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
基本信息
- 批准号:10533469
- 负责人:
- 金额:$ 7.59万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 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:
- 关键词:2,4-DinitrophenolAddressAndrogen ReceptorAndrogensBasic ScienceBiological MarkersBiologyBiopsyBlood TestsBone DiseasesCancer DetectionCarboplatinClinicalClinical InvestigatorClinical ManagementClinical ProtocolsClinical ResearchClinical TrialsCommunitiesConsensusDataData AnalysesDiseaseEcho-Planar ImagingElementsEventFundingGenerationsGeneticGoalsGrantHeterogeneityImageImaging DeviceImaging TechniquesInformation ResourcesInstitutesLiverLiver diseasesMagnetic ResonanceMagnetic Resonance ImagingMalignant NeoplasmsMalignant neoplasm of prostateMeasurementMetabolicMetastatic Neoplasm to the BoneMetastatic Neoplasm to the LiverMetastatic Prostate CancerMethodsModelingMolecularMusNeoplasm MetastasisNeuroendocrine CellNeuroendocrine Prostate CancerNeurosecretory SystemsNoiseOncologyOutcomePathologicPathway interactionsPatientsPhysiologic pulsePlatinumPositron-Emission TomographyPostdoctoral FellowPrediction of Response to TherapyProcessProtocols documentationPyruvateReceptor SignalingReproducibilityResearchResearch DesignResearch Project GrantsResistanceResourcesSerumSignal TransductionSiteSmall Cell CarcinomaSomatostatin ReceptorTechnologyTestingTherapeutic Clinical TrialTimeTreatment EfficacyUnited States National Institutes of HealthValidationadvanced prostate canceranalytical toolandrogen deprivation therapyanticancer researchbasebonecancer clinical trialcastration resistant prostate cancerchemotherapyclinical imagingco-clinical trialconventional therapydata acquisitiondata analysis pipelinedata modelingdata repositorydata standardsfluorodeoxyglucoseimaging approachimaging informaticsimaging modalityimaging studyimprovedimproved outcomein vivoinformatics infrastructureinhibitormenmetabolic imagingmetabolic profilemodel developmentmouse modelnew therapeutic targetnext generationnovelonline repositoryonline resourcepatient derived xenograft modelpatient responsepre-clinicalpreclinical developmentpredictive markerprogramsprostate cancer metastasisquantitative imagingradio frequencyreal time monitoringresponseresponse biomarkerstable isotopestandard of caretemporal measurementtherapy resistanttooltranscriptomicstransdifferentiationtranslational barriertreatment responsetumortumor xenograftweb portal
项目摘要
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
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
John Kurhanewicz其他文献
John Kurhanewicz的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('John Kurhanewicz', 18)}}的其他基金
High Field MRI For Optimized Translational 1H Multiparametric and Multinuclear Imaging Research
用于优化平移 1H 多参数和多核成像研究的高场 MRI
- 批准号:
10175910 - 财政年份:2021
- 资助金额:
$ 7.59万 - 项目类别:
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 - 财政年份:2020
- 资助金额:
$ 7.59万 - 项目类别:
Co-Clinical Quantitative Imaging of Small Cell Neuroendocrine Prostate Cancer Using Hyperpolarized 13C MRI
使用超极化 13C MRI 对小细胞神经内分泌前列腺癌进行临床联合定量成像
- 批准号:
10669081 - 财政年份:2020
- 资助金额:
$ 7.59万 - 项目类别:
Co-Clinical Quantitative Imaging of Small Cell Neuroendocrine Prostate Cancer Using Hyperpolarized 13C MRI
