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Cancer Res. Author manuscript; available in PMC Oct 1, 2011.
Published in final edited form as:
PMCID: PMC2948586
NIHMSID: NIHMS228564
Hyperpolarized 13C spectroscopic imaging informs on hypoxia-inducible factor-1 and Myc activity downstream of platelet-derived growth factor receptor
Hagit Dafni, Peder E.Z Larson, Simon Hu, Hikari A.I. Yoshihara, Christopher S. Ward, Humsa S. Venkatesh, Chunsheng Wang, Xiaoliang Zhang, Daniel B. Vigneron, and Sabrina M. Ronen
Radiology and Biomedical Imaging, University of California, San Francisco, CA, United States
To whom reprint request should be sent: Hagit Dafni or Sabrina Ronen 1700 4th St., Suite 304, Box 2532, San Francisco, CA 94158. hagit.dafni/at/weizmann.ac.il or ; sabrin.ronen/at/radiology.ucsf.edu
The recent development of hyperpolarized 13C magnetic resonance spectroscopic imaging (MRSI) provides a novel method for in-vivo metabolic imaging with potential applications for detection of cancer and response to treatment. Chemotherapy-induced apoptosis was shown to decrease the flux of hyperpolarized 13C-label from pyruvate to lactate due to depletion of NADH, the coenzyme of lactate dehydrogenase (LDH). In contrast, we show here that in PC-3MM2 tumors, inhibition of platelet-derived growth factor receptor with imatinib reduces the conversion of hyperpolarized pyruvate to lactate by lowering the expression of LDH itself. This was accompanied by reduced expression of vascular endothelial growth factor and glutaminase, and is likely mediated by reduced expression of their transcriptional factors hypoxia-inducible factor-1 and c-Myc. Our results indicate that hyperpolarized 13C MRSI could potentially detect the molecular effect of various cell-signaling inhibitors, thus providing a radiation-free method to predict tumor response.
Keywords: Hyperpolarized 13C MRS, Tumor metabolism, PDGFR signaling, HIF-1, cMyc
Aerobic glycolysis, the switch in glucose metabolism from oxidative phosphorylation to enhanced glycolysis, occurs in cancer cells even in the presence of adequate oxygen levels. This phenomenon, first described by Otto Warburg in the 1920s, is referred to as the Warburg effect (1). The understanding that metabolism is tightly regulated by signaling pathways and transcriptional programs, together with the development of diagnostic tools such as 18F-fluorodeoxyglucose-positron-emission tomography (FDG-PET), have led to a renewed interest in the Warburg effect (1), which was recently described as the seventh hallmark of cancer (25).
Modulation of glycolysis can be used as an indicator of treatment efficacy (4). For example in the case of imatinib, an inhibitor of the tyrosine kinase BCR-ABL1 and tyrosine kinases associated with the receptors for stem cell factor (c-KIT) and platelet-derived growth factor (PDGFR) (68), FDG-PET was used to detect a rapid reduction in glucose uptake following treatment of patients with gastrointestinal stromal tumors (GISTs) that carry a gain-of-function mutation in c-KIT (9), Importantly, the metabolic changes were associated with complete remission whereas a lack of metabolic change was associated with resistance to imatinib (9, 10).
Another powerful tool for the study of metabolism and bioenergetics is magnetic resonance spectroscopy (MRS). MRS was used to detect a decrease in uptake of 13C-labeled glucose in response to imatinib in BCR-ABL1-positive chronic myeloid leukemia (CML) cells, demonstrating a reversal of the Warburg effect (11). However, the intrinsically low sensitivity and long sampling times have limited the use of 13C MRS to metabolic studies of experimental models. The recent development of hyperpolarized 13C MR using dynamic nuclear polarization (DNP), and a dissolution method that maintains hyperpolarization of injectable molecules in the liquid-state, has resulted in an increase in the 13C MR signal-to-noise ratio by more than 10,000-fold (12). This has opened the door to numerous MRS and MRS imaging (MRSI) applications, including in-vivo imaging of metabolic rates in real-time and assessment of tumor response to chemotherapy (13, 14).
