Preclinical imaging characterization and resource development of PDX SCNC prostate cancer murine models

PDX SCNC 前列腺癌小鼠模型的临床前成像特征和资源开发

• 批准号: 10378320
• 负责人: John Kurhanewicz
• 金额: --
• 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 2021-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10378320
• 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; Prediction of Response to Therapy; Process; Protocols documentation; Pyruvate; Receptor Signaling; Reproducibility; Research; Research Design; Research Project Grants; Resistance; Resource Development; 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/antagonist; men; metabolic imaging; metabolic profile; mouse model; new therapeutic target; next generation; novel; online repository; online resource; patient derived xenograft model; patient response; pre-clinical; preclinical development; preclinical imaging; 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; 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 该肿瘤学共同临床成像研究计划（CIRP）提案的目标是克服 如第18-18-18-18-18-18-18-18-18-18-18-18-18-18-18-18-184号的转化障碍，开发了共同临床成像研究资源 鼓励就如何优化定量成像方法达成共识，以提高成像的质量 共同临床试验的结果。这将通过使用新颖的定量代谢临床前完成 超极化（HP）13C磁共振成像（MRI）评估小细胞的治疗反应 神经内分泌（SCNC）前列腺癌（PCA）。鼠类成像研究将与A平行进行 临床试验（NCI R01 CA215694），旨在评估SCNC对转移性男性中卡铂的反应 PCA，由Drs领导。约翰·库尔哈内维奇（John Kurhanewicz）和拉胡尔·阿格加瓦尔（Rahul Aggarwal）在加州大学洛杉矶斯基（UCSF）。 SCNC越来越普遍，致命 PCA的亚型是作为对雄激素剥夺疗法应用和 第二代雄激素途径抑制剂。选择最合适的治疗方法 患有转移性SCNC的患者因血液测试或当前成像方式无法 可靠地确定这些转移性肿瘤中通常也不适合活检的治疗功效。这 该U24项目的研究设计包含CIRP的四个关键要素：1）临床前开发和 优化定量HP 13C MRI获取和数据分析方法，这些方法解决了严格缺乏和 现有的临床前和临床方法的可重复性（AIM 1）； 2）使用适当的患者来源 异种移植（PDX）模型，反映了SCNC的遗传，代谢和微环境异质性 患者转移； 3）优化的临床前动态HP 13C MRI协议和数据的应用 在PDX模型中研究转移骨和肝病的反应的建模方法 化学疗法，与患者资助的研究并行（AIM 2）； 4）建立在线资源 定量HP 13C MRI成像协议，数据分析，建模工具，更宽的相关生物学数据 科学界传播，验证和建立共识（AIM 3）。 为了完成这个重要的翻译定量成像项目，我们组建了一个杰出的团队 具有临床前和临床癌专业知识的基础科学和临床研究者的 研究，现实的PDX模型，HP 13C MRI，信息学以及领先的成像和治疗临床试验。 该研究项目还将利用NIH资助的P41提供的广泛资源 超极化磁共振技术资源中心，大量的临床前和临床 DNP极化器和13C启用的MRI扫描仪以及UCSF上存在的成像信息基础设施。 尽管该建议将集中于当前的护理水平治疗，但新的定量HP 13C代谢 本提案中开发的MRI方法将具有一般适用于各种新的目标 为SCNC以及其他疾病的研究开发了治疗方法。