RESUMEN
BACKGROUND: We recently showed improved between-subject variability in our [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) experiments using a Michaelis-Menten transport model to calculate the metabolic tumor glucose uptake rate extrapolated to the hypothetical condition of glucose saturation: MRglucmax=Ki*(KM+[glc]), where Ki is the image-derived FDG uptake rate constant, KM is the half-saturation Michaelis constant, and [glc] is the blood glucose concentration. Compared to measurements of Ki alone, or calculations of the scan-time metabolic glucose uptake rate (MRgluc = Ki * [glc]) or the glucose-normalized uptake rate (MRgluc = Ki*[glc]/(100 mg/dL), we suggested that MRglucmax could offer increased statistical power in treatment studies; here, we confirm this in theory and practice. METHODS: We compared Ki, MRgluc (both with and without glucose normalization), and MRglucmax as FDG-PET measures of treatment-induced changes in tumor glucose uptake independent of any systemic changes in blood glucose caused either by natural variation or by side effects of drug action. Data from three xenograft models with independent evidence of altered tumor cell glucose uptake were studied and generalized with statistical simulations and mathematical derivations. To obtain representative simulation parameters, we studied the distributions of Ki from FDG-PET scans and blood [glucose] values in 66 cohorts of mice (665 individual mice). Treatment effects were simulated by varying MRglucmax and back-calculating the mean Ki under the Michaelis-Menten model with KM = 130 mg/dL. This was repeated to represent cases of low, average, and high variability in Ki (at a given glucose level) observed among the 66 PET cohorts. RESULTS: There was excellent agreement between derivations, simulations, and experiments. Even modestly different (20%) blood glucose levels caused Ki and especially MRgluc to become unreliable through false positive results while MRglucmax remained unbiased. The greatest benefit occurred when Ki measurements (at a given glucose level) had low variability. Even when the power benefit was negligible, the use of MRglucmax carried no statistical penalty. Congruent with theory and simulations, MRglucmax showed in our experiments an average 21% statistical power improvement with respect to MRgluc and 10% with respect to Ki (approximately 20% savings in sample size). The results were robust in the face of imprecise blood glucose measurements and KM values. CONCLUSIONS: When evaluating the direct effects of treatment on tumor tissue with FDG-PET, employing a Michaelis-Menten glucose correction factor gives the most statistically powerful results. The well-known alternative 'correction', multiplying Ki by blood glucose (or normalized blood glucose), appears to be counter-productive in this setting and should be avoided.
RESUMEN
BACKGROUND: The BRAF inhibitor, vemurafenib, has recently been approved for the treatment of metastatic melanoma in patients harboring BRAFV600 mutations. Currently, dual BRAF and MEK inhibition are ongoing in clinical trials with the goal of overcoming the acquired resistance that has unfortunately developed in some vemurafenib patients. FDG-PET measures of metabolic activity are increasingly employed as a pharmacodynamic biomarker for guiding single-agent or combination therapies by gauging initial drug response and monitoring disease progression. However, since tumors are inherently heterogeneous, investigating the effects of BRAF and MEK inhibition on FDG uptake in a panel of different melanomas could help interpret imaging outcomes. METHODS: 18 F-FDG uptake was measured in vitro in cells with wild-type and mutant (V600) BRAF, and in melanoma cells with an acquired resistance to vemurafenib. We treated the cells with vemurafenib alone or in combination with MEK inhibitor GDC-0973. PET imaging was used in mice to measure FDG uptake in A375 melanoma xenografts and in A375 R1, a vemurafenib-resistant derivative. Histological and biochemical studies of glucose transporters, the MAPK and glycolytic pathways were also undertaken. RESULTS: We demonstrate that vemurafenib is equally effective at reducing FDG uptake in cell lines harboring either heterozygous or homozygous BRAFV600 but ineffective in cells with acquired resistance or having WT BRAF status. However, combination with GDC-0973 results in a highly significant increase of efficacy and inhibition of FDG uptake across all twenty lines. Drug-induced changes in FDG uptake were associated with altered levels of membrane GLUT-1, and cell lines harboring RAS mutations displayed enhanced FDG uptake upon exposure to vemurafenib. Interestingly, we found that vemurafenib treatment in mice bearing drug-resistant A375 xenografts also induced increased FDG tumor uptake, accompanied by increases in Hif-1α, Sp1 and Ksr protein levels. Vemurafenib and GDC-0973 combination efficacy was associated with decreased levels of hexokinase II, c-RAF, Ksr and p-MEK protein. CONCLUSIONS: We have demonstrated that 18 F-FDG-PET imaging reflects vemurafenib and GDC-0973 action across a wide range of metastatic melanomas. A delayed post-treatment increase in tumor FDG uptake should be considered carefully as it may well be an indication of acquired drug resistance. TRIAL REGISTRATION: ClinicalTrials.gov NCT01271803.
RESUMEN
BACKGROUND: A retrospective analysis of estimates of tumor glucose uptake from 1,192 dynamic 2-deoxy-2-(18F)fluoro-D-glucose-positron-emission tomography [FDG-PET] scans showed strong correlations between blood glucose and both the uptake rate constant [Ki] and the metabolic rate of glucose [MRGluc], hindering the interpretation of PET scans acquired under conditions of altered blood glucose. We sought a method to reduce this glucose bias without increasing the between-subject or test-retest variability and did this by considering that tissue glucose transport is a saturable yet unsaturated process best described as a nonlinear function of glucose levels. METHODS: Patlak-Gjedde analysis was used to compute Ki from 30-min dynamic PET scans in tumor-bearing mice. MRGluc was calculated by factoring in the blood glucose level and a lumped constant equal to unity. Alternatively, we assumed that glucose consumption is saturable according to Michaelis-Menten kinetics and estimated a hypothetical maximum rate of glucose consumption [MRGlucMAX] by multiplying Ki and (KM + [glucose]), where KM is a half-saturation Michaelis constant for glucose uptake. Results were computed for 112 separate studies of 8 to 12 scans each; test-retest statistics were measured in a suitable subset of 201 mice. RESULTS: A KM value of 130 mg/dL was determined from the data based on minimizing the average correlation between blood glucose and the uptake metric. Using MRGlucMAX resulted in the following benefits compared to using MRGluc: (1) the median correlation with blood glucose was practically zero, and yet (2) the test-retest coefficient of variation [COV] was reduced by 13.4%, and (3) the between-animal COVs were reduced by15.5%. In statistically equivalent terms, achieving the same reduction in between-animal COV while using the traditional MRGluc would require a 40% increase in sample size. CONCLUSIONS: MRGluc appeared to overcorrect tumor FDG data for changing glucose levels. Applying partial saturation correction using MRGlucMAX offered reduced bias, reduced variability, and potentially increased statistical power. We recommend further investigation of MRGlucMAX in quantitative studies of tumor FDG uptake.
