应用质谱成像与定量蛋白质组学寻找新的抗炎调控网络关键节点

Inflammation-related diseases threats human health. Recent studies have found inflammatory responses is closely-associated with the development of major diseases such as obesity, diabetes and cancer. Inflammation plays a key role and affects every step of tumor progression. Understanding the molecular mechanism of inflammation, is therefore not only for treating inflammation, but to understand the mechanism of cancer and other major diseases, and promote new therapies. Although extensive studies have been done to understanding the of initiation and regulatory mechanism of inflammatory response, the current understanding of inflammatory key nodes and cell processes is still limited, the detailed molecular mechanism of inflammation is still not clear. Imaging Mass Spectrometry (IMS) emerges as a new molecular imaging technology, has many advantages such as high speed, high throughput, simple preparation, without the needs of prior knowledge. It can be used to obtain the visual information of molecules the organization, spatial and temporal distribution in tissues. We therefore decided to combine the use of IMS with quantitative proteomics tools, to identify the key components of the inflammatory regulatory network by analyzing the common and unique pathways of two anti-inflammatory natural products. These key components are expected to have the potential of being used as clinical prognostic markers. The technology platform for the project will provide new tools for finding key nodes in inflammatory-transformed tumors, provide the clues for disease prediction, diagnosis, treatment and drug targets.

炎症相关疾病长期困扰人类健康。近来炎症反应更被发现与多种重大疾病如肥胖，糖尿病与癌症等的发展密切相关。炎症已被视为肿瘤进展的关键组成部分，影响着每一个步骤。理解炎症分子机制，不单对治疗炎症起关键作用，更有助理解癌症等重大疾病，促进新的疗法。虽然大量的研究工作已涉及理解启动和调节炎症反应的机制，目前对炎症关键节点和细胞过程的理解仍然有限，炎症的分子机制与调控规律尚不明确。质谱成像作为新兴的分子成像技术，具有高速，高通量，制备简单，无需先验知识等优点；可全景式的获得分子在组织中的结构、空间与时间分布的可视化信息。我们拟通过质谱成像结合定量蛋白质组学技术，通过分析两种抗炎天然产物信号通路的异同，寻找炎症调控网络关键节点，并在细胞及小鼠模型中诠释其功能。这些关键节点有望作为临床预后标志物使用。项目所建技术平台也有可能为寻找炎症的关键节点提供新工具，为疾病的预测、诊断、治疗提供线索。

炎症相关疾病长期困扰人类健康。近来炎症反应更被发现与多种重大疾病如肥胖，糖尿病与癌症等的发展密切相关。炎症已被视为肿瘤进展的关键组成部分，影响着每一个步骤。理解炎症分子机制，不单对治疗炎症起关键作用，更有助理解癌症等重大疾病，促进新的疗法。本课题建立了开发了一套针对蛋白翻译后修饰的从非靶向至靶向的整合定量蛋白质组学分析方法，并用以分析天然小分子CEL的抗炎信号通路的关键节点及其翻译后修饰的调控模式。 建立并优化了代谢组、脂质组、转录组和质谱成像的多组学分析和数据整合方法。基于这些建立的方法，分析并鉴定了抗炎小分子在细胞层面上对信号通路调控的关键组成部件，阐明了在这些信号分子在时间维度上的变化规律，为寻找调控炎症信号的关键分子提供了线索。更进一步将这些方法应用于细颗粒物的毒理分析，找到了新的毒性机制和炎症发生机制。