Recently, we demonstrated that 13C MRS of hyperpolarized pyruvate can be used to detect metabolic changes resulting from treatment with inhibitors of phosphatidylinositol 3-kinase (PI3K) signaling (15). Cell-signaling through the PI3K pathway can be activated by various receptor tyrosine kinases (RTKs). In the present study we describe a thorough investigation of signal inhibition with imatinib using, for the first time, hyperpolarized 13C MRSI to monitor the metabolic consequences of RTK signal inhibition in-vivo. Our results inform on the mechanism by which inhibition of cell-signaling affects metabolism, and demonstrate that hyperpolarized 13C MRSI has potential as a valuable tool for detecting in-vivo response to imatinib and other targeted therapies that inhibit signaling upstream of HIF-1 and c-Myc.
In-vivo hyperpolarized 13C MRSI and macromolecular DCE-MRI
All animal studies were carried out according to the guidelines, and following approval, of the UCSF Institutional Animal Care and Use Committee. We deposited 2 × 105 PC-3MM2 cells in the tibia of CD1 nude mice and imaged 7–10 mm tumors before and at the end of 2-days treatment with imatinib (50 mg/kg daily) alone or in combination with paclitaxel (Bristol-Myers Squibb; 8 mg/kg once) (16).
We used a dual-tuned 1H/13C mouse birdcage coil and 3T GE Signa scanner (GE Healthcare) to acquire localizing T2-weighted images in three planes followed by dynamic 2D 13C MRSI in axial orientation (multiband excitation pulse applying flip angle of 3.3° to pyruvate and 20° to lactate and alanine, echo-planar readout, TR/TE 250/160 ms, 2 sec acquisition time per image, voxels size 5×5×10 mm) (17). Hyperpolarized pyruvate (350 µL of 80 mM, (17)) was injected to isoflurane (1–2%)-anesthetized mice over 12 s through a tail vein catheter, followed by a 150 µL PBS flush. Acquisition started at the end of the 12 s pyruvate injection and repeated every 5 s up to 100 s.
After changing the RF coil to a high-resolution custom-built 1H-mouse knee coil, a localizing T2-weighted axial imaging was followed by DCE-MRI (3D–fast spoiled gradient recalled sequence, TR/TE 24.7/3.4 ms, flip angle 35°, 2 NEX, slice thickness 600 µm, in-plane resolution 156×156 µm, acquisition time 3.4 minutes) acquired pre and post-injection of albumin-GdDTPA (200 µl of 4 µmol/kg followed by flush) (18, 19).
In-vivo data processing
Imaging data was processed with custom in-house software using MATLAB (MathWorks, Inc.). The dynamic 13C MRSI was reconstructed (Fig S1) and the noise from the last time point when the hyperpolarized signal had decayed completely. Signal-to-noise ratio values were then normalized to percent polarization measured using an aliquot of the hyperpolarized 13C-pyruvate injected into a polarimeter, and to injected volume. Overlay images of lactate peak amplitudes on the anatomical images were generated by applying a cubic interpolation spatially to match the resolution of the anatomical images (Fig S1 and Fig S2).
We generated maximal intensity projections (MIPs) of DCE-MRI for each post-contrast time point, after subtraction of the pre-contrast dataset. Signal intensity (SI) values were normalized to the dynamic range of signal intensity and semi-quantitative analysis of vascular permeability was performed by calculating the change in signal intensity (contrast accumulation) during the first 15 minutes post-contrast (ΔSI/dt) for a region of interest manually drawn around the entire tumor, and using linear regression to fit the data (Fig S3). Tumor volume was evaluated from 3D MR images by drawing regions of interest around the tumor in all relevant slices, adding tumor voxels and multiplying by voxel size.
