非可控性炎症调控网络体内定量监视预测技术研究

Given the bottleneck problem of lack of in vivo quantitative visualization technique in the research of nonresolving inflammation regulatory networks aggressively transformation, the investigation is based on the complicated biology systems imbalanced theory of host internal environment with pro-inflammatory and anti-inflammatory cytokines network regulation. From the three perspectives: the host internal environment, inflammatory microenvironment and molecular targets group of inflammation and tumor, in combination of applicant team self-developed target molecular probes with independent intellectual property rights in China, we are going to determine the pro- and anti-inflammation biomarkers for the preparation of inflammatory microenvironment new molecular probes, by using approaches such as high-resolution MAS probe/HPLC-cryoNMR-MS and ELISA to acquire molecular data within host internal environment and inflammatory microenvironment. Using molecular imaging technology by means of noninvasive, real-time, dynamic and quantitative visualization, it is to collect the key inflammatory cytokines in the inflammation microenvironment of animal model and clinical patients, and the information of the crucial network target expression during in inflammation malignant transformation, as well as restoring trends of drug intervention. Combining the information on basis of bio-systems theory, the purpose is to build a quantitative evaluation mathematical model for inflammation-tumor conversion analysis by machine-learning etc, to build integrated techniques which are able to observe inflammation regulation network in vivo, though translational medicine method from animal model to preliminary clinical trials, with potential values of analyzing and predicting inflammation vicious transformation.

针对非可控性炎症调控网络恶性转化研究中缺乏体内定量可视化技术的瓶颈问题，本研究基于复杂性生物系统内环境促炎与抗炎因子网络调控失衡理论，以宿主内环境、炎症微环境、炎癌靶标群三个系统视角，在申请团队自主构建、具有我国自主知识产权的炎癌靶标分子探针基础上，采用高分辨魔角旋转探头结合超低温液核质谱联用等技术，采集宿主内环境和炎症微环境分子信息，定量检测促、抗炎两大系统炎症标志物，为制备炎症微环境新型分子探针提供依据。以分子显像技术无创、实时、动态、定量可视化获取动物模型及临床患者体内炎症微环境中关键炎症因子和炎症恶性转化过程中关键网络靶标蛋白的表达信息，以及药物干预后转归趋势。基于系统生物学理论整合上述数据，以机器学习等相关方法构建病程分析炎癌转化定量评估数学模型；通过从动物模型到临床初步验证转化医学手段建立能够体内直观显示炎症调控网络、具有炎症恶性转化早期分析预测潜在应用价值的集成技术体系。

本研究以宿主内环境、炎症微环境、炎癌靶标群三个系统视角，采用胃癌患者（17例）和慢性胃炎患者（5例）组织标本进行了部分促、抗炎靶标分子的免疫组化检测：包括：IL-1、IL-4、IL-10、VEGF、NF-KB、PAR-1、CXCR4、FPRL1、COX2 、αV3。基础上自主构建具有我国自主知识产权的炎癌靶标分子探针，如整合素αVβ3 分子探针18F-RGD2、细胞凋亡膜磷脂分子探针68Ga-NOTA-Duramycin、血管粘附蛋白-1分子探针68Ga-DOTAVAP-P1、蛋白酶激活受体-1分子探针99mTc-HYNIC-BMS-200261、包括IL-2、IL-8等多种白介素类分子探针在C57背景下APCmin/+小鼠结肠癌炎癌转化模型上获得如下分子显像结果：病灶在炎症初期未见明显的18F-RGD2的摄取，αVβ3表达不显著；而随着炎症进展，病灶18F-RGD2摄取逐渐增强， αVβ3表达逐渐显著，恶性肿瘤形成后，18F-RGD摄取进一步增强，αVβ3表达不仅增多，而且范围扩展。18F-RGD2 MicroPET/CT分子显像有可能成为炎症恶性转化监测的有效的影像学方法。. 癌症患者的癌组织+癌旁组织多种类型高通量数据获取通过对样本差异分析进行组间重叠分析，发现胃炎向胃癌转化相关的基因最富集的通路是细胞周期，且该通路中绝大多数的基因上调表达，可能与胃癌的发生和发展相关；此外，炎症应答和应答刺激通路等信号通路也富集，暗示相关基因可能在胃癌的病程发展中具有重要功能，显著下调表达的基因富集到了炎症应答等功能通路。