流行病学证据支持慢性胃炎发展为胃癌，但确切机制尚不完全清楚，从整体上理解慢性胃炎向胃癌转化过程中分子调控机制及其调控网络研究尚无报道，本项目拟以临床病人样品为出发点，以正常组织、慢性萎缩性胃炎、胃癌的病理发展过程为研究对象，运用cDNA microarray和aCGH技术，分别构建正常组织、癌前病变组织和胃癌组织RNA表达谱和DNA拷贝数数据库。通过大规模数据比对，找出在差别表达数据，结合转录因子活性分析、随机动力学和贝叶斯概率分析等方法，建立慢性炎症向胃癌的转录调控网路并揭示其关键节点。运用大规模扰动加以确认，并以胃癌细胞株和动物模型加以验，进一步揭示胃癌发生发展的分子机制。

Epidemiological studies provide associations between chronic gastric inflammation and gastric cancer; however, the mechanisms are largely unknown. The molecular regulators and transcriptional networks during the progresses of gastritis to gastric cancer are not documented yet. The goal of this project is to investigate the progress of chronic inflammation to carcinogenesis in stomach by using clinical samples from patients and healthy volunteers. The RNA and DNA database of normal gastric tissues, precancerous lesions and gastric cancer tissues are constructed by using cDNA microarray and aCGH analyses. The differently expressed genes within different stages of disease are obtained by large-scale comparing based on computing platform. The key regulators and its cohort are identified using biosystematic methods including master regulator analysis, stochastic dynamics and Bayesian probability analysis, etc. Large-scale perturbation cell models are used to rank the interactions between regulators and its target genes. The transcriptional networks are thus constructed and separated by functional modules. Gastric cancer cell lines are used to validate the roles of key regulators and deepen the signaling pathway investigations. Nude mice models are used for in vivo analysis. These findings provide understanding of mechanisms about chronic gastric inflammation progresses to gastric cancer; furthermore, propose promising targets for clinical intervention.