In-vitro hyperpolarized 13C MRS
We performed the MRS studies of PC-3MM2 cells (20) after 2 days of activation and inhibition of PDGFR signaling with recombinant human PDGF-BB (20 ng/mL; Invitrogen) and imatinib (5 or 50 µM; kindly provided by Novartis Pharma, Basel, Switzerland) respectively. We encapsulated 6 – 8 × 107 cells into agarose beads and a day later loaded them into a perfusion system (15, 21, 22). We polarized [1-13C] pyruvic acid and [5-13C] glutamine (Isotec) to ~20% and ~5% (17, 23), and injected the polarized substrate to a final concentration of 5 mM and 2.5 mM respectively during acquisition of 13C spectra on a 500-MHz INOVA spectrometer (Varian) while medium circulation was briefly stopped (15). Glutamine was also injected directly into a cell lysate (6 – 8 × 107 cells)(23).
We recorded 13C spectra (single transient every 3 s, 13° excitation pulses) and 31P spectra (to confirm cell viability) on a 500-MHz INOVA spectrometer (Varian), and quantified intensities of metabolite peaks by integration (ACD/Spec Manager, Advanced Chemistry Development, Toronto, Canada) and normalization to total carbon signal and cell number (15).
Immunostaining and immunoblotting
Tissue sections (prepared as described (16)) from untreated and 2 day treated tumors, and whole cell lysates (RIPA; Cell Signaling, or 50 mM Tris (pH 8.2), 2 mM dithiothreitol, 2 mM EDTA and 1% Triton X-100) or nuclear extracts (for HIF-1α; (24)) from tumors and cells, were probed with the following: rabbit antibodies against cleaved caspase-3, caspase-3, c-Myc, AKT, p-AKT, β-actin, (Cell Signaling), c-Myc, LDH-A (Epitomics), VEGF, CAIX (Abcam), HIF-1α (Novus), MCT1 (Santa Cruz Biotechnology, Santa Cruz, CA), mouse antibody against glutaminase (Abcam), and fluorescent (Invitrogen) or HRP-linked secondary antibodies (Cell Signaling or Abcam). For loading control in western blots (Fig S4), anti β-actin was used in combination with other antibodies or after striping the membrane. Quantification was performed using Photoshop by measuring band intensities in scanned blots, subtracting background intensity and normalizing to loading control. Results are presented as percent of control (untreated tumors).
LDH activity and NAD(H) assays
The activity of LDH was measured (25) in tumor lysate (RIPA). KM and Vmax values were determined by fitting initial rates of NADH consumption (absorbance at 340 nm) and pyruvate concentrations to a Lineweaver-Burke plot. The levels of total NAD(H) in lysates (freeze-thaw) were determined by measuring the change in absorbance at 570 nm due to reduction of thiazolyl blue by NADH (26).
Statistical analysis
Results are expressed as means ± s.d. Statistical analyses were performed using analytic computerized software (Statistix 8 Student Edition, Analytical Software, Tallahassee, FL, USA). The effect of imatinib versus imatinib-paclitaxel treatment on the MRSI signal (Δ) between day 0 and day 2 of treatment was evaluated using Kruskall–Wallis non-parametric one-way ANOVA, since the data was not normally distributed (Shapiro-Wilk Test) and the variances were not equal between the groups (Bartlett’s Test). This comparison between the treatments indicated no statistical difference (p>0.9999). Treatment groups were therefore combined and paired t-test analysis was used to evaluate the difference between day 0 and day 2 where each mouse served as its own control. Unpaired t-test was used for perfused cells studies, activity assay and immunoblot analysis. p < 0.05 was considered statistically significant.
Additional data is provided Supplementary Data.
Signal inhibition with imatinib reduces the hyperpolarized lactate signal
PDGFR expression and activation, and PDGFR inhibition with imatinib or imatinib in combination with paclitaxel, were previously established in the PC-3MM2 prostate cancer bone metastasis model (16, 2729). To study the possible metabolic consequences of signal inhibition in PC-3MM2 tumors we investigated the fate of hyperpolarized 13C-pyruvate using MRSI (Figs 1, S1, S2).
