Characterization of PDX SCNC prostate cancer metastatic murine models and development of associated research resources

PDX SCNC 前列腺癌转移小鼠模型的表征和相关研究资源的开发

• 批准号: 10533469
• 负责人: John Kurhanewicz
• 金额: $ 7.59万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-07 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10533469
• 关键词: 2,4-Dinitrophenol; Address; Androgen Receptor; Androgens; Basic Science; Biological Markers; Biology; Biopsy; Blood Tests; Bone Diseases; Cancer Detection; Carboplatin; Clinical; Clinical Investigator; Clinical Management; Clinical Protocols; Clinical Research; Clinical Trials; Communities; Consensus; Data; Data Analyses; Disease; Echo-Planar Imaging; Elements; Event; Funding; Generations; Genetic; Goals; Grant; Heterogeneity; Image; Imaging Device; Imaging Techniques; Information Resources; Institutes; Liver; Liver diseases; Magnetic Resonance; Magnetic Resonance Imaging; Malignant Neoplasms; Malignant neoplasm of prostate; Measurement; Metabolic; Metastatic Neoplasm to the Bone; Metastatic Neoplasm to the Liver; Metastatic Prostate Cancer; Methods; Modeling; Molecular; Mus; Neoplasm Metastasis; Neuroendocrine Cell; Neuroendocrine Prostate Cancer; Neurosecretory Systems; Noise; Oncology; Outcome; Pathologic; Pathway interactions; Patients; Physiologic pulse; Platinum; Positron-Emission Tomography; Postdoctoral Fellow; Prediction of Response to Therapy; Process; Protocols documentation; Pyruvate; Receptor Signaling; Reproducibility; Research; Research Design; Research Project Grants; Resistance; Resources; Serum; Signal Transduction; Site; Small Cell Carcinoma; Somatostatin Receptor; Technology; Testing; Therapeutic Clinical Trial; Time; Treatment Efficacy; United States National Institutes of Health; Validation; advanced prostate cancer; analytical tool; androgen deprivation therapy; anticancer research; base; bone; cancer clinical trial; castration resistant prostate cancer; chemotherapy; clinical imaging; co-clinical trial; conventional therapy; data acquisition; data analysis pipeline; data modeling; data repository; data standards; fluorodeoxyglucose; imaging approach; imaging informatics; imaging modality; imaging study; improved; improved outcome; in vivo; informatics infrastructure; inhibitor; men; metabolic imaging; metabolic profile; model development; mouse model; new therapeutic target; next generation; novel; online repository; online resource; patient derived xenograft model; patient response; pre-clinical; preclinical development; predictive marker; programs; prostate cancer metastasis; quantitative imaging; radio frequency; real time monitoring; response; response biomarker; stable isotope; standard of care; temporal measurement; therapy resistant; tool; transcriptomics; transdifferentiation; translational barrier; treatment response; tumor; tumor xenograft; web portal

PROJECT SUMMARY / ABSTRACT 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.

项目摘要/摘要