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 这项肿瘤学联合临床影像研究计划(CIRP)计划的目标是克服 翻译障碍，如PAR-18-184中所述，开发联合临床成像研究资源，将 鼓励就如何优化定量成像方法以提高成像质量达成共识 联合临床试验的结果。这将通过使用新的临床前定量代谢来实现 超极化(HP)~(13)C磁共振成像(MRI)评估小细胞治疗反应 神经内分泌(SCNC)前列腺癌(PCa)。这项小鼠成像研究将与 临床试验(NCI R01 CA215694)，旨在评估SCNC对转移性男性卡铂的疗效 加州大学旧金山分校的John Kurhanewicz博士和Rahul Aggarwal博士领导的PCA。SCNC是一种日益流行的、致命的 作为对雄激素剥夺治疗应用的适应性反应而出现的前列腺癌的亚型 第二代有效的雄激素途径抑制剂。选择最合适的治疗方法 转移性SCNC患者受阻于这样一个事实：无论是血液检测还是目前的影像检查都不能。 可靠地确定这些转移性肿瘤的治疗效果，这些转移性肿瘤通常也不适合进行活检。这个 这项U24项目的研究设计结合了CIRP的四个关键要素：1)临床前开发和 优化HP 13C MRI定量采集和数据分析方法，以解决缺乏严密性和 现有临床前和临床方法的可重复性(目标1)；2)使用适当的患者衍生方法 反映SCNC遗传、代谢和微环境异质性的异种移植(PDX)模型 3)优化的临床前动态HP 13C磁共振成像方案和数据的应用 研究PDX模型中转移性骨和肝脏疾病对 化疗，与资助的患者研究并行(目标2)；以及4)建立一个在线资源 定量HP 13C MRI成像协议、数据分析、建模工具、相关生物学数据 由科学界传播、确认和建立共识(目标3)。 为了完成这一重要的翻译定量成像项目，我们组建了一支出色的团队 在临床前和临床癌症方面具有免费专业知识的基础科学和临床研究人员 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。 这项研究项目还将利用美国国立卫生研究院资助的P41提供的广泛资源 超极化磁共振技术资源中心，大量临床前和临床 加州大学旧金山分校现有的DNP偏振器和13C核磁共振扫描仪，以及成像信息学基础设施。 尽管这项建议将重点放在当前的护理治疗标准上，但新的量化Hp 13C代谢 本提案中开发的MRI方法将普遍适用于各种新的靶向 正在为SCNC以及其他疾病的研究开发治疗方法。