Translational Applications in an Animal Model of Pancreatic Cystic Neoplasm and Cancer

胰腺囊性肿瘤和癌症动物模型中的转化应用

• 批准号: 9904574
• 负责人: ANIRBAN MAITRA
• 金额: $ 59.76万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-04-04 至 2022-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9904574
• 关键词: Abdomen; Address; Algorithms; Animal Model; Appendix Adenocarcinoma; Area; Autoantibodies; Benign; Biology; Cancer Detection; Cancer Etiology; Clinical; Credentialing; Cyst; Cystic Lesion; DNA; Data; Detection; Development; Diagnosis; Doxycycline; Early Diagnosis; Engineering; Excision; Funding; GTP-Binding Proteins; Genetic; Genetically Engineered Mouse; Genome; Genomics; Human; Image; Indigenous; Indolent; KRAS2 gene; Knowledge; Label; Laboratories; Lesion; MRI Scans; Magnetic Resonance Imaging; Malignant Neoplasms; Malignant neoplasm of pancreas; Mass Spectrum Analysis; Modeling; Monitor; Mucinous Neoplasm; Mucins; Mus; Mutation; Neoplasms; Oncogenic; Operative Surgical Procedures; Pancreas; Pancreatic Cyst; Pancreatic Ductal Adenocarcinoma; Pancreatic cystic neoplasia; Papillary; Pathogenesis; Patients; Pattern; Performance; Plasma; Positioning Attribute; Protein Array; Proteins; Pyruvate; Recommendation; Reflex action; Risk; Risk Factors; Sampling; Scanning; Sensitivity and Specificity; Survival Rate; Time; Translational Research; United States; Validation; base; blood-based biomarker; cancer invasiveness; circulating biomarkers; cohort; digital; driver mutation; exosome; feature extraction; high risk; high risk population; human disease; imaging platform; imaging study; liquid biopsy; member; molecular imaging; mortality; mouse model; multidisciplinary; mutant; novel; overtreatment; pancreas imaging; patient population; prevent; progression marker; serial imaging; specific biomarkers; success; translational study; treatment stratification; tumor progression; validation studies

ABSTRACT Pancreatic ductal adenocarcinoma (PDAC) has a median 5-year survival of only 8%, and early diagnosis of PDAC is an area of highest priority for the NCI. Amongst the best-recognized risk factors for PDAC are mucinous pancreatic cysts, of which the most common subtype is known as intraductal papillary mucinous neoplasm (IPMN). Currently, IPMN patients either undergo surgical resection due to “worrisome” imaging features, or are followed conservatively by serial imaging studies for risk of progression to invasive PDAC. Unfortunately, the imaging criteria reflexing patients to surgery are imperfect, leading to both over- and under-treatment of IPMNs. Further, there are no credentialed blood-based biomarkers with a sensitivity and specificity that warrants reliable therapeutic stratification. Our group has identified oncogenic mutations of KRAS and GNAS as the two most common driver mutations in IPMNs – one or other is present in ~96% of cases. We have now engineered the first animal model of IPMN that harbors the mutational combination (Kras;Gnas) found most commonly in the cognate human disease. Upon doxycycline induction, the Kras;Gnas mice uniformly develop cystic lesions by 6 weeks, with progression to invasive cancer in 25% of mice by 21 weeks, mimicking the multistep progression of human IPMN to PDAC. The objective of this proposal is to enhance the translational applicability of this model by using it as a controlled platform to address key unmet needs in the management of IPMNs in two areas: imaging correlates and circulating biomarkers. In Aim 1, we will use the animal model to investigate two novel imaging platforms – quantitative feature extraction from MRI scans using an indigenously developed algorithm known as “Enhancement Pattern Mapping” (EPM) and second, hyperpolarized MRI (HPMRI), in order to determine imaging correlates that coincide with the transition from low grade IPMN to cancer. In Aim 2, we will use a combination of unbiased mass spectrometry and array-based approaches to identify circulating proteins and autoantibodies, respectively that correlate with progression of murine IPMNs to PDAC. In addition, we will examine the potential of genomic liquid biopsies for cancer prediction, through utilizing an ultrasensitive and quantitative droplet digital PCR (ddPCR) platform for detection of mutant KRAS and GNAS DNA within circulating exosomes. All three classes of blood-based biomarkers (proteins, autoantibodies and exoDNA) will be assessed in matched murine plasma samples, which will allow us to estimate the additive performance for cancer detection using robust statistical paradigms. Both aims will benefit from ready access to imaging scans and biospecimens from IPMN patients for cross-species translational validation studies, through NCI-funded multicenter U01 consortia that are led by the PI. We believe this multidisciplinary proposal has the potential for long-term impact on PDAC mortality through practice changing alterations in the approach towards monitoring cancer progression in IPMNs.

抽象的 胰腺导管腺癌 (PDAC) 的中位 5 年生存率仅为 8%，早期诊断 PDAC 是 NCI 最优先考虑的领域，其中最受认可的 PDAC 风险因素是粘液性。 胰腺囊肿，其中最常见的亚型是导管内乳头状粘液性肿瘤 (IPMN)。目前，IPMN 患者要么因“令人担忧”的影像学特征而接受手术切除，要么正在接受手术切除。 不幸的是，随后进行了一系列影像学研究，以了解进展为侵袭性 PDAC 的风险。 反映患者手术情况的影像学标准并不完善，导致 IPMN 治疗过度或治疗不足。 此外，没有经过认证的血液生物标志物具有可保证可靠的敏感性和特异性。 我们的小组已确定 KRAS 和 GNAS 是两个最重要的致癌突变。 IPMN 中的常见驱动突变——约 96% 的病例中存在一种或另一种突变，我们现在已经设计了这种突变。 第一个 IPMN 动物模型含有最常见的突变组合（Kras；Gnas） 在强力霉素诱导下，Kras;Gnas 小鼠均匀出现囊性病变 6 倍。 周，21 周时 25% 的小鼠进展为浸润性癌症，模仿了多步进展 该提案的目的是增强该模型的转化适用性。 通过将其用作受控平台来解决 IPMN 管理中两个领域中未满足的关键需求： 在目标 1 中，我们将使用动物模型来研究两篇小说。 成像平台 – 使用自主开发的算法从 MRI 扫描中提取定量特征 称为“增强模式映射”(EPM) 和第二种超极化 MRI (HPMRI)，以便 在目标 2 中，我们将确定与从低级别 IPMN 转变为癌症相一致的影像学相关性。 结合使用无偏质谱和基于阵列的方法来识别循环蛋白 和自身抗体，分别与小鼠 IPMN 发展为 PDAC 相关。 通过利用超灵敏和可检测基因组液体活检的癌症预测潜力 定量液滴数字 PCR (ddPCR) 平台，用于检测循环中突变的 KRAS 和 GNAS DNA 将评估所有三类血液生物标志物（蛋白质、自身抗体和外切 DNA）。 在匹配的小鼠血浆样本中，这将使我们能够估计癌症检测的附加性能 使用强大的统计范式将受益于随时获取成像扫描和生物样本。 通过 NCI 资助的多中心 U01，从 IPMN 患者中进行跨物种转化验证研究 由 PI 领导的联盟我们相信这一多学科提案具有长期影响的潜力。 通过实践改变监测癌症进展的方法来降低 PDAC 死亡率 在 IPMN 中。