferate and survive. Many cancers show altered glucose metabolism, which constitutes the basis for in vivo positron emission tomography (PET) imaging with 18F-fluorodeoxyglucose (18F-FDG). However, 18F-FDG is ineffective in evaluating gliomas because of high background uptake in the brain. Glutamine metabolism is also altered in many cancers, and we demonstrate that PET imaging in vivo with the glutamine analog 4-18F-(2S,4R)-fluoroglutamine (18F-FGln) shows high uptake in gliomas but low background brain uptake, facilitating clear tumor delineation. Chemo/radiation therapy reduced 18F-FGln tumor avidity, corresponding with decreased tumor burden. 18F-FGln uptake was not observed in animals with a permeable blood-brain barrier or neuroinflammation. We translated these findings to human subjects, where 18F-FGln showed high tumor/background ratios with minimal uptake in the surrounding brain in human glioma patients with progressive disease. These data suggest that 18F-FGln is avidly taken up by gliomas, can be used to assess metabolic nutrient uptake in gliomas in vivo, and may serve as a valuable tool in the clinical management of gliomas.

INTRODUCTION

Cancer cells commonly undergo metabolic reprogramming, enabling increased nutrient uptake and metabolism (1). Glucose and glutamine are key nutrients that cancer cells use for survival and proliferation (1, 2). Through the Warburg effect, tumors exhibit enhanced glucose uptake and metabolism by aerobic glycolysis (1, 2). This increase in glucose uptake can be evaluated in vivo using positron emission tomography (PET) imaging with the glucose analog 18F-fluorodeoxyglucose (18F-FDG). 18F-FDG PET imaging is a valuable clinical tool and is routinely used in diagnosing, grading, and staging cancers and in assessing the efficacy of therapies (3). However, 18F-FDG is not effective in evaluating gliomas in vivo because the high glucose metabolism in the normal brain results in suboptimal tumor detection and delineation (4, 5). Neurologically destructive gliomas are one of the most fatal forms of cancer. Thus, there is an urgent and unmet need to develop more effective clinical imaging modalities as a means to effectively and noninvasively evaluate altered nutrient uptake and metabolism in gliomas in vivo.

Glutamine is the other principal nutrient that tumor cells use. It is the most abundant amino acid in the plasma, and many cancers are addicted to glutamine for their survival. Cancers such as neuroblastoma, lymphoma, renal carcinoma, and pancreatic adenocarcinoma use altered glutamine metabolism to support their growth and survival. Glutamine metabolism contributes to tumor cell proliferation, ATP (adenosine 5′-triphosphate) synthesis, and the production of biomolecules, such as proteins, lipids, and nucleic acids (6, 7). We have recently developed 4-18F-(2S,4R)-fluoroglutamine (18F-FGln), an analog of glutamine that is taken up by cancer cells in vitro and shows specific uptake on PET imaging in mouse xenograft models in vivo (8).

We hypothesized that glutamine addiction in gliomas can be leveraged to image gliomas in vivo by PET with 18F-FGln to assess altered nutrient uptake in the tumors. Primary glioblastomas (GBMs) show various genetic alterations, such as platelet-derived growth factor receptor A (PDGFRA) amplification, phosphatase and tensin homolog (PTEN) loss, and epidermal growth factor (EGFR) alterations (9). These molecular abnormalities converge on deregulation of the PI3K (phosphatidylinositol 3-kinase)/AKT/mTOR (mammalian target of rapamycin) pathway (9). Secondary GBMs and ~70% of intermediate-grade gliomas harbor mutations in isocitrate dehydrogenase 1 (IDH1), an enzyme in the tricarboxylic acid (TCA) cycle, resulting in the production of the oncometabolite 2-hydroxyglutarate (2-HG) (10). Thus, from a metabolic perspective, gliomas fall into two broad groups: those driven by enhanced PI3K/AKT/mTOR signaling (primary GBMs) and those bearing IDH1 mutations (secondary GBMs and intermediate-grade gliomas).

To address our hypothesis, we used PET imaging with 18F-FGln in vivo to evaluate glutamine uptake in PDGF (platelet-derived growth factor)–driven glioma models with PTEN loss (to model primary GBMs with enhanced PI3K/AKT/mTOR signaling) and in IDH1-mutant (IDH1m) glioma models. The data demonstrate that 18F-FGln showed high uptake in both glioma models but minimal uptake in the normal brain, enabling clear tumor visualization. Further, 18F-FGln specifically delineated gliomas in vivo by PET imaging in animal models and in human glioma patients with disease progression. The results suggest that 18F-FGln may serve as a valuable clinical tool in the assessment of metabolic nutrient uptake in gliomas in vivo using PET imaging.

RESULTS

18F-FGln shows high uptake in gliomas but negligible uptake in the normal brain

Because glutamine is an important source of replenishment of TCA cycle metabolites (termed anaplerosis) in many cancers, we first evaluated the contribution of glutamine to TCA cycle anaplerosis in glioma cell lines bearing various oncogenes: U87-MG (PTEN−/−), TS543 (PDGFRA, PTEN−/−), and TS603 (IDH1m). Glutamine was the main TCA cycle anaplerotic substrate in all cell lines tested (fig. S1), underscoring the importance of glutamine as a key nutrient in gliomas and the rationale for developing glutamine-based PET imaging of gliomas. To determine if fluorinated glutamine is metabolized to glutamate, we compared 19F-FGln [identical to 18F-FGln, except that 18F is replaced with the more stable fluorine isotope 19F to enable gas chromatography (GC)–mass spectroscopy analyses] with [U-13C]glutamine metabolism in the above cell lines. Whereas [U-13C]glutamine was metabolized to [U-13C]glutamate, no 19F-glutamate was detected (in comparison to standards), suggesting that 19F-FGln is not converted to 19F-glutamate (fig. S2). These in vitro data with 19F-FGln are similar to 18F-FGln data in vivo, where only a minor fraction of 18F-FGln [~9% in animal tumor xenografts (8)] is converted to 18F-glutamate, suggesting that 18F-FGln PET imaging is mainly a measure of glutamine uptake.

