本项目提出炎症致癌与炎症保护作用失衡导致肿瘤发生假说，围绕非可控性炎症恶性转化的调控网络及其关键节点这一核心科学问题，开展计算方法、实验方法密切结合的多学科联合攻关研究。主要以结肠炎到大肠癌、肝炎到肝癌为例，以来自临床样本的高通量组学数据为基础，发展多源、多层次信息融合的动态网络构建方法，构建非可控炎症恶性转化的分子网络；通过炎症致癌与炎症保护的网络平衡分析，阐释非可控炎症恶性转化的分子机制；采用dE-MAP实验方法解析导致炎症向肿瘤转化的网络关键节点，并在体内外模型和大规模临床样本中验证网络关键节点作为生物标志和药物分子靶标的可能性。本项目从临床出发进行分子网络构建与机制分析，到回归临床进行网络关键节点验证，具有源于临床、回归临床的特点。本项目的顺利进行，有望从分子水平和系统层次加深对非可控炎症恶性转化的机制理解，并为发现肿瘤早期生物标志、防治肿瘤的药物靶点提供重要科学基础。

We hypothesize that cancer genesis is caused by unbalance of inflammation resolution. We propose a multi-disciplinary approach by combining computational and experimental biology to study the regulatory network and key components controlling the transition from nonresolving inflammation to cancer genesis. The aims of our proposal are 1) to construct the dynamic regulatory network that plays key roles in transition from nonresolving inflammation to colon and liver cancer genesis by integrating multi-source and multi-level high-throughput “omic” data derived from clinical samples, 2) to elucidate the molecular mechanism about how unbalanced resolution of inflammation mediates the transition from nonresolving inflammation to cancer genesis , 3) to identify the key components regulating the transition from nonresolving inflammation to cancer genesis by using dE-MAP analysis, verify functions of the key components in cell culture model and animal model, and study whether it is possible to use these key components as biomarkers or therapeutic targets. The novelty of this proposal lies in that we deduce the molecular network based on clinical data and verify the function of the predicted key regulatory network for clinical purposes. This project will facilitate our understanding of the transition from nonresolving inflammation to cancer genesis at molecular and systemic levels, and will provide the foundation for identification of early biomarkers and novel drug targets.