The goal of this Oncology Co-Clinical Imaging Research Program (CIRP) proposal is to overcome the translational barrier, as stated in PAR-18-184, to develop co-clinical imaging research resources that will encourage a consensus on how quantitative imaging methods are optimized to improve the quality of imaging results for co-clinical trials. This will be accomplished by using novel quantitative metabolic preclinical hyperpolarized (HP) 13C magnetic resonance imaging (MRI) to assess therapeutic response of small cell neuroendocrine (SCNC) prostate cancer (PCa). The murine imaging study will be conducted in parallel to a clinical trial (NCI R01 CA215694), aiming to assess response of SCNC to carboplatin in men with metastatic PCa, led by Drs. John Kurhanewicz and Rahul Aggarwal at UCSF. SCNC is an increasingly prevalent, lethal subtype of PCa that arises as an adaptive response to the application of androgen deprivation therapy and second-generation potent androgen pathway inhibitors. The selection of the most appropriate treatment of patients with metastatic SCNC is hindered by the fact that neither blood tests or current imaging modalities can reliably identify therapeutic efficacy in these metastatic tumors which are also often not amenable to biopsy. The study design of this U24 project incorporates the four key elements of CIRP: 1) The preclinical development and optimization of quantitative HP 13C MRI acquisition and data analysis methods that address the lack in rigor and reproducibility of existing preclinical and clinical approaches (aim 1); 2) The use of appropriate patient-derived xenograft (PDX) models that reflect the genetic, metabolic and micro-environmental heterogeneity of SCNC metastases in patients; 3) The application of the optimized preclinical dynamic HP 13C MRI protocols and data modeling approaches to study the response of metastatic bone and liver disease in the PDX models to chemotherapy, paralleling the funded study in patients (aim 2); and 4) The establishment of an online resource of quantitative HP 13C MRI imaging protocols, data analyses, modeling tools, correlative biology data for wider dissemination, validation and establishment of consensus by the scientific community (aim 3). To accomplish this important translational quantitative imaging project, we have assembled an exceptional team of basic science and clinical investigators with complimentary expertise in preclinical and clinical cancer research, realistic PDX models, HP 13C MRI, informatics, and in leading imaging and therapeutic clinical trials. This research project will also capitalize on the extensive resources provided by the NIH funded P41 Hyperpolarized Magnetic Resonance Technology Resource Center, the large number of preclinical and clinical DNP polarizers and 13C-enabled MRI scanners, and imaging informatics infrastructure which exist at UCSF. Although this proposal will focus on current standard of care treatment, the new quantitative HP 13C metabolic MRI approaches developed in this proposal will have general applicability for a variety of new targeted therapeutic approaches being developed for SCNC as well as for the study of other diseases.

Public Health Relevance

The successful outcome of this Co-Clinical Imaging Research Program proposal is the establishment of an online resource of quantitative HP 13C MRI protocols, data analyses tools, and correlative biology data allowing for a consensus on how quantitative HP 13C MRI can be used in co-clinical imaging trials to improve the assessment of therapeutic response and resistance. While this project focuses on advanced prostate cancer, these new quantitative metabolic imaging techniques could ultimately benefit the clinical management of other cancers and diseases.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Resource-Related Research Projects--Cooperative Agreements (U24)
Project #
1U24CA253377-01
Application #
10057724
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Zhang, Huiming
Project Start
2020-09-07
Project End
2025-08-31
Budget Start
2020-09-07
Budget End
2021-08-31
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of California San Francisco
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94118