To assess glutamine uptake in vivo in gliomas, we used PET imaging with the glutamine analog 18F-FGln (Fig. 1A). Biodistribution studies with 18F-FGln in normal mice (fig. S3) showed that 18F-FGln crossed the blood-brain barrier (BBB) but showed minimal uptake in the normal brain compared to other organs such as the pancreas and the gut (Fig. 1 and fig. S3). We thus postulated that high glutamine utilization in gliomas (fig. S1) coupled with minimal uptake in the normal brain (Fig. 1 and fig. S3) would result in high tumor-to-background ratios. To test this, we compared 18F-FGln and 18F-FDG uptake in the normal mouse brain with glioma xenografts. Xenograft models were created by subcutaneously injecting TS543 (PDGFRA, PTEN−/−), TS603 (IDH1m), TS598 (EGFR), and U87-MG (PTEN−/−) glioma cells into SCID (severe combined immunodeficient) mice. Xenografts histopathologically resembled human gliomas (9) (fig. S4, A to D). Fasting or perfusion did not have any effect on 18F-FGln uptake in glioma subcutaneous xenografts (fig. S5). Further, 18F-FGln uptake was significantly (P = 0.0088) lowered in xenografts on co-injection of excess cold 19F-FGln (fig. S3). All glioma subcutaneous xenografts showed significantly (P < 0.0001) higher uptake of 18F-FGln compared to the normal brain (Fig. 1 and fig. S6, whole body images). 18F-FDG showed higher or equivalent uptake in the normal brain compared to all tested glioma subcutaneous xenografts (Fig. 1 and fig. S6, whole-body images).

Fig. 1. 18F-FGln shows high uptake in glioma xenografts and low background in normal brain.

(A) Illustration of the structure of 18F-FGln. (B) Comparison of 18F-FGln uptake at 0.5, 1, and 2 hours after injection in the normal brain (black bars, n = 6 for all time points) with glioma xenografts: TS598 with EGFR amplification (green bars, n = 6 for all time points), U87-MG with PTEN deletion (dark blue bars, n = 5 for all time points), TS543 with PDGFRA amplification and PTEN deletion (light blue bars, n = 5 for 0.5- and 1-hour time points, n = 4 for 2-hour time point), and TS603 with IDH1 R132H mutations (orange bars, n = 5 for all time points). %ID/cc: percent injected dose/cubic centimeter. Statistical significance was determined by two-sided analysis of variance (ANOVA); ***P < 0.001. (C) Comparison of 18F-FDG uptake at 0.5, 1, and 2 hours after injection in the normal brain (black bars, n = 6 for all time points) with glioma xenografts: TS598 with EGFR amplification (green bars, n = 3 for 0.5 and 1 hour time points and n = 6 for 2-hour time point), U87-MG with PTEN deletion (dark blue bars, n = 5 for all time points), TS543 with PDGFRA amplification and PTEN deletion (light blue bars, n = 6 for 0.5-hour time point and n = 4 for 1- and 2-hour time points), and TS603 with IDH1 R132H mutations (orange bars, n = 5 for all time points). %ID/cc: percent injected dose/cubic centimeter. (D) Illustration of mouse with glioma xenograft implanted in the shoulder region, indicating coronal and transverse planes along which PET images were captured. (E) Representative coronal PET images of the normal skull and brain depicting 18F-FGln and 18F-FDG uptake. (F) Representative transverse PET images (see fig. S5 for full-body coronal images) showing 18F-FGln and 18F-FDG uptake in TS603 (IDH1 R132H) glioma xenografts (indicated by red arrows). (G) Representative transverse PET images (see fig. S5 for full-body coronal images) showing 18F-FGln and 18F-FDG uptake in TS543 (PDGFRA, PTEN−/−) glioma xenografts (indicated by red arrows). For all graphs, data are represented as means ± SEM.

In IDH1m glioma cells, we found that [U-13C]glutamine was metabolized to generate the oncometabolite 2-HG. This was reversed either by short hairpin RNA (shRNA) knockdown of total IDH1 (mutant and wild type) or by an IDH1m-specific inhibitor (IDH35) (11) in vitro (figs. S1I and S7). Glioma xenografts bearing shRNA against total IDH1 did not show significant alterations in 18F-FGln uptake compared to controls (fig. S7). This suggests that 18F-FGln uptake in vivo in TS603 IDH1m cells is not altered when the activity of mutant IDH1 generating 2-HG is inhibited (fig. S7).

18F-FGln enables distinct delineation of gliomas in vivo

We next evaluated well-characterized genetically engineered glioma mouse models using the RCAS (replication-competent avian sarcoma-leukosis virus long terminal repeat with splice acceptor)/tv-a (tumor virus A) system driven by PDGF with a PTEN-null background (RCAS-PDGF, PTEN−/−), which develop GBM histologically identical to human GBM (fig. S4, E and G) (12). PET imaging in these animals showed marked 18F-FGln uptake with distinct tumor delineation (compared to the surrounding brain) in a region directly corresponding to the tumor, as detected by magnetic resonance imaging (MRI) and confirmed by autoradiography and histopathology (Fig. 2, A to F). Tumor-to-background ratios with 18F-FGln ranged from 4:1 to 6:1, compared to ~1:1 tumor-to-background ratio with 18F-FDG (Fig. 2F). Similar findings were observed in RCAS-PDGF animals on a PTEN wild-type background (fig. S8, A to D) and in an orthotopic IDH1m glioma model (Fig. 2, G to L, and fig.S8, E to G).

