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Dynamic Imaging of Emerging Resistance during Cancer Therapy

Departments of ¹ Biological Chemistry, ² Radiology, ³ Biostatistics, and ⁴ Radiation Oncology and ⁵ Center for Molecular Imaging, University of Michigan Medical School; ⁶ MIR Preclinical Services, Ann Arbor, Michigan; and ⁷ Roswell Park Cancer Institute, Buffalo, New York

Requests for reprints: Brian D. Ross, University of Michigan Medical School, Kresge II, 200 Zina Pitcher Place, Ann Arbor, MI 48109. Phone: 734-763-2099; Fax: 734-763-5447; E-mail: bdross{at}umich.edu.

	Abstract

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One of the greatest challenges in developing therapeutic regimens is the inability to rapidly and objectively assess tumor response due to treatment. Moreover, tumor response to therapeutic intervention in many cases is transient, and progressive alterations within the tumor may mask the effectiveness of an initially successful therapy. The ability to detect these changes as they occur would allow timely initiation of alternative approaches, maximizing therapeutic outcome. We investigated the ability of diffusion magnetic resonance imaging (MRI) to provide a sensitive measure of tumor response throughout the course of treatment, possibly identifying changes in sensitivity to the therapy. Orthotopic 9L gliomas were subjected to two separate therapeutic regimens, with one group receiving a single 5-day cycle (1) of low-dose 1,3-bis(2-chloroethyl)-1-nitrosourea (BCNU) and a second group receiving two cycles at the same dose, bisected with 2 days of rest (2). Apparent diffusion coefficient maps were acquired before and throughout treatment to observe changes in water mobility, and these observations were correlated to standard measures of therapeutic response and outcome. Our results showed that diffusion MRI was indeed able to detect the emergence of a drug-resistant tumor subpopulation subsequent to an initially successful cycle of BCNU therapy, leading to minimal gains from a second cycle. These diffusion MRI findings were highly correlated with tumor growth delay, animal survival, and ex vivo growth inhibition assays showing emerging resistance in excised tumors. Overall, this study highlights the ability of diffusion MRI to provide sensitive dynamic assessment of therapy-induced response, allowing early opportunities for optimization of therapeutic protocols. (Cancer Res 2006; 66(9): 4687-92)

	Introduction

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Although advances in therapeutic intervention, such as surgical techniques, radiation therapy, and chemotherapy, have provided some success in managing brain neoplasms, the prognosis for highly aggressive tumors, such as glioblastoma multiforme, is still poor, with a median survival time of 9 months, and only 5% to 10% of patients surviving past 2 years (1). Both neuroresection and radiotherapy have proven to be effective methods in treating gliomas; however, adjuvant chemotherapy has yielded mixed results and is still a subject of controversy (2). Studies have shown that tumors consist of subpopulations, which exhibit variable characteristics, growth rates, and drug sensitivities (3–5), which may account for variable and unpredictable response to chemotherapy. Even with optimal tumor response, there is a high rate of tumor recurrence of increased malignancy, which is frequently refractory to further treatment. A number of studies suggest that the treatment-refractory nature of these recurrences could result from previous chemotherapy (6–8). With tumors being such a dynamic entity, optimal therapeutic benefit presumably would require proficient management of the therapeutic regimen to account for these changes. This would require early, sensitive, and progressive assessment of therapeutic response.

Diffusion magnetic resonance imaging (MRI) has emerged as a powerful tool that has garnered attention as a quantitative approach for assessment of tumor response to therapeutic intervention (9). This technique exploits water mobility within tissues as a biomarker that highly correlates with cellularity (10–12). Destruction of tumor cells in response to therapy leads to a change in water mobility that is detectable by diffusion MRI. Moreover, these microscopic changes in the diffusibility of water occur well in advance of currently used macroscopic indicators of tumor status, such as changes in volume, performance status, or survival. Our studies, among others, have shown the capability of this approach to provide sensitive and rapid prospective assessment of therapeutic response, which has proven to be invaluable in the evaluation and development of experimental therapies (9, 12–18).