Fig 1
Fig 1
13C MRSI of the metabolism of hyperpolarized pyruvate indicating reduced tumor lactate signal in response to treatment
Hyperpolarized [1-13C] pyruvate can be enzymaticaly converted to [1-13C] lactate, [1-13C] alanine, or enter the mitochondria and the TCA cycle as acetyl-CoA, in which case H13CO3 (bicarbonate) is produced. Bicarbonate and alanine have been detected in normal tissue (heart, kidneys, liver) together with baseline levels of lactate (3032), whereas conversion of pyruvate into lactate is dominant under hypoxic conditions (anaerobic glycolysis) and in tumor cells performing aerobic glycolysis (2, 33). Accordingly, we detected significantly higher lactate signal in the tumor than in the muscle of the contralateral limb (n=10, p=0.016). We then investigated the effects of imatinib or imatinib-paclitaxel combination. Importantly, no statistically significant difference was observed in any of the metabolic effects of treatment between the two treatment groups (p>0.9999) indicating that our findings are likely due mostly to the effect of imatinb. Consequently, data from imatinib and imatinib-paclitaxel–treated animals was combined. Following treatment, lactate signal, normalized to noise, percent polarization and injected volume, dropped significantly 33±26% in treated animals (Fig 1, Fig 2a; n=10; p=0.021), while there was no significant change in the contralateral limb (n=10; p=0.5). A similar decrease was observed when lactate signal was normalized to control lactate signal as measured in the contralateral limb (Fig 2b; 30±65%; n=10; p=0.036) or when it was normalized to blood-pyruvate, as measured from the tail (Fig 2c;34±53%; n=10; p=0.042). At the same time, and in line with previous findings, treatment did not affect tumor size when compared to control. Tumor volume increased by 16% between day 0 and day 2 in both treated tumors (from 291±184 to 339±220 mm3; n=10) and untreated tumors (from 225±95 to 261±117; mm3) groups (p=0.5). Long-term imatinib treatment of the same tumor model inhibited tumor growth (25, 26). Thus, 13C MRSI can detect reduced conversion of hyperpolarized pyruvate to lactate in PDGFR-expressing tumors treated with imatinib before decrease in tumor size is apparent.
Fig 2
Fig 2
Quantitative MRSI results indicating significant decrease in tumor lactate signal due to treatment
Signal inhibition with imatinib reduces vascular permeability and VEGF expression
Whereas in long-term treatment imatinib inhibited tumor growth, partially by sensitizing PDGFR-expressing, tumor-associated endothelial cells to paclitaxel-mediated cytotoxicity (27, 28), the vascular effect of short-term treatment with imatinib was apparent as reduced vascular permeability without any additional effect of paclitaxel (16). To confirm vascular response in the same tumors studied by metabolic imaging, we used macromolecular DCE-MRI. The macromolecular contrast material, albumin-GdDTPA, extravasated from permeable vessels in the periphery of PC-3MM2 tumors (Fig 3a, d0; Fig S3). Semi-quantitative analysis of accumulation of contrast with time (ΔSI/dt) indicated that 11±7% out of total tumor voxels (21864±18469 voxels; which mapped to tumor periphery) were hyper-permeable (ΔSI/dt > 7.5 AU/min). This number significantly dropped to 4261±3164 voxels (2±2% relative to pretreatment) in response to treatment, while the number of voxels with low permeability increased (Fig 3b, b; n=10; p<0.03).
Fig 3
Fig 3
Macromolecular DCE-MRI indicating reduced vascular permeability in response to treatment
This significant decease in vascular permeability is in agreement with that we measured in an earlier study of the same model using a full quantitative analysis (16). Although that earlier study indicated no change in tumor blood volume (vessel density) in response to treatment, the decrease in permeability suggests partial normalization of tumor vessel function, returning to permeability levels of normal tissue. Additionally, changes in permeability can indicate changes in the levels of VEGF, a major permeability factor (19). Indeed we found that the decrease in permeability was associated with a decrease in the expression of VEGF (Fig 3c).