Fig. 2. 18F-FGln shows high tumor uptake compared to background in gliomas.

(A) Representative coronal MRI depicting tumor (red arrows) in genetically engineered RCAS-PDGF, PTEN−/− mice. (B) Coronal 18F-FGln PET image illustrating high tumor uptake (red arrows) compared to surrounding nonneoplastic brain (white asterisk). (C) Coronal 18F-FDG PET image from the same animal. (D) Representative ex vivo 18F-FGln autoradiogram from a RCAS-PDGF, PTEN−/− animal. (E) Histological section from the same animal depicted in (D), showing the tumor region (dotted black line). Scale bar, 1000 μm. H&E, hematoxylin and eosin. (F) Time-activity curve illustrating tumor-to-background ratio with 18F-FGln (blue) compared to 18F-FDG (red) in RCAS-PDGF, PTEN-null animals (n = 6 each). Dotted black line indicates an equal tumor-to-brain ratio of 1:1. Statistical significance was determined by two-sided, unpaired Student’s t test; ***P < 0.0001. (G) Representative coronal MRI showing tumor (red arrows) in mice orthotopically implanted with TS603 (IDH1 R132H) glioma cells. (H) Coronal 18F-FGln PET image from the same animal illustrating high tumor uptake (red arrows) compared to surrounding nonneoplastic brain (white asterisk). (I) Coronal 18F-FDG PET image from the same animal. (J) Ex vivo 18F-FGln autoradiogram from the same animal. (K) Histological section from the same animal. Scale bar, 1000 μm. (L) Time-activity curve illustrating tumor-to-background ratio with 18F-FGln (blue, (n = 4 for 36-min imaging time point, n = 3 for all other time points) compared to 18F-FDG (red, n = 3 for all time points) in mice orthotopically implanted with TS603 (IDH1 R132H) glioma cells. Dotted black line indicates an equal tumor-to-brain ratio of 1:1. Statistical significance was determined by two-sided, unpaired Student’s t test; *P < 0.05 and **P < 0.01. For all graphs, data are represented as means ± SEM.

18F-FGln uptake is not observed in neuroinflammation or BBB disruption

To evaluate if inflammatory cells contributed to 18F-FGln uptake, we created mouse models of neuroinflammation (Fig. 3A). Lipopolysaccharide (LPS) injection into the brain resulted in global activation of IBA1 immunoreactive microglia/macrophages in the injected hemisphere well beyond the injection site (Fig. 3B and fig. S9, A to D). We also used interferon-γ (IFN-γ), which polarizes macrophages/microglia toward classic activation, and interleukin-4 (IL4), which mediates an alternative activation phenotype similar to tumor-associated macrophages (13). Robust neuroinflammation was confirmed histopathologically (Fig. 3B and fig. S9, A to D). Mice were imaged at the peak of neuroinflammation with 18F-FGln and 18F-FDG (Fig. 3, C to E, and fig. S9, E to G). 18F-FDG PET is generally a poor measure of neuroinflammation in mouse brains in vivo because of the high background uptake in the brain (14). Consistent with this, no lesion was discernible with 18F-FDG PET (Fig. 3D and fig. S9F). Conversely, 18F-FGln did not show any uptake at the site of the lesion in neuroinflammatory models, as opposed to the high uptake seen in gliomas (Fig. 3C and fig. S9E).

Fig. 3. 18F-FGln shows no uptake in animals with neuroinflammation or a disrupted BBB.

(A) Animal models of neuroinflammation were created by intracerebral injection of LPS or a combination of IFN-γ and IL4. (B) Quantification of IBA1-positive activated microglia/macrophages at the site ipsilateral to the lesion (black bars) or contralateral to the lesion (white bars) from animals injected with LPS (n = 3) or IFN-γ/IL4 (n = 3). Statistical significance was determined by two-sided, unpaired Student’s t test; *P < 0.05 and **P < 0.01. (C) Representative coronal 18F-FGln PET image from an LPS-injected animal. (D) Representative 18F-FDG PET image from the same animal. (E) Representative ex vivo 18F-FGln autoradiogram from the same animal. (F) BBB was disrupted [as measured by extracerebral intravenous (IV) dextran] by treating animals with NECA [1-(6-amino-9H-purin-9-yl)-1-deoxy-N-ethyl-β-d-ribofuranuronamide], a combined A1 and A2 adenosine receptor agonist that increases BBB permeability by increasing spaces between endothelial cells. (G) Measurement of extracerebral IV dextran in NECA- or vehicle-treated animals (n = 3, each condition). Statistical significance was determined by two-sided, unpaired Student’s t test; *P < 0.05. (H) Representative coronal 18F-FGln PET image from a NECA-injected animal. (I) Representative 18F-FDG PET image from the same animal. (J) Representative ex vivo 18F-FGln autoradiogram from the same animal. (K) Comparison of 18F-FGln uptake and 18F-FDG uptake in RCAS-PDGF, PTEN−/− animals (black bars, n = 6 for 18F-FGln and n = 5 for 18F-FDG at all time points) injected intracerebrally with LPS (blue bars, for both 18F-FGln and 18F-FDG n = 5 at 0.5 hour, n = 4 at 1 hour, and n = 4 at 2 hours) or IFN-γ/IL4 (red bars, n = 6 for 18F-FGln at all time points; for 18F-FDG, n = 5 at 0.5 hour, and n = 6 at 1 and 2 hours) or intravenously with NECA (green bars, n = 5 for 18F-FGln and n = 4 for 18F-FDG at all time points). Dotted black line indicates an equivalent lesion-to-brain ratio of 1:1. Statistical significance was determined by two-sided ANOVA. For all graphs, data are represented as means ± SEM. ***P < 0.001.

