INTRODUCTION:

Kinase inhibitors are at the forefront of advances in melanoma therapy. Studies have suggested that concurrent inhibition of the BRAF kinases and MEK of the MAPK pathway could decrease MAPK-driven acquired resistance, resulting in a longer duration of responses observed from paradoxical MAPK pathway activation with BRAF inhibitor monotherapy.¹ Both BRAF and MEK genes are closely related, so drugs that are targeted to BRAF can also help treat melanoma with MEK mutations.¹ Our approach is to combine a BRAF inhibitor (dabrafenib) with a MEK inhibitor (trametinib) in two metabolically different melanoma xenograft models, DB-1 and WM983B. This combination has been shown to be more effective than the use of either drug alone.¹ Our fundamental hypothesis is that ¹H and ³¹P MRS will lead to much earlier reliable detection of therapeutic response, recurrence, or resistance, independent of changes in tumor volume. Differences in relative levels of glycolysis may produce differential therapeutic responses to BRAF and MEK inhibitors in melanomas.²

METHODS:

DB-1 and WM983B human melanoma cells were grown with DMEM supplemented to 25 mM glucose, 2 mM glutamine, 10 mM HEPES, 100 Units/mL penicillin, 100 µg/mL streptomycin, and 10% FBS. 10 x 10⁶ cells/ml and inoculated subcutaneously in each mouse with 0.1mL suspension. ³¹P and ¹H MRS experiments were performed on DB-1 (n=3) and WM983B (n=3) melanoma xenografts after treatment with dabrafenib and trametinib alone and in combination. MRS experiments were performed on a 9.4 T Bruker magnet using a homemade ¹H/³¹P dual tuned coil. To prepare tumor-bearing mice for MRS experiments, 1% isoflurane in 1 L/min oxygen was used to anesthetize the mice. To monitor respiration and core temperature, a respiration pillow and a rectal thermistor were used, respectively. Mouse core temperature was maintained at 37 ± 1°C by blowing warmed air into the bore of the magnet with heating controlled by a thermal regulator system. (3-Aminopropyl)phosphonate (3-APP) (300 mg/mL solution in water) was injected exogenously into the peritoneum of the mouse before putting the animal in the magnet to measure the extracellular pH (pHe).³ For ¹H MRS, a slice-selective, double-frequency, Hadamard-selective, multiple quantum coherence transfer pulse sequence was used to detect lactate and to filter out overlapping lipid signals.⁴ Intracellular pH (pHi), pHe, bioenergetics (βNTP/Pi), lactate and alanine concentration were measured using ³¹P and ¹H MRS, respectively, on Day 0 (pre-), Day 2 and Day 5 (post-) treated with dabrafenib (30 mg/kg; oral), trametinib (10 mg/kg; oral) and dabrafenib plus trametinib (similar dose) using methods described elsewhere.³ Tumor volumes were measured using calipers. An independent paired t-test was performed for statistical analysis using SPSS 20. A p-value ≤ 0.05 was considered significant.

RESULTS:

Dabrafenib treatment produced a sustained significant change in pHi at Day 2 (p=0.031) and Day 5 (p=0.024) compared to Day 0 (baseline) in DB-1 melanoma xenografts (Figure 1). We observed a significant change in pHi at Day 2 (p<0.001) only compared to baseline in WM983B xenografts (Figure 1). However, pHe produced significant change at Day 2 (p=0.032) and Day 5 (p=0.017) compared to baseline in DB-1 and WM983B, respectively (Figure 1). We did not observe any significant change in bioenergetics (βNTP/Pi) after treatment with dabrafenib in either of the melanoma models (Figure 1). Furthermore, we observed a significant change in the level of total lactate at Day 2 (p=0.027), Day 5 (p=0.012) compared to baseline, and between Day 2 and Day 5 (p=0.018) (Figure 2).
Trametinib treatment produced a sustained significant change in pHe at Day 2 (p=0.018) compared to baseline in DB-1 melanoma xenografts only (Figure 1). We observed a significant change in bioenergetics (βNTP/Pi) after treatment with trametinib in DB-1 melanoma model at Day 2 (p=0.017) compared to baseline (Figure 1). We observed a significant change in the level of total lactate (p=0.003) and alanine (p=0.048) at Day 5 compared to baseline in DB-1 (Figure 2).
Dabrafenib plus Trametinib treatment produced a significant change in pHi at Day 2 compared to Day 5 (p=0.006) in DB-1 (Figure 1); however, we observed a significant change in the level of total lactate (p=0.018) at Day 5 compared to baseline in DB-1 (Figure 2). We observed a decrease in tumor volume after treatment with dabrafenib, trametinib and dabrafenib plus trametinib in both melanoma models (Figure 3).

DISCUSSION:

Because DB-1 melanoma models are inherently more glycolytic than WM983B, as evident from lactate levels (Figure 2 A), we predict that BRAF and MEK inhibitors should induce more response in DB-1 compared to WM983B. This is indeed what we observed. At least conceptually, this model has the potential for translation to clinical settings. Notably, we now have instruments and methodologies to monitor tumor metabolism and energetics non-invasively. Bioenergetics measurements could form the basis of predictions about the response of the tumor to an energetically demanding treatment. It is reasonable to think that information about metabolism could also be highly useful in monitoring and predicting response to other modalities, such as BRAF and MEK inhibitors and immunotherapy. Future studies are needed to illuminate the nature of the link between the observed changes with a bigger sample size.

CONCLUSION:

Differences in the predominance of glycolysis may explain differential therapeutic responses between DB-1 and WM983B melanomas.

Acknowledgements

NIH 1R01CA250102-01, 1R01CA228457-01A1