使用超极化 13C MRI 对小细胞神经内分泌前列腺癌进行临床联合定量成像
- 批准号:
10057724 - 财政年份:2020
- 资助金额:
$ 7.59万 - 项目类别:
Co-Clinical Quantitative Imaging of Small Cell Neuroendocrine Prostate Cancer Using Hyperpolarized 13C MRI
使用超极化 13C MRI 对小细胞神经内分泌前列腺癌进行临床联合定量成像
- 批准号:
10470345 - 财政年份:2020
- 资助金额:
$ 7.59万 - 项目类别:
Co-Clinical Quantitative Imaging of Small Cell Neuroendocrine Prostate Cancer Using Hyperpolarized 13C MRI
使用超极化 13C MRI 对小细胞神经内分泌前列腺癌进行临床联合定量成像
- 批准号:
10256057 - 财政年份:2020
- 资助金额:
$ 7.59万 - 项目类别:
Co-Clinical Quantitative Imaging of Small Cell Neuroendocrine Prostate Cancer Using Hyperpolarized 13C MRI
使用超极化 13C MRI 对小细胞神经内分泌前列腺癌进行临床联合定量成像
- 批准号:
10737795 - 财政年份:2020
- 资助金额:
$ 7.59万 - 项目类别:
Metabolic imaging comparisons of patient-derived models of renal cell carcinoma
肾细胞癌患者来源模型的代谢成像比较
- 批准号:
9753176 - 财政年份:2017
- 资助金额:
$ 7.59万 - 项目类别:
Metabolic imaging comparisons of patient-derived models of renal cell carcinoma
肾细胞癌患者来源模型的代谢成像比较
- 批准号:
10227078 - 财政年份:2017
- 资助金额:
$ 7.59万 - 项目类别:
CLINICAL TRANSLATION OF HYPERPOLARIZED 13C-UREA FOR CANCER MR MOLECULAR IMAGING
超极化 13C-尿素用于癌症 MR 分子成像的临床转化
- 批准号:
10116302 - 财政年份:2017
- 资助金额:
$ 7.59万 - 项目类别:
相似海外基金
Rational design of rapidly translatable, highly antigenic and novel recombinant immunogens to address deficiencies of current snakebite treatments
合理设计可快速翻译、高抗原性和新型重组免疫原,以解决当前蛇咬伤治疗的缺陷
- 批准号:
MR/S03398X/2 - 财政年份:2024
- 资助金额:
$ 7.59万 - 项目类别:
Fellowship
CAREER: FEAST (Food Ecosystems And circularity for Sustainable Transformation) framework to address Hidden Hunger
职业:FEAST(食品生态系统和可持续转型循环)框架解决隐性饥饿
- 批准号:
2338423 - 财政年份:2024
- 资助金额:
$ 7.59万 - 项目类别:
Continuing Grant
Re-thinking drug nanocrystals as highly loaded vectors to address key unmet therapeutic challenges
重新思考药物纳米晶体作为高负载载体以解决关键的未满足的治疗挑战
- 批准号:
EP/Y001486/1 - 财政年份:2024
- 资助金额:
$ 7.59万 - 项目类别:
Research Grant
Metrology to address ion suppression in multimodal mass spectrometry imaging with application in oncology
计量学解决多模态质谱成像中的离子抑制问题及其在肿瘤学中的应用
- 批准号:
MR/X03657X/1 - 财政年份:2024
- 资助金额:
$ 7.59万 - 项目类别:
Fellowship
CRII: SHF: A Novel Address Translation Architecture for Virtualized Clouds
CRII:SHF:一种用于虚拟化云的新型地址转换架构
- 批准号:
2348066 - 财政年份:2024
- 资助金额:
$ 7.59万 - 项目类别:
Standard Grant
The Abundance Project: Enhancing Cultural & Green Inclusion in Social Prescribing in Southwest London to Address Ethnic Inequalities in Mental Health
丰富项目:增强文化
- 批准号:
AH/Z505481/1 - 财政年份:2024
- 资助金额:
$ 7.59万 - 项目类别:
Research Grant
ERAMET - Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and paediatric medicines
ERAMET - 快速采用建模和模拟方法的生态系统,以满足孤儿药和儿科药物开发中的监管需求
- 批准号:
10107647 - 财政年份:2024
- 资助金额:
$ 7.59万 - 项目类别:
EU-Funded
BIORETS: Convergence Research Experiences for Teachers in Synthetic and Systems Biology to Address Challenges in Food, Health, Energy, and Environment
BIORETS:合成和系统生物学教师的融合研究经验,以应对食品、健康、能源和环境方面的挑战
- 批准号:
2341402 - 财政年份:2024
- 资助金额:
$ 7.59万 - 项目类别:
Standard Grant
Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and paediatric medicines
快速采用建模和模拟方法的生态系统,以满足孤儿药和儿科药物开发中的监管需求
- 批准号:
10106221 - 财政年份:2024
- 资助金额:
$ 7.59万 - 项目类别:
EU-Funded
Recite: Building Research by Communities to Address Inequities through Expression
背诵:社区开展研究,通过表达解决不平等问题
- 批准号:
AH/Z505341/1 - 财政年份:2024
- 资助金额:
$ 7.59万 - 项目类别:
Research Grant