To address the concern of BBB permeability as a factor in causing increased 18F-FGln delivery to the brain, we used an adenosine receptor agonist that is an established means of increasing BBB permeability by increasing spaces between endothelial cells in brain capillaries (15, 16). NECA [1-(6-amino-9H-purin-9-yl)-1-deoxy-N-ethyl-β-d-ribofuranuronamide], a combined A1 and A2 adenosine receptor agonist, significantly (P = 0.034) increased BBB permeability in mice as determined by measuring extravasation of fluorescent-labeled dextran into the brain (Fig. 3, F and G). We did not see increased 18F-FGln delivery to the brain in NECA-treated animals (Fig. 3, H to K), suggesting that increased BBB permeability by itself does not artificially increase 18F-FGln delivery to the brain. This demonstrates that neuroinflammation or a breach in the BBB using NECA does not significantly contribute to 18F-FGln uptake.

18F-FGln uptake in gliomas is reduced after chemo/radiation therapy

To evaluate if 18F-FGln can monitor treatment efficacy and differentiate tumor from posttreatment changes, we studied a well-characterized RCAS-PDGF, PTEN-null mouse model of radiation/chemotherapy (17) (Fig. 4A and fig. S10, A to C). The same mouse was imaged before therapy and after treatment with MRI, 18F-FGln, and 18F-FDG (Fig. 4, B to F). As can be seen in posttreatment changes in human patients, the T2-weighted MRI showed no appreciable differences when comparing before-treatment scans with after-treatment scans (18). In contrast, 18F-FGln showed a significant reduction (P = 0.0078) in tumor uptake after treatment, which was confirmed by autoradiography (Fig. 4, C to F).

Fig. 4. 18F-FGln uptake in gliomas is reduced after chemo/radiation therapy.

(A) Treatment regimen in RCAS-PDGF, PTEN−/− mice consisted of 5 days of chemotherapy (temozolomide, 50 mg/ml) and radiation therapy (155 cGy). (B) The same animal was imaged with either 18F-FGln or 18F-FDG before treatment (black bars, n = 8 for 18F-FGln and n = 6 for 18F-FDG for all time points) and after treatment (gray bars, n = 9 for 18F-FGln for 0.5- and 1-hour time points and n = 6 for 2-hour time point, and n = 6 for 18F-FDG for all time points). Dotted black line indicates an equivalent tumor-to-brain ratio of 1:1. For all graphs, data are represented as means ± SEM. Statistical significance was determined by Wilcoxon matched-pairs signed-rank t test (because the same animal was imaged before and after treatment). *P < 0.05 and **P < 0.01. (C) Representative before-treatment images of MRI, 18F-FGln PET, and 18F-FDG PET (red arrows indicate identifiable lesion). (D) Representative after-treatment images of MRI (red arrows show posttreatment changes), 18F-FGln PET, and 18F-FDG PET. (E) Ex vivo 18F-FGln autoradiogram from a different animal before treatment. (F) Ex vivo 18F-FGln autoradiogram from a different animal after treatment.

To assess the mechanism by which chemo/radiation therapy results in a decrease in 18F-FGln uptake, we compared before-treatment and after-treatment glioma brain tissues. Tumor burden was dramatically reduced after treatment, as demonstrated by a reduction in the Olig2-positive tumor cells (P = 0.031) (fig. S10, A and B). Brain tissues after treatment showed increased reactive gliosis in the form of GFAP (glial fibrillary acidic protein)–positive astrocytosis and abundant IBA1-positive macrophages/microglia (fig. S11, A and B). No significant changes were noted in CD3-positive lymphocyte infiltration or in blood vessels as delineated by CD31 staining for endothelial cells and collagen staining for vessel walls (fig. S11, C to E). Moreover, expression of the glutamine transporter SLC1A5 in residual tumor cells after treatment was not significantly different from that seen in tumor cells before treatment (fig. S11F). These data suggest that reduction in 18F-FGln uptake after chemo/radiation therapy is due to a decrease in tumor burden. Further, these data imply that 18F-FGln is taken up specifically in tumor cells, can monitor treatment responses, and can potentially differentiate posttreatment changes from tumor in glioma animal models.

18F-FGln shows high tumor-to-brain uptake ratio in human gliomas with progression

To determine if our findings could be translated to a spectrum of human gliomas apart from the animal models studied, we evaluated the expression of the glutamine transporter SLC1A5, which in part mediates 18F-FGln uptake (8, 19), as demonstrated by siRNA (small interfering RNA) knockdown and pharmacologic inhibition (fig. S12, A and B). Immunohistochemistry in normal brain tissue samples (n = 8, fig. S12C) showed minimal expression, mirroring low background 18F-FGln uptake. In contrast, SLC1A5 demonstrated higher expression in various gliomas (n = 64), consistent with high 18F-FGln glioma uptake (fig. S12, C and D). Further, we queried the GBM Cancer Genome Atlas for SLC1A5 mRNA expression, which was noted in all GBM subtypes (fig. S12E). These data suggest that 18F-FGln uptake is not restricted to the animal model glioma genotypes tested and may be of broader use in evaluating uptake of glutamine as a key nutrient in gliomas.