The imatinib-induced metabolic effect is independent of tumor vasculature
The imatinib-induced vascular response following 2 days of treatment did not include a decrease in tumor blood volume (16), or induction of apoptosis of tumor-associated endothelial cells as determined by caspase-3 staining (data not shown). Nonetheless, we were concerned that delivery of pyruvate to the tumor might be impaired by treatment and thus contribute to the observed metabolic effect. To further validate the direct metabolic effect of imatinib on tumor cells, independent of tumor vasculature and systemic substrate delivery, we studied the fate of hyperpolarized 13C-pyruvate in PC-3MM2 cells encapsulated into agarose beads and maintained in a perfusion system. In control cells, PDGF signaling was associated with substantial conversion of hyperpolarized pyruvate into lactate whereas inhibition of the PDGF-activated signaling with imatinib resulted in a 40±21% decrease in maximum lactate signal (Fig 4; n=3; p=0.024). This decrease in lactate signal is in line with our results in-vivo, indicating that the metabolic effect of imatinib is not simply due to impaired substrate delivery but can mostly be attributed to a direct effect on the tumor cells.
Fig 4
Fig 4
In-vitro 13C MRS of metabolism of hyperpolarized pyruvate confirming reduced lactate signal in response to treatment
Imatinib-blockade of cell-signaling reduces expression and activity of LDH
Next we wanted to investigate more closely the reason for the change in lactate signal. The enzymatic pyruvate-to-lactate conversion by LDH is bi-directional and rapidly reaches dynamic steady state. The decrease in lactate signal observed with 13C MRS(I) upon treatment could reflect a decrease in the amount of enzyme (LDH), endogenous substrates (pyruvate and lactate), the required coenzyme (NADH) (14)or could be affected by the rate of pyruvate trans-membrane transport via the monocarboxylate transporter 1 (MCT1) (34) and other MCTs.
In another experimental system, chemotherapy-induced apoptosis resulted in a drop in hyperpolarized lactate due to activation of poly(ADPribose) polymerase which leads to depletion of NADH (14, 35). However, using immunostaining of tumor sections with the apoptotic marker cleaved caspase-3 we detected very low levels of apoptosis in both control and treated tumors (Fig 5a), and the total NAD(H) pool dropped slightly, but not significantly, from 2.30±0.09 to 1.78±0.76 µmoles NADH per g of tissue protein (p=0.16). Furthermore, we did not detect a change in MCT1 expression (data not shown).
Fig 5
Fig 5
Decrease in expression and activity of LDH-A in response to treatment
In contrast, staining for LDH-A showed a high level of enzyme expression at the outer rim of untreated tumors, and dramatically lower levels in treated tumors (Fig 5a). Immunoblotting of tissue extracts further confirmed that cleaved caspase-3 was below detection level in all treatments while LDH-A was elevated in controls and reduced following treatment (Fig 5b, Fig S4). In addition we evaluated LDH enzymatic activity in tumor lysates in an assay independent of trans-membrane transport and levels of endogenous substrate showing that treatment reduced the LDH tissue Vmax by 42±19% (p=0.014) relative to controls (Fig 5c), consistent with a drop in tissue enzyme level.
Taken together, these results demonstrate that imatinib affects tumor metabolism mostly by modulating LDH expression and its enzymatic activity.