In this study, we employed the well-characterized orthotopic 9L glioma model as a system to evaluate therapeutic response to different 1,3-bis(2-chloroethyl)-1-nitrosourea (BCNU) dosing regimens. Historically, this model has been shown to be an effective system for preclinical evaluation of therapeutic strategies, including BCNU. This study focused on the ability of diffusion MRI to provide a quantitative comparison of therapeutic response between subjects given either one 5-day cycle of BCNU given at 2 mg/kg/d (1), or two similar cycles of BCNU therapy separated by a 2-day rest period (2). Our results showed that not only did diffusion MRI provide an early prediction of therapeutic outcome, but was also sensitive enough to immediately detect the loss of therapeutic response to BCNU. These results were shown to correlate with survival and with ex vivo determination of the emergence of drug resistance in the treated tumors. These findings show that diffusion MRI is an effective tool for dynamic assessment of the dynamic changes in the sensitivity of a tumor to fractionated therapy.

	Materials and Methods

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9L animal models. Rat 9L glioma cells were obtained from the Brain Tumor Research Center at the University of California at San Francisco. The cells were grown as monolayers in 10-cm² sterile plastic flasks in DMEM with 10% fetal bovine serum, 100 IU/mL penicillin and 100 mg/mL streptomycin, and 2 mmol/L L-glutamine in an incubator held at 37°C and 95%/5% air/CO₂ atmosphere. Before implantation, cells were harvested by trypsinization, counted, and resuspended in serum-free medium for injection.

Intracerebral tumor implantation was done as previously described (19). Male Fischer 344 (Harlan Sprague-Dawley, Indianapolis, IN) rats weighing between 125 and 150 g were anesthetized with a ketamine/xylazine mixture given i.p. A small skin incision was made over the right hemisphere, and a 1-mm-diameter burr hole was drilled through the skull. A 5-µL suspension containing 1 x 10⁵ 9L cells was injected through the burr hole to a depth of 3 mm. The surgical field was then cleaned with 70% ethanol, and the burr hole was filled with bone wax to prevent extracerebral extension of the tumor. Surgical staples were then applied to the incision to seal the open incision.

For treatment, BCNU was dissolved in absolute ethanol and diluted in saline at the time of treatment. Animals were subdivided into three groups. The 1 group (n = 5) received a total of 10 mg/kg BCNU fractionated into 2 mg/kg doses given by daily i.p. injections for 5 days. The 2 group (n = 17) received a total of 20 mg/kg BCNU fractionated into 2 mg/kg daily doses for 5 days, given 2 days of rest, and then five more 2 mg/kg daily i.p. injections. Lastly, control animals with 9L tumor implants (n = 5) received injections of only vehicle (10% ethanol in saline) at volumes equivalent to treated groups for a complete 5-day cycle.

Diffusion MRI. Imaging was done every other day beginning 10 days after tumor cell implantation on a Varian Unity Inova system equipped with a 7.0-T, 18.3-cm horizontal bore magnet and a quadrature rat head coil (USA Instruments, Aurora, OH). For MRI examination, rats were anesthetized with an isofluorane/air mixture and maintained at 37°C inside the magnet using a heated animal bed. A single-slice sagittal spin-echo sequence was used to facilitate proper positioning of the animal. An isotropic, diffusion-weighed sequence (20) was employed with two interleaved b factors (b = 1,148 s/mm²) and the following acquisition variables: TR/TE = 3,500/60 ms, 128 x 128 matrix, and a 3-cm field of view. Thirteen 1-mm-thick slices separated by a 0.5-mm gap were used to cover the whole rat brain. The low b factor images (b = 100 s/mm²) were essentially T₂-weighed to allow tumor volume measurements, as previously described (19). Images were acquired before treatment and at 2-day intervals thereafter. Isotropic apparent diffusion coefficient (ADC) maps were calculated for each image set.