We translated these findings in vivo to human glioma subjects as an initial investigation of 18F-FGln PET imaging in human cancer patients [phase 1 study; Fig. 5 (A to L) and figs. S13, S14 (A to C), and S15 (A to C)]. As part of this study, we compared 18F-FGln uptake in three glioma patients with clinical progression of disease and three patients with stable disease (tables S1 and S2). Normal brain parenchyma showed minimal 18F-FGln uptake, and 18F-FGln avidity was noted in all tumors that showed progression within the three patients (tumor/brain ratio range: 3.7 to 4.8; Fig. 5L, fig. S14, and tables S2 and S3). In contrast, clinically stable tumors showed minimal or no 18F-FGln avidity on PET (fig. S15 and table S2). Normal brain tissues in these same patients demonstrated high 18F-FDG avidity, with normal brain 18F-FDG concentrations (SUV) equivalent to or greater than tumor SUV values (tumor/brain ratio range: 0.9 to 1.0; Fig. 5L and table S2). For example, in patient #5, 18F-FDG could distinguish the posterior portion of the tumor (Fig. 5C, three red arrows) from the surrounding brain, but not the anterior part (two red arrows, Fig. 5C). In contrast, both regions of the tumor showed high uptake with 18F-FGln (Fig. 5, B and E). This is an important issue considering the infiltrative nature of gliomas. Further, this patient’s tumor demonstrated mild contrast enhancement on gadolinium-enhanced MRI (Fig. 5A), but high 18F-FGln avidity (Fig. 5, B and E) and retention of 18F-FGln compared to its rapid clearance in the blood (Fig. 5F). Whole-body PET images, plasma and blood time-activity curves, biodistribution, tracer metabolite analysis, and dosimetry from these glioma patients are provided in the Supplementary Materials (figs. S14 to S16 and tables S3 to S5). These findings in human subjects recapitulate our 18F-FGln PET and 18F-FDG PET findings in mouse models and demonstrate that clinical 18F-FGln PET can evaluate high-grade glioma in vivo and may be potentially useful in identifying tumors undergoing transformation.

Fig. 5. 18F-FGln shows uptake in human gliomas undergoing progression.

(A to F) Images from patient #5. (A) T1-weighted MRI with contrast enhancement from a 42-year-old IDH1m oligodendroglioma patient showing tumor with minimal gadolinium enhancement (red arrows) along surgical cavity (indicated by white dotted line). (B) Fusion 18F-FGln PET-CT showing 18F-FGln uptake in areas corresponding to tumor (red arrows). (C) 18F-FDG PET image from the same patient showing high background brain avidity and tumor uptake in the posterior part of the tumor (three red arrows), but not in the anterior portion (two red arrows). (D) CT scan used to generate the PET-CT fusion image in (B). (E) 18F-FGln PET showing high uptake in tumor with minimal uptake in the surrounding brain. (F) Time-activity curve indicating standard uptake values (SUV) corresponding to tumor (black squares) and blood (clear circles). (G to K) Images from patient #6. (G) T1-weighted MRI with contrast enhancement from a 57-year-old GBM patient showing tumor with gadolinium enhancement (red arrows). (H) Fusion 18F-FGln PET-CT showing 18F-FGln uptake in areas corresponding to tumor. (I) 18F-FDG PET image from same patient showing high background brain avidity and tumor uptake. (J) CT scan used to generate the PET-CT fusion image in (H). (K) 18F-FGln PET showing high uptake in tumor with minimal uptake in the surrounding brain. (L) Comparison of 18F-FGln (blue bars) and 18F-FDG (red bars) illustrates differences in background uptake with both ligands in normal brain (top panel) and tumor-to-brain ratios from three clinically stable glioma patients and three glioma patients with clinically progressive disease (bottom panel) (see tables S1 and S2 for details). For all graphs, data are represented as means ± SEM.

DISCUSSION

The two principal nutrients that cancers depend on are glucose and glutamine, and metabolism of these nutrients through glycolysis and glutaminolysis is vital for cancer survival and growth (1, 2). We aimed specifically to develop a means of noninvasively assessing nutrient uptake in gliomas. 18F-FDG as a measure for metabolic glucose uptake is ineffective in gliomas because of the high background in the surrounding brain. To begin to address this gap in our knowledge, we examined whether glutamine addiction displayed by many cancer cells can be leveraged to detect glutamine uptake in gliomas in vivo using 18F-FGln. Building on our initial characterization of 18F-FGln (8), here, we (i) demonstrate that gliomas, due to their glutamine addiction, show high uptake of 18F-FGln and that the normal brain shows minimal uptake, enabling clear tumor distinction; (ii) report the use of 18F-FGln in human patients; and (iii) show that 18F-FGln could monitor treatment response in preclinical glioma models. We do not propose that glutamine is superior to current imaging standards, but that glutamine-based PET imaging enables assessment of metabolic nutrient uptake, providing complementary information about the metabolic status of gliomas.

High tumor avidity of 18F-FGln with minimal uptake in the surrounding brain enabled clear tumor delineation in all glioma animal models tested. No 18F-FGln uptake was noted in a model of impaired BBB or multiple animal models of neuroinflammation. 18F-FGln uptake is mainly mediated by the amino acid transporter SLC1A5 (8, 19), which was minimally expressed in the normal brain but markedly increased in gliomas. GC–mass spectroscopy analysis showed that FGln was not metabolized to F-glutamate. Further, we have previously shown that 60 to 70% of 18F-FGln is incorporated into protein (8, 19), and we now suggest a model wherein 18F-FGln is taken up mainly by SLC1A5 and is trapped in glioma cells by incorporation into proteins.