Vascular and metabolic effects of imatinib are associated with reduced activity of HIF-1α and expression of c-Myc
The concurrent vascular and metabolic response might suggest that both are mediated by the same factor(s) downstream of PDGFR signaling. One possible regulator is the hypoxia inducible transcription factor, HIF-1, that regulates many angiogenic factors and glycolytic enzymes including VEGF, carbonic anhydrase IX (CAIX), and LDH-A (3638). Another transcription factor highly involved in regulation of tumor cell metabolism including LDH expression, and potentially involved in tumor angiogenesis, is c-Myc (37, 3941). In our study we detected high immunostaining for cell surface CAIX (which serves as a sensitive indicator of HIF-1 activity (38)) and for nuclear c-Myc in control tumors, and a much lower level of staining in treated tumors (Fig 6a). Immunoblotting of tumor extracts also indicated a decreasing trend in HIF-1α expression and HIF-1 transcriptional activity (probed with CAIX) and a significant drop in c-Myc in treated tumors (p=0.008; Fig 6b, Fig S4). These findings indicate that the metabolic effects of imatinib, inhibiting cell-signaling, correlates with expression and or activation of both transcription factors HIF-1α and c-Myc.
Fig 6
Fig 6
Vascular and metabolic response involves changes in HIF-1 and c-Myc
Tumor cells with high expression of c-Myc were reported to depend on glutamine uptake and glutaminolysis for survival and growth (42, 43). Accordingly, we detected elevated levels of glutaminase in untreated tumors and a decrease in glutaminase expression following treatment (Fig S4). We also observed a drop in glutaminase levels following treatment with imatinib of cells activated with PDGF (Fig S4). These changes followed the pattern observed for LDH-A and c-Myc (Fig 5, Fig 6). Imaging the glutamine to glutamate conversion using hyperpolarized glutamine (23) could thus provide an additional approach for monitoring PDGFR inhibition. We were not successful in detecting this conversion either in-vivo, in encapsulated cells or in cell lysates, but this method could prove useful in other systems.
In this study we have investigated the consequences of signal inhibition with imatinib in an in-vivo tumor model with elevated PDGFR signaling. We describe the metabolic consequences of treatment as detected by hyperpolarized 13C MRSI, as well as their underlying mechanism. Proliferation of cancer cells and tumor growth are often termed uncontrolled or disregulated. However, signaling pathways and transcriptional networks tightly regulate cellular metabolism in both quiescent and proliferating cells. As more pieces of the intracellular machinery puzzle fall into place, it appears that proliferation of cancer cells requires a switch to a metabolic program that provides sufficient energy while channeling precursors for the biosynthesis of macromolecules needed for cell doubling (3). The metabolic switch that supports proliferation can be triggered by extracellular stimuli such as growth factors, cytokines and stress conditions, or by various mutations that result in the continuous activation of signaling pathways. Thus, while many tumors switch to aerobic glycolysis, the trigger for this metabolic switch may vary.
Identifying the tumorigenic trigger and detecting the metabolic consequences could identify targets for drug design and provide powerful diagnostic tools. BCR-ABL1 and mutated c-KIT serve as such triggers in CML and GIST, leading to constitutively active tyrosine kinases. The prototype of targeted drugs, imatinib, was first designed to target BCR-ABL1 (6), but later its high efficacy in inoperable and metastatic GIST patients was demonstrated using FDG-PET (7, 9). PET is a highly sensitive diagnostic tool and when used with FDG can inform on glucose uptake. However, due to radiation exposure, there is concern in using this approach for long-term longitudinal studies of treated patients. In addition, FDG-PET might have limited diagnostic value for tumor detection in brain and prostate cancers as a result of the high glucose uptake in normal brain and the relatively low uptake of glucose in prostate tumors (44, 45). MRSI on the other hand, involves no ionizing radiation and provides straightforward co-registration with anatomical images. Used with hyperpolarized substrates, 13C MRSI is emerging as a novel and promising diagnostic tool, with the ability to detect the metabolic fluxes of a variety of substrates (13, 23, 46, 47) in multiple organs, including in brain and prostate cancers (48, 49). As we have shown here, the metabolic effects of signaling inhibition can be detected by this technique when used to monitor the metabolism of pyruvate. Detection of metabolic changes within 2 days is comparable to the time frame for a change in FDG uptake in imatinib-treated GIST patients. This was predictive of therapeutic outcome and exceeded by far (weeks) the time needed to detect changes in tumor size (9). Similarly, several weeks were required to achieve significant growth inhibition in PC-3MM2 tumors treated with imatinib relative to control (28) but as shown here 2 days of treatment lead to hyperpolarized 13C MRSI-detectable metabolic changes, suggesting that this method could prove predictive of clinical outcome in patients treated with various RTK inhibitors.