Functional diffusion map analysis. Magnetic resonance images following initiation of therapy were coregistered to the initial pretreatment diffusion map with an automated mutual information module (21). After coregistration, brain tumors were then manually contoured to define the region of interest. The diffusion maps within the tumor at days 4 and 8 were compared with the pretreatment values. Shrinkage or growth of the tumor during the time between scans may have occurred; therefore, only voxels that were present in both the pre-therapy and post-therapy tumor volumes were included. The tumor was further segmented into three different categories, yielding the functional diffusion maps (fDM) in which the red voxels represent areas within the tumor where ADC increased (>20 x 10^–3 mm²/s), the blue voxels represent a decreased ADC (<20 x 10^–3 mm²/s), and the green voxels represent regions within the tumor that were within these thresholds. Moreover, the percentages of red voxels (>20 x 10^–5 mm²/s) were calculated for each group.

Tumor growth delay. Tumor volumes were calculated from the low b factor images, as previously described, and were obtained every 2 days until cessation of the experiment. The mean time for the control group tumors to reach eight times the initial volume was determined. Subsequently, the mean time for tumors from each treatment group, 1 and 2, to reach eight times the initial pretreatment volume was also determined and subtracted by the mean time of the control group to obtain the tumor growth delay value. Tumor growth delay represents the difference in days for treated groups to reach eight times the initial volume compared with the control group.

In vitro cytotoxicity assays. Growth inhibition was evaluated using the sulforhodamine B assay as previously described (22). Briefly, 9L cells were seeded at a density of 4,000 per well in 96-well plates. After 24 hours, the cells were treated with serial dilutions of BCNU ranging from 200 to 0.1 µmol/L or vehicle in complete medium. Cells were allowed to grow until untreated cells reached confluence, at which time the cells were fixed and stained with sulforhodamine B (Sigma, St. Louis, MO). A microtiter plate reader was used to measure the absorbance at 490 nm (V_max; Molecular Devices, Sunnyvale, CA). Data plotted represent the mean and SD of 2 BCNU (n = 8) and vehicle controls (n = 2) with each cell line done in quadruplicate.

	Results

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Diffusion-weighed MRI detects cellular response to fractionated BCNU therapy. Representative serial ADC maps (color overlaid on anatomic image) of controls (vehicle only), 1- and 2-treated animals are shown in Fig. 1 . Pretreatment ADC maps were similar, indicating that the treatment groups were well matched for ADC values. However, whereas tumor diffusion of the control animals remained essentially unchanged over time, an appreciable increase in ADC was observable in the BCNU-treated animals over the first 6 days. Moreover, a progressive decrease in diffusion (shift towards blue) was observed in both 1 and 2 groups that started on day 8, which subsequently reached and remained at baseline until the end of the experiment. Interestingly, despite receiving a second cycle of BCNU therapy, the 2 group similarly decreased in diffusion as with the 1 group through qualitatively comparing representative images from each group. Visual comparison of the serial MRI images also qualitatively revealed a modest retardation of tumor growth rate in BCNU-treated animals compared with the vehicle control group.

View larger version (51K): [in this window] [in a new window]   Figure 1. Anatomic images with color ADC maps from representative tumors over course of therapy. Normalized quantitative color ADC maps overlays of representative vehicle control tumor (left), 1 group (middle), and 2 group (right) from days 0 to 14 of therapy. Color intensities are directly related to ADC values (ADC units of 1 x 10–3 mm2/s), with blue representing low diffusion and red representing high diffusion. The ADC value of the tumor in the control animal remained relatively constant throughout the study, whereas both 1 and 2 BCNU-treated tumors showed a much greater increase in tumor diffusion throughout treatment.