As part of our human trial of 18F-FGln for clinical PET imaging, high 18F-FGln avidity was noted in gliomas with progression in contrast to low background brain uptake. Additionally, no relationship was observed between contrast enhancement and 18F-FGln avidity. For example, patient #5 with mild contrast enhancement demonstrated the highest 18F-FGln avidity and retention of 18F-FGln compared to rapid clearance in the blood. If the tumor activity on PET was merely due to BBB breakdown, the data plot would instead demonstrate progressive clearance of tracer from the tumor region, in parallel with tracer clearance from the blood pool. Although we cannot entirely rule out the effects of BBB alteration, human and animal data together suggest that the relatively high 18F-FGln avidity in gliomas is not solely a function of tumor BBB disruption.

A limitation of this study is that the isotope shows bone uptake in animal models and humans (including axial uptake), with free fluorine-18 detected in the blood of all patients, implying that in vivo defluorination occurs. Peripheral bony uptake was minimal compared to axial uptake, suggesting uptake by bone marrow cells. To evaluate the impact of free fluoride on organ uptake of 18F-FGln, we compared the biodistribution of 18F-sodium fluoride as a control with that of 18F-FGln. 18F-sodium fluoride showed high bony uptake, but free fluoride uptake within various organs, including the brain, was minimal. In contrast, 18F-FGln showed lower bony uptake, but higher uptake in all organs compared to 18F-sodium fluoride. These data suggest that free fluoride does not majorly contribute to specific uptake of 18F-FGln within various organs. Moreover, tracer uptake in the skull did not obscure glioma 18F-FGln PET evaluations, because gliomas are restricted to the brain and do not invade the skull or metastasize to bone. Another limitation is the small sample size of the glioma subjects assessed. However, despite this small sample size, data from human subjects closely mirror data from glioma cell lines and animal models, as evidenced by high 18F-FGln glioma uptake and low avidity in the surrounding brain. Further, one of the prerequisites of the Food and Drug Administration (FDA)–approved, human microdose, open-label, phase 1 trial was for every patient to have a tissue diagnosis prior to imaging. This precluded imaging any surgery-naïve patients. Despite these limitations, the data presented support an exploratory proof-of-principle concept that 18F-FGln could be potentially used as an imaging agent in glioma patients.

Noninvasive imaging forms an integral part of the clinical management of glioma patients. T1-weighted MRI with or without gadolinium is the current neuroimaging standard in glioma assessment (20). MRI provides vital anatomic and structural information and is helpful in characterizing tumors using FLAIR (fluid-attenuated inversion recovery) and in assessing BBB disruption using gadolinium contrast enhancement, but it does not provide information on nutrient uptake and metabolism. Newer modalities such as magnetic resonance spectroscopy or perfusion/diffusion-weighted MRI are beginning to address these limitations (21, 22). PET imaging agents such as [11C]methionine (MET), [18F]fluorothymidine (FLT), [18F]DOPA, and [18F]fluoroethyl-l-tyrosine (FET) have also been used to image gliomas (23, 24). We do not propose that 18F-FGln is superior to many of these current neuroimaging modalities, but that 18F-FGln may provide complementary biological information specifically about metabolic nutrient uptake relevant to glioma pathology. More recently, 18F-labeled glutamate (4S)-4-(3-18F-fluoropropyl)-l-glutamate (Bayer ligand BAY 94-9392/18F-FSPG) as a PET tracer has been described in preclinical models and human subjects (25, 26). This tracer relies on the xCT cysteine/glutamate exchanger system and is thought to label intracellular glutamate pools (25). Our goal is to translate a specific nutrient metabolic pathway that is biologically relevant to the pathology of gliomas to a clinically useful imaging modality. Indeed, 18F-FGln PET imaging takes advantage of glutamine addiction in gliomas and may serve as a valuable tool to assess metabolic glutamine uptake in gliomas in vivo. Low uptake in the normal brain may also help in evaluating central nervous system metastasis.

Mice treated with chemo/radiation therapy showed a profound reduction in 18F-FGln uptake after treatment, corresponding to a decrease in tumor volume. Brain vasculature (CD34-positive and collagen IV–positive blood vessel walls) did not differ before and after treatment. Although these data suggest that vasculature may not be altered in this model, we cannot entirely rule out other changes in the vasculature or the BBB that may contribute to reduced 18F-FGln uptake after treatment. However, neuroinflammatory models showed no 18F-FGln uptake and, together with reduced uptake after treatment, suggest that 18F-FGln may be potentially useful in differentiating nonneoplastic, posttreatment, and inflammatory changes from tumor. Data from our small sample size of patients suggest that 18F-FGln may also be useful in monitoring progression of gliomas as they transform to more metabolically active and aggressive tumors. In summary, the studies suggest that glutamine-based PET imaging with 18F-FGln may be an important measure of glutamine uptake in gliomas in vivo and may serve as a valuable tool in the clinical management of gliomas.

MATERIALS AND METHODS

Study design

The objective of this study was to address the clinically unmet need of assessing metabolic nutrient uptake in gliomas in vivo. This goal was addressed by (i) evaluating glutamine uptake in gliomas by PET imaging in clinically relevant glioma animal models, (ii) assessing if glutamine PET-based imaging could monitor therapeutic response in glioma animal models, and (iii) translating these findings to human subjects.

