Synopsis
This study demonstrated that diffusion weighted HP 13C MRI
can provide an estimate of the amount of extra- versus intracellular HP 13C
lactate based on its apparent diffusion coefficient (ADC). In metastatic
renal cell carcinoma, a large portion of the HP 13C lactate signal
arises from an extracellular lactate pool, based on reliable estimates of ADC in the same cell line in a the MR compatible bioreactor.
The juxtaposition of cells in bioreactor and the in vivo animal model is a powerful tool
for interpretation of the hyperpolarized ADC measurements. This unique
combination can be further extended to investigate the relationship between lactate
transport and tumor metastatic potential.Aim
The up-regulation of
aerobic glycolysis and lactate production and efflux is an adaptation of cancer
cells that aids in tumor survival, growth and metastasis1. Prior
publications have consistently demonstrated significantly elevated hyperpolarized
(HP) [1-
13C]lactate levels in cancer2, however the relative
amounts of intra- and extracellular HP lactate that contributes to the observed
in vivo signal has not been determined.
Aggressive renal cell carcinomas (RCCs) are tumors that exemplify the Warburg
effect with both high lactate production and rapid lactate export. The goal of
this study was to determine if diffusion weighted (DW) HP
13C MR, a clinically
translatable technique
1-3, could provide an estimate of the amount of extracellular versus
intracellular HP
13C lactate based on its apparent diffusion
coefficient (ADC) in a RCC murine model. This was accomplished using a
combination of ex vivo MR compatible 3D cell culture bioreactor and in
vivo orthotopic murine model
studies of the same RCC cell line.
Methods
UOK262
cells, a model of metastatic RCCs, were used as described before
3. Ex
vivo: alginate-encapsulated UOK262 cells
in bioreactor were studied on the 14.1T Varian INOVA with 100 G/cm gradients. A
pulsed gradient double spin echo sequence was used for all hyperpolarized
13C
diffusion experiments with δ=10ms, Δ=30ms, and a diffusion weighting of 3 to
15,000 s/mm
2 (Gx or Gy). Dynamic data (30°
pulses, 3s interval for 300s) after HP [1-13C]pyruvate infusion
(16µmols) were acquired. In vivo: Immune compromised mice implanted with UOK262
cells under the renal capsule were used for DW imaging with a spectrally and
spatially selective 30° RF pulse for 8mm thick slice and 2x2mm in–plane
resolution with 4 b-values (25-4000 s/mm
2). Respiratory gating (two
b-values/breath) was used to minimize signal loss from bulk motion.
Results
Ex vivo: Figure.1a shows
a plot of HP [1-
13C]pyruvate signal versus b-value (0-1500 s/mm
2) from two MR compatible bioreactor
studies. In the first study the bioreactor contains cell-free alginate microspheres
(blue squares), and co-polarized [1-
13C]pyruvate and [1-
13C]lactate are injected. In the second study,
the bioreactor contains UOK262 cell-laden alginate microspheres (red squares)
and only hyperpolarized pyruvate is injected. The HP pyruvate signal from the
bioreactor containing UOK262 cells reveals a bi-exponential signal decay, with the
fast decay constant being the same as that of the cell-free bioreactor study,
and the slow decay constant being attributed to restricted intracellular
diffusion. Figure.1b shows
representative HP
13C MR spectra obtained from the same bioreactor
experiments at 3 increasing b-values (left to right). In the cell free study, we observe a complete
loss of HP lactate and pyruvate signal at the highest b-value, whereas in the
UOK262 cell study, HP and pyruvate signals are still visible. This is attributed to the shorter
intracellular ADC. The extra- and intracellular ADC calculated for lactate and
pyruvate in cell-free alginate microspheres and UOK262 cells, respectively, are
listed in Table 1. Figure.2 shows a representative bioreactor study containing
UOK262 cells after injection of HP pyruvate in which alternating low and high
b-values (2.4 and 3863 s/mm
2)
were applied over time. This allowed for
the detection of total HP lactate pool (low b-value) and the predominately
intracellular pool (high-b value), and the calculation of the extra cellular
pool (difference).
In vivo: Mice with orthotopic
UOK262 tumors were imaged by DW HP pyruvate MRI (4 b-values) when tumor volumes
reached at least 0.2cc. DW HP signals were corrected for RF utilization and fit
voxel-wise to a monoexponential decay S(b)=S
0e
-bD
to compute the ADC map of lactate. We observe a lactate ADC in the tumor of 0.709 ± 0.15, (n=4).
Discussion and Conclusion
Discussion and Conclusion: We show that, in the bioreactor, intracellular
and the extracellular HP lactate ADC can be measured simultaneously and
dynamically. The intracellular ADC value of lactate determined using HP
13C
is similar to that measured thermally using proton spectroscopy
5. Additionally, the dynamic measurement
of the lactate production and efflux was feasible using HP
13C DW
spectroscopy in the bioreactor. These studies demonstrated that lactate efflux
occurred almost instantaneously with lactate production, similar to recent
detection of extracellular HP
13C lactate using chemical shift
separation approach
6,7.
The dynamically resolved intra- and extracellular lactate pools obtained
after injection of HP pyruvate in the UOK262 cell bioreactor studies demonstrated
that ~60% of the total HP lactate signal was extracellular during the time
frame of the hyperpolarized MR acquisition. Based on the ex vivo intra- and extracellular lactate ADC values, and the measured
in vivo ADC value of ≈ 0.7 mm2/s,
≈ 60% of the HP lactate signal arose from extracellular lactate in UOK262 orthotopic tumors.
Acknowledgements
Dave
Korenchan, Justin DeLos Santos, Ailin Hansen, Jinny Sun, Jessie Lee and Romelyn
DeLos Santos
Grants: P41-EB013598 (JK, DV), R01 CA166655 (JK) and DoD
CA110032 (RS), Department of Defense Peer Reviewed
Cancer Research Concept Award (ZJW), Radiological Society of North America Scholar grant (ZJW).
References
1 B. L.
Koelsch, G. D. Reed, K. R. Keshari, M. M. Chaumeil, R. Bok, S. M. Ronen, D. B.
Vigneron, J. Kurhanewicz and P. E. Z. Larson, Magn Reson Med, 2014.
2 M. I.
Kettunen, B. W. C. Kennedy, D.-E. Hu and K. M. Brindle, Magn Reson Med,
2012.
3 F.
Schilling, S. Düwel, U. Köllisch, M. Durst, R. F. Schulte, S. J. Glaser, A.
Haase, A. M. Otto and M. I. Menzel, NMR Biomed., 2013, 26,
557–568.
4 P. C. Van
Zijl, C. T. Moonen, P. Faustino, J. Pekar, O. Kaplan and J. S. Cohen, Proc.
Natl. Acad. Sci. U.S.A., 1991, 88, 3228–3232.
5 J. Pfeuffer,
J. C. Lin, L. Delabarre, K. Ugurbil and M. Garwood, J Magn Reson, 2005, 177,
129–138.
6 V. Breukels,
K. C. F. J. Jansen, F. H. A. van Heijster, A. Capozzi, P. J. M. van Bentum, J.
A. Schalken, A. Comment and T. W. J. Scheenen, NMR Biomed., 2015, 28,
1040–1048.
7 R. Sriram,
M. Van Criekinge and A. Hansen, NMR Biomed, 2015.