View larger version (11K): [in this window] [in a new window]   Figure 2. Mean ADC changes from serial acquisitions throughout therapy. Normalized ADC values from each group were plotted as a function of time. Arrows, 2 mg/kg BCNU injections, where the first cycle was given from days 0 to 4, and animals receiving a second cycle were injected from days 7 to 11. Changes in mean ADC of control groups remained fairly constant, where as both BCNU-treated groups showed a significant rise in ADC after the initial cycle of BCNU therapy. Note that animals receiving a second cycle of BCNU therapy showed a progressive decrease in ADC throughout the second course of BCNU therapy.

View larger version (27K): [in this window] [in a new window]   Figure 3. Scatter plots of tumor response using fDM analysis. Scatter plots were generated for representative animals from control (A and D), 1 group (B and E), and 2 group (C and F) at day 4 (A-C) and day 8 (D-F) to show the distribution of ADC (ADC units of 1 x 10–3 mm2/s) changes for the entire tumor volume. The red pixels indicate areas of increased diffusion, whereas the blue and green pixels indicate regions of decreased and unchanged ADC, respectively. For the control group, a minimal percentage of tumor voxels were found to have an increase in ADC at either day 4 (A) or day 8 (D). The 1 (B and E) and 2 (C and F) groups exhibited much larger increases that were statistically significant versus controls at day 4 (1, P < 0.05; 2, P < 0.05) and day 8 (1, P < 0.05; 2, P < 0.05). However, statistical significance was not achieved between the 1 and 2 groups at either day 4 (P > 0.3) or day 8 (P > 0.02).

Minimal therapeutic gain with 2 as compared with 1.

View larger version (8K): [in this window] [in a new window]   Figure 4. Kaplan-Meier survival curves. Kaplan-Meier survival curves for animal survival were determined as the time of survival from onset of therapy until animal death due to tumor burden. As shown in the curve, there was a significant survival advantage (P < 0.05) for both 1 (12.5 days) and 2 (13 days) fractionated BCNU-treated groups versus the vehicle control group (9 days). However, there was no significant survival advantage for animals receiving a second cycle of therapy (2) versus animals receiving only a single cycle (1; P > 0.4).

View larger version (10K): [in this window] [in a new window]   Figure 5. Sulforhodamine B growth inhibition assay for BCNU sensitivity. Cell lines were developed from excised 2 and vehicle control tumors and assayed for BCNU sensitivity. Using a previously described assay (Materials and Methods), cell lines were grown in varying BCNU concentrations ranging from 1 to 200 µmol/L and were then fixed to determine differences in total protein. A 2-fold shift in IC50 was observed in tumors from the 2 group (150.4 ± 1.9 and 73.8 ± 4.9 µmol/L, respectively).

	Discussion

Top Abstract Introduction Materials and Methods Results Discussion References

To test the use of diffusion MRI as a noninvasive, sensitive readout for optimization of dose and schedule of cancer therapy, we evaluated two separate schedules of BCNU therapy in an orthotopic 9L tumor model. In this study, diffusion MRI predicted initial therapeutic response, but more importantly, also detected a loss of tumor response during ongoing therapy. As shown in Fig. 2, there was a statistical difference in mean ADC change between BCNU-treated groups and control. However, comparison of the two treatment groups showed only slight differences in ADC profiles. The 1 group did have a more pronounced decline in ADC at the end of therapy compared with the 2 group, suggesting perhaps that a second cycle of therapy produced some level of tumor response. However, statistical significance of mean ADC change between the treated groups was never achieved throughout the course of the experiment. Nonetheless, this mirroring of ADC profiles between the 1 and 2 groups correctly predicted comparable tumor response. This provided the first indication that although the 2 group received a much higher total dose of BCNU, the more aggressive therapy did not lead to greater tumor cell death compared with the 1 group. Moreover, the decrease of ADC values in the 2 group before and throughout the second cycle of therapy indicated that the initial cycle of BCNU therapy altered tumor responsiveness to BCNU cytotoxicity during the second cycle.