The metabolic effect of imatinib involved decreased production of hyperpolarized lactate. Decreased hyperpolarized lactate was also detected in response to the chemotherapeutic drug etoposide (14, 35). However, the cause of the metabolic change is likely different due to the different mechanisms of the two drugs. Etoposide was reported to induce apoptosis and necrosis leading to depletion of the coenzyme (NADH) pool and consequently to a decrease in the apparent pyruvate-to-lactate flux through LDH (14, 35). In contrast, we found no evidence of treatment-induced apoptosis in our model. Similarly, whereas we have not investigated all MCTs, we found no convincing evidence in our model for changes in the level of MCT1, which was recently suggested as a rate-limiting step in conversion of hyperpolarized pyruvate to lactate (34). Instead, we detected a decrease in LDH expression and a drop in LDH activity in tumor extracts in an assay independent of tissue NADH or substrate transport rate. Thus our mechanistic findings reflect the difference between chemotherapy-induced cell death, and signal inhibition resulting in growth inhibition.
In addition to the metabolic effect, imatinib also induced vascular effects as demonstrated here and previously (16, 28). We found that the metabolic and vascular effects of PDGFR signaling inhibition are likely mediated by two transcription factors, HIF-1 and c-Myc. Both transcription factors are induced by the PI3K/AKT pathway and possibly other Ras and Src-dependent signaling pathways (50, 51) downstream to RTKs. The role of HIF-1 in regulating glycolysis and angiogenesis is well established (36) and includes control over LDH and VEGF expression. Myc is also known for regulation of metabolism and recent publications indicate its crucial role in developmental and tumor angiogenesis, involving expression of VEGF and release of VEGF sequestered in the extracellular matrix (37, 3941). Under physiologic conditions, HIF-1 inhibits normal Myc activity but Myc over-expression in tumors may overcome this inhibition such that HIF-1 and Myc cooperate to promote tumor growth (37, 39, 52). Thus both HIF-1 and Myc can promote glycolysis and divert pyruvate away from the mitochondria by inducing LDH. In addition, Myc also promotes the TCA cycle and maintains the anaplerotic flux by inducing glutaminase expression and glutamine metabolism (43, 53). Accordingly we found that glutaminase expression showed the same dependence on PDGFR signaling and c-Myc transcriptional activity as LDH.
To summarize, we found that the metabolic consequences of imatinib treatment in PDGFR-expressing prostate cancer bone metastasis can be detected by monitoring the pyruvate-to-lactate conversion using hyperpolarized 13C MRSI within 2 days of treatment. Our results indicate that monitoring aerobic glycolysis using 13C MRSI with hyperpolarized pyruvate is a promising technique that could potentially detect the molecular effect of various emerging therapies that target cell-signaling, and thus provide a radiation-free method to longitudinally assess tumor response before detectable changes in tumor size can be observed.
Supplementary Material
Acknowledgments
Financial support: This work was supported by Department of Defense Prostate Cancer Research Programs grant PC060032, and NIH grants R01-CA130819, R01-EB007588 and R01-EB004453, and UC Discovery grant ITL-BIO04-10148, in conjunction with GE Healthcare.
Other notes: Data for this study were acquired in part at the Nikon Imaging Center at UCSF/QB3. We would like to thank Lynn DeLosSantos, Dr. Robert Bok, Kristen R. Scott, and Loretta Chan for technical support and Dr. Tal Raz for help with statistical analysis.
Footnotes
Potential conflict of interest: SMR and DBV acknowledge funding from GE Healthcare.
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