All animal experiments were performed after approval from the Memorial Sloan Kettering Cancer Center (MSKCC) Institutional Animal Care and Use Committee and were conducted as per National Institutes of Health (NIH) guidelines for animal welfare. The use of glutamine-based PET imaging to monitor therapeutic response was assessed using standard chemo/radiation therapy protocols in glioma animal models. Animals were randomly assigned to various test groups in a blinded manner. Individuals handling the animals and conducting animal surgeries and therapies were blinded to the experimental design. Evaluation of 18F-FGln PET uptake measurements in animals was performed in a nonblinded fashion. Because 18F-FGln microPET imaging is a new imaging technology, it is difficult to estimate sample size with adequate power. An n = 3 to 9 was selected for these well-controlled models with a low (<10%) error in consecutive studies. Cell culture studies were conducted using three independent experiments (27). No samples or animals were excluded from data analyses.

Human glioma subjects were studied as part of an in-human microdose, open-label, phase 1 trial of 18F-FGln PET that was approved by the institutional review board and conducted under the auspices of an FDA-approved investigational new drug application in compliance with the Standards for Reporting of Diagnostic Accuracy studies (STARD) guidelines for diagnostic studies (trial registered at www.clinicaltrial.gov; NCT01697930). Informed consent was obtained before imaging.

Animal models of gliomas

Subcutaneous glioma xenografts were created by inoculating SCID mice (4 to 6 weeks of age, male and female, nonobese diabetic (NOD)–SCID, Taconic Farms Inc.) with 1 × 106 U87-MG, TS603, TS543, or TS598 cells resuspended in 200 μl of a 1:1 volume of cell culture medium and Matrigel (BD Biosciences). Animals were imaged when xenograft tumor volumes approached 200 mm3. Genetically modified glioma models were generated using the RCAS/tv-a system. Four- to 6-week-old, male or female C57BL6 Nestin-tv-a/Ink4a-Arf−/− mice with or without a PTENfl/fl background were anesthetized by injection of ketamine (0.1 mg/g) and xylazine (0.02 mg/g), using a stereotactic fixation device (Stoelting) (17). One microliter of RCAS-PDGF or a 1:1 mixture of 4 × 104 RCAS-PDGF and RCAS-Cre–transfected DF1 cells was delivered using a 30-gauge needle attached to a Hamilton syringe. Cells were injected into the right frontal cortex [stereotactic coordinates: bregma +1.7 mm (anterior), lateral −0.5 mm (right), and at a depth of 2.5 mm]. For orthotopic injection of glioma cells, the same procedure was followed, except that TS603 IDH1m (1 × 106 cells) was implanted into the right frontal cortex (same coordinates as above). Individuals performing implantation and stereotactic injections were blinded to the experimental design.

Small animal PET imaging

Animals were imaged with 18F-FDG and 18F-FGln (24 hours apart to allow complete decay of radiotracer) by injecting 200 μCi of the radiotracer into the lateral tail vein. PET imaging was performed using a dedicated small-animal microPET scanner (Concorde Microsystems) under 2% isoflurane anesthesia, with the tumors centered in the field of view. Dynamic imaging was performed by obtaining 60-min acquisitions with an energy window of 350 to 750 keV with a coincidence timing window of 6 ns. For static imaging, acquisitions were collected 0.5, 1, and 2 hours after injection. In each animal, the MRI and PET images were directly compared. Region-of-interest (ROI) analysis of the acquired images was performed using ASI Pro software (Siemens) in a nonblinded manner, and the observed maximum pixel value was represented as percent-injected dose/cubic centimeter (%ID/cc). Tumor-to-brain ratios were determined by normalizing tumor uptake to surrounding brain uptake.

18F-FGln synthesis

Synthesis of the precursor for 18F-FGln was performed as described (8, 28). Briefly, the radiolabeling procedure was similar except that the radiolabeling was performed at 90°C, and the final compound (in saline) was passed through a C18 cartridge and AG11A8 resin to formulate the final solution for injection. The purity of 18F-FGln was analyzed with a chiral column (Chirex 3126 d-penicillamine, 1 mM CuSO4 solution, 1 ml/min). For human subjects, 18F-FGln was manufactured at the MSKCC Radiochemistry and Molecular Probe Core Facility pursuant to an Investigational New Drug Application (IND) acknowledged by the United States FDA. Every batch of final drug product was tested to assure conformance to the drug product acceptance specifications, which included radiochemical purity (≥80%) and identity, residual solvent content, endotoxin content, radionuclidic identity, pH, and appearance. A total of 125 MBq was adequate for imaging the brain ROI and provided satisfactory PET image quality and count statistics.

18F-FGln PET–computed tomography protocol

Microdose 18F-FGln tracer was administered to patients by single peripheral intravenous injection of 125 MBq as a slow bolus (1-min duration) in a volume of 5 to 10 ml. Imaging of 18F-FGln biodistribution was obtained at about 30, 90, and 160 min after injection, using a Discovery DSTE PET–computed tomography (CT) scanner (GE Healthcare) with the patient supine on the scanner bed. After a scout x-ray, CT data were acquired with 140 kVp; 70 mA; pitch of 1.75:1; reconstructed slice thickness of 3.75 mm; 0.8 s per rotation. CT data were reconstructed in a 512 × 512 matrix using a filtered back-projection algorithm. PET emission scans were acquired starting at the proximal thigh region and ending at the head region; emission scanning specifically of the brain tumor field of view shown was acquired as a single bed position of 35-min duration in three-dimensional mode. PET images were reconstructed using an ordered subset expectation maximization iterative algorithm. PET/CT scans obtained at the 60- and 150-min postinjection time points also spanned thighs to skull using the same x-ray/CT and PET emission data acquisitions and reconstructions. PET emission data were reconstructed using an ordered subset expectation maximization iterative algorithm. Emission data were corrected for random detector inhomogeneity, scatter, attenuation, dead time, and decay. PET, CT, and fusion PET-CT images shown were generated for display using an integrated GE PACS AW Suite Workstation (GE Healthcare). PET data were analyzed using HERMES workstation (Hermes Medical Solutions).