fDM analysis of ADC change has been validated as an invaluable clinical tool for stratifying tumor response and predicting patient outcome in cases of primary brain neoplasms (29, 30). More importantly, the fDM approach provides an avenue to account for heterogeneity inherent of solid tumors and their response to therapy (23). Using this methodology, a quantitative assessment of therapeutic tumor response is obtained by measurements of the changes in regional fluctuations in ADC values within the whole tumor. In this study, we showed (Fig. 3; Table 1) that treated tumors displayed a significant tumor response versus controls, as evidenced by an increase of the tumor fraction with elevated ADC values. However, no statistical difference in tumor response, based on fDM analysis, was observed between the 1 and 2 groups at day 4 (P > 0.3). Moreover, at day 8, whereas therapy was still in progress for the 2 group, similar tumor response was observed between the 1 and 2 groups, suggesting that the second cycle of therapy provided minimal therapeutic benefit over tumors receiving only a single cycle.

Tumor growth delays and a Kaplan-Meier plot of animal survival were generated to ascertain the therapeutic value obtained from two cycles of BCNU therapy (2) versus a single cycle (1). As previously described, although treated groups showed a significant tumor growth delay compared with control tumors (1, 4.05 ± 0.25 days; 2, 3.55 ± 0.52 days), no significant difference was discernable between the 1 and 2 groups (P > 0.3). Moreover, as shown in Fig. 4, the 2 group exhibited negligible survival advantage compared with the 1 group, where median survival times were 13 and 12.5 days, respectively. This correlated with the diffusion data where a progressive decrease in mean ADC change during the second phase of therapy showed a decrease in cellular response to BCNU. Moreover, fDM analysis of treated tumors showed that the 1 and 2 groups had minimal differences in voxels of increased ADC at both days 4 and 8, thereby indicating that a second cycle of BCNU therapy did not provide an appreciable gain in tumor response. These findings reveal that diffusion MRI is effective as an early predictive biomarker for detection of diminished tumor response to a second cycle of BCNU therapy. This was confirmed by a lack in survival benefit of the 2 group over the 1 group.

With both diffusion MRI and animal survival studies indicating diminishing response of 2 tumors to BCNU therapy, we investigated whether BCNU-treated tumors did in fact acquire resistance to BCNU. Representative tumors from the 2 and vehicle control groups were excised, and cell lines were derived to establish BCNU sensitivity. Using a growth inhibition assay (22), we showed that BCNU-treated tumors were 2-fold more resistant to BCNU than control tumors with an IC₅₀ of 150.4 ± 1.9 versus 73.8 ± 4.9 µmol/L, respectively. These findings parallel previous reports documenting the development of BCNU-resistant 9L tumors induced by in vivo BCNU therapy (23, 31) and confirms that diffusion MRI predicted loss of tumor response over time, which corresponded to diminished therapeutic benefit.

In summary, this report shows that diffusion MRI can provide a rapid assessment of therapy-induced tumor response to fractionated BCNU as well as the dynamic detection of the emergence of resistance. The findings of this study provide an example of the potential for diffusion MRI to play a major role in the preclinical development of therapeutic regimens with dynamic assessment of therapeutic effect driving efficient optimization of treatment regimens within a single experiment, dramatically increasing the efficiency of preclinical experimentation. Moreover, the data presented also clearly points to the potential application of diffusion MRI technologies for dynamic optimization of therapeutic outcomes of individual patients in the clinic.

	Acknowledgments

 
Grant support: NIH/National Cancer Institute grants P01CA85878, R24CA83099, and P50CA093990.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received 9/ 7/05. Revised 12/13/05. Accepted 2/24/06.

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This Article Abstract Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Lee, K. C. Articles by Ross, B. D. Search for Related Content PubMed PubMed Citation Articles by Lee, K. C. Articles by Ross, B. D.