Poster Session B   |   7:00am Expo - Hall A & C   |   Poster ID #194

Multimodal Imaging to Interrogate the Metabolic Fingerprint of Prostate Cancer

Program:
Academic Research
Category:
Tumor Biology
FDA Status:
Not Applicable
CPRIT Grant:
Cancer Site(s):
Prostate
Authors:
Jose S Enriquez
The University of Texas M.D. Anderson Cancer Center
Vincenzo Paolillo
The University of Texas M.D. Anderson Cancer Center
Prasanta Dutta
The University of Texas M.D. Anderson Cancer Center
Jenny Han
The University of Texas M.D. Anderson Cancer Center
Ryan Armijo
The University of Texas M.D. Anderson Cancer Center
Muxin Wang
The University of Texas M.D. Anderson Cancer Center
Peter Shepherd
The University of Texas M.D. Anderson Cancer Center
Daniel Frigo
The University of Texas M.D. Anderson Cancer Center
Pratip Bhattacharya
The University of Texas M.D. Anderson Cancer Center
Federica Pisaneschi
The University of Texas Health Science Center at Houston

Introduction

There is an unmet clinical need for robust imaging biomarkers to distinguish indolent from aggressive prostate cancer (PCa). Many advanced prostate cancer patients receiving anti-androgens (Enzalutamide) as the first line of treatment, develop resistance which relapses. Dysregulated cell metabolism is a key driver for PCa progression and resistance to therapy. Two pathways that are commonly dysregulated in PCa are glycolysis and lipid metabolism. We sought to analyze these pathways in vivo with multimodal metabolic imaging and ex vivo, with metabolomics. Enzalutamide-sensitive or resistant Androgen Receptor-dependent (AR+) and AR-independent (AR-) patient-derived xenograft (PDX) tumors were utilized. [1-13C]-Pyruvate hyperpolarized magnetic resonance spectroscopy (HP-MRS) and [18F]-fluorodeoxyglucose positron emission tomography (18F-FDG-PET) were used to interrogate glycolysis, and [18F]fluoropivalic acid positron emission tomography (18F-FPIA-PET) was used to interrogate lipid metabolism.

Methods

PDX models included 183 and 180 (AR+, Enzalutamide Sensitive), 274 and 477 (AR+, Enzalutamide Resistant), 144, 177, 118, and 114 (AR-) models. Models were imaged before and after 7 days of treatment with Enzalutamide. 18F-FPIA was produced on GE TracerLab via implementation of the published procedure and PET/CT images were acquired on an Albira trimodal PET/SPECT/CT image station. Simultaneously, [1-13C]-labeled pyruvic acid was hyperpolarized using a commercial DNP HyperSense polarizer following standard protocol. Anatomical MRI and 13C-MRS were obtained on different PCa PDX mouse models at different time points using a Bruker 7T scanner. 

Results

[18F]FPIA has been successfully produced in 25.4±3.8 (n=9) activity yield, >99% radiochemical purity, and high UV purity. In some models, the dynamic HP-MR metabolic flux ratio, lactate-to-pyruvate (Lac/Pyr) was determined in vivo pre and post-treatment with Enzalutamide. At baseline, the Lac/Pyr ratio in 177 AR- PDX is lower than in 180 AR+ PDX by 20%. Post-treatment with Enzalutamide, in the sensitive group, the Lac/Pyr ratios decreased after treatment, whereas the ratio increased in the resistant PDX. With PET, [18F]FDG uptake was higher in the 180 AR+ group compared to the 144-4 AR- group. After treatment of the 180 AR+ group, there was also a decrease in FDG uptake, suggesting a decrease in glycolysis that correlated with the HP-MR data. Preliminary data on [18F]FPIA-PET at baseline on AR+ and AR- PDXs suggest that FPIA is uptaken in these models and increases over time. We are currently still collecting data at base line on more AR+ PDXs, both sensitive and resistant to Enzalutamide.

Conclusion

Metabolic imaging combining [1-13C]-pyruvate HP-MRS and [18F]FDG- and [18F]FPIA-PET presents an exciting opportunity to interrogate both glycolysis and fatty acid metabolism in PCa, with the ultimate aim to use PET/MRI to non-invasively detect predictive biomarkers of resistance to therapy. From this preliminary data, [1-13C]-pyruvate HP-MRS seems to be predictive of resistance to Enzalutamide.