Abstract B37: Patient-derived tissue culture model systems of renal cell carcinoma for development of clinically translatable metabolic biomarkers

Aim: Renal cell carcinomas (RCCs) is a diverse group of tumors of varying aggressiveness. The development of noninvasive biomarkers of RCC aggressiveness is hindered by a lack of relevant model systems that recapitulate the human situation. In this study, we report the development of patient- derived tumor tissue slice ex vivo and in vivo models in conjunction with clinically translatable non-invasive hyperpolarized (HP) 13C magnetic resonance (MR) imaging technique for the metabolic evaluation of RCC. HP MR is a powerful tool that allows dynamic measurement of specific enzymatic processes implicated in tumorigenesis, and has recently been applied to prostate cancer patients. Methods: Tissue slice cultures (TSCs): RCC tissues were obtained from 8mm cores of nephrectomy cases, precision cut into 300 μm thick disks to allow for maximal oxygen and nutrient diffusion. Long-term tissue viability was assessed by biochemical assays (ATP luciferase, LIVE/DEAD) and phosphorous (31P) MR. Immunohistohcemical staining was also performed to characterize the RCC. Ex vivo evaluation of TSCs in a bioreactor: 4 tissue slices were kept alive in a micro-engineered MR compatible perfusion system. MR data were acquired on a narrow-bore 11.67T Varian INOVA equipped with a 5mm broadband probe. HP 13C MR was acquired dynamically following injection of HP pyruvate and DHA (dehydroascorbate) to assess metabolism in the RCC tissue slices. Animal model: The RCC tissue slices were implanted under the renal capsule of immune-compromised mice. Mice underwent multipramateric proton imaging in addition to dynamic HP 13C MR at 14T (Agilent microimaging system). For the HP MR, a 2D echo-planar based spectral spatial selective pulse sequence was used to obtain dynamic lactate images, post injection of 80mM of HP [1-13C]pyruvate. HP [1-13C] pyruvate has been used to study glycolysis in tumors. Results and Discussion: Ex vivo model: TSCs were viable in the bioreactor for up to 48 hours as confirmed by βNTP levels in 31P spectrum. The 31P spectra displayed characteristic metabolite peaks in the TSCs as seen in RCC patients, with dominant phosphor-ester peaks. Following injection of HP [1-13C] pyruvate into the bioreactor, a dynamic flux to lactate of 0.05 nmols/s/mg tissue was observed in the RCC tissue slices. Additionally we observed the conversion of DHA to Vitamin C in the tumor tissue slices. RCCs are known to have high level of reactive oxygen species, and the combination of this tumor model with HP DHA offers the possibility to interrogate redox potential which is implicated in tumor aggressiveness and treatment response. In vivo model: TSCs were grafted successfully in the sub-renal capsule for even low-grade tumors. Mean tumor ADC measurement of 1.23e-3 mm2/sec in the implanted tumor is similar to that reported in renal cancers clinically. Contrast enhancement of the tumor also confirmed engraftment and perfusion. Elevated HP lactate conversion was observed in the tumor graft, demonstrating the potential of the in vivo model for in-depth metabolic evaluation of tumors that more closely emulate the human situation. IHC of tumor grafts showed the persistence of human vasculature and oncogenic markers. Conclusion: The patient-derive tumor models described above may further enhance our understanding of RCC metabolism and development of clinically relevant biomarkers of tumor aggressiveness and therapy response. Citation Format: Renuka Sriram, Kayvan R. Keshari, Mark Van Criekinge, John Kurhanewicz, David M. Wilson, Donna M. Peehl, Robert Bok, Wang J. Zhen. Patient-derived tissue culture model systems of renal cell carcinoma for development of clinically translatable metabolic biomarkers. [abstract]. In: Proceedings of the AACR Special Conference: The Translational Impact of Model Organisms in Cancer; Nov 5-8, 2013; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Res 2014;12(11 Suppl):Abstract nr B37.