Statistical analysis

Statistical analyses were performed in consultation with the Sloan Kettering biostatistics facility. Data are represented as means ± SEM unless specified otherwise. Graphs were plotted and statistical analyses were performed using Prism software (version 6, GraphPad). All statistical tests were two-sided. Unpaired, two-tailed Student’s t test or one-way ANOVA followed by post hoc Bonferroni, Dunnett’s, or Tukey multiple comparison analysis was used to analyze data. Wilcoxon matched pairs signed-rank t test was used when the same parameter was assessed in the same animal in any given experiment (chemo/radiation therapy when the same animal was imaged with a given radioligand before and after treatment). Data were considered significant if P values were less than 0.05 (95% confidence intervals). The original data and P values are provided in tables S6 and S7.

SUPPLEMENTARY MATERIALS

www.sciencetranslationalmedicine.org/cgi/content/full/7/274/274ra17/DC1

Materials and Methods

Fig. S1. Glutamine is a major TCA cycle substrate and generates 2-HG.

Fig. S2. 19F-FGln is not metabolized in gliomas.

Fig. S3. 18F-FGln shows minimal, but specific, uptake in the normal brain.

Fig. S4. Mouse glioma models mimic human gliomas.

Fig. S5. Fasting and perfusion do not affect 18F-FGln uptake.

Fig. S6. 18F-FGln shows uptake in mouse glioma xenografts.

Fig. S7. Gln is metabolized to 2-HG without altering 18F-FGln uptake.

Fig. S8. Glioma animal models show 18F-FGln tumor uptake.

Fig. S9. Neuroinflammatory mouse models do not show 18F-FGln uptake.

Fig. S10. Chemoradiation decreases tumor burden and improves survival.

Fig. S11. Chemoradiation therapy results in increased gliosis.

Fig. S12. SLC1A5 partly mediates 18F-FGln uptake and is expressed in human gliomas.

Fig. S13. Patients imaged with 18F-FGln show glioma SLC1A5 expression.

Fig. S14. 18F-FGln shows uptake in a clinically progressive glioma.

Fig. S15. 18F-FGln does not show uptake in a clinically stable glioma.

Fig. S16. 18F-FGln shows clearance from blood and plasma.

Table S1. Patient characteristics.

Table S2. Comparison of 18F-FGln and 18F-FDG imaging in human subjects.

Table S3. Biodistribution of 18F-FGln in human subjects.

Table S4. 18F-FGln parent compound and radiometabolites in plasma at 1, 30, and 60 min after tracer injection.

Table S5. 18F-FGln dosimetry in human subjects.

Table S6. P values (provided as a separate Excel file).

Table S7. Data used to generate graphs (provided as a separate Excel file).

References (29, 30)

REFERENCES AND NOTES

  1. Acknowledgments: We thank E. M. Burnazi and S. Cai of the MSKCC Radiochemistry and Molecular Imaging Probe Core; V. Longo of the MSKCC Small Animal Imaging Core; D. Yarilin of the MSKCC Cytology Core Facility; J. Chou and K. Panageas from the Epidemiology and Biostatistics program; P. Desai, Y. Koike, and A. Ku for technical assistance; A. Pedraza for maintaining and distributing glioma cell lines; and the MSKCC Organic Synthesis Core. We also thank A. Lashley and B. Gansukh for facilitating human studies and C. Le, M. Lupu, and D. Winkleman for animal MRI studies. We thank T. Lindsten, D. Pozega, and members of the Thompson Laboratory for critical reading of the manuscript. Funding: Supported by a Stand Up to Cancer Dream Team Translational Research Grant, grant number SU2C-AACR-DT0509 (C.B.T.). Stand Up to Cancer is a program of the Entertainment Industry Foundation administered by the American Association for Cancer Research. This work was supported by grants from the MSKCC Brain Tumor Center (S.V. and H.Z.), National Cancer Institute (NCI) K08 CA181475 (S.V.), National Institute of General Medical Sciences Medical Scientist Training Program (NIGMS MSTP) GM07739 (K.L.P.), National Institute of Neurological Disorders and Stroke (NINDS) F31 NS076028 (K.L.P.), NCI P50 CA086438 (J.S.L.), NIH R01 NS080944 (I.K.M.), and NCI R01-CA164490 (H.F.K). The MSKCC Cores were supported by the NIH Cancer Center Support Grant P30 CA08748 (C.B.T.). Author contributions: S.V., J.S.L, and C.B.T. conceived the experiments and wrote the paper. S.V. and H.Z. performed the animal experiments and analyzed the data. M.P.D. conducted the human subject study with guidance from A.M.O. and W.A.W. M.P.D., B.B., and P.Z. analyzed human data. K.L.P., C.C., S.D.C., D.R., I.K.M., G.L.R., and E.C.H. contributed to the animal experiments. M.P.D., H.Z., K.L.P., W.A.W., I.K.M., and H.F.K. provided critical insights. J.R.C. helped with the metabolism experiments, and C.W.B. helped in establishing cell lines. S.L., K.P., and H.F.K. enabled synthesis of the radioligand. Competing interests: C.B.T. is cofounder of Agios Pharmaceuticals and has financial interest in Agios. He is also a director of Charles River Laboratories and Merck Pharmaceuticals and owns stocks in these companies. H.F.K. is the CEO of Five Eleven Pharma, which has no conflict of interest with the subject matter in this manuscript. Data and materials availability: Patents have been filed concerning F-glutamine PET tracer preparation and imaging. These patents do not restrict the research or noncommercial use of the probe or technique.
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