Ultra-Sensitive MR Probes for Molecular Diagnosis of Lung Cancer

描述（由申请人提供）：本研究的长期目标是开发超灵敏的磁共振成像（MRI）探针，可以通过MRI对肺部肿瘤进行癌症特异性检测。MRI是一种临床成像技术，在癌症的无创诊断和治疗后评估中有着广泛的应用。虽然Gd-DTPA （Magnevist.）和其他小分子量试剂在动态对比增强MRI应用中效果很好，但这些试剂不是很敏感（检测下限为~10-4 M），因此不能用于检测体内特定的生物标志物。在这个应用程序中，我们将研究使用超顺磁聚合物胶束（SPPM），它装载了一簇磁铁矿纳米颗粒用于肺癌的分子成像。该平台显示出约20 pM的MRI检测灵敏度，这将是诊断肺癌所必需的。从噬菌体筛选中鉴定出的一类新型肺癌靶向肽（LCPs）将在SPPM表面功能化以靶向肺癌细胞。所分离的肽具有显著的结合亲和力（<nM）和细胞特异性（20-1000倍），可区分不同的细胞类型。我们的中心假设是lcp编码的SPPM将允许在胸腺裸鼠原位肺肿瘤模型中高度敏感和特异性地诊断不同类型的肺癌。为了验证这一假设，我们将开展以下具体工作：(1)建立ORS方法，优化SPPM成分，增强ORS对比度；(2)体外制备并表征lcp编码的SPPM；(3)验证lcp编码的SPPM在体内对肺癌的诊断作用。本应用的成功实施将为该胶束平台无创肺癌诊断奠定技术基础和临床前疗效。公共卫生相关性：将开发一种新型MRI成像方法和超灵敏分子探针的组合，以提供肺肿瘤的细胞特异性表征。这些知识有助于及时干预肺癌，实现个体化治疗。

DESCRIPTION (provided by applicant): The long-term goal of this research is to develop ultra-sensitive magnetic resonance imaging (MRI) probes that can provide cancer-specific detection of lung tumors by MRI. MRI is a clinical imaging technique that has broad applications in non-invasive diagnosis and post-therapy assessment for cancer. Although Gd-DTPA (Magnevist.) and other small molecular weight agents work well for dynamic contrast enhancement MRI applications, these agents are not very sensitive (lower limit of detection is ~10-4 M) and therefore cannot be used for detecting specific biological markers in vivo. In this application, we will investigate the use of superparamagnetic polymeric micelles (SPPM) that are loaded with a cluster of magnetite nanoparticles for molecular imaging of lung cancer. This platform demonstrated ~20 pM sensitivity of detection by MRI that will be essential for diagnosing lung cancers. A novel class of lung cancer-targeting peptides (LCPs) identified from phage screening will be functionalized on the surface of SPPM to target lung cancer cells. The isolated peptides demonstrated remarkable binding affinities (<nM) and cell specificities (20-1000 fold) to discriminate between different cell types. Our central hypothesis is that LCP-encoded SPPM will allow for highly sensitive and specific diagnosis of different types of lung cancer in an orthotopic lung tumor model in athymic nude mice. To test this hypothesis, we will carry out the following specific aims: (1) Establish ORS method and optimize SPPM compositions to enhance ORS contrast; (2) produce and characterize LCP-encoded SPPM in vitro; and (3) validate LCP-encoded SPPM for diagnosis of lung cancer in vivo. Successful execution of this application will establish the technology foundation and preclinical efficacy of the micelle platform for non-invasive diagnosis of lung cancer. PUBLIC HEALTH RELEVANCE: A combination of novel MRI imaging method and ultra-sensitive molecular probes will be developed to provide cell-specific characterization of lung tumors. This knowledge can facilitate timely intervention of lung cancer to achieve personalized medicine.