基于多维网状Meta分析和WGCNA的复方苦参注射液干预胃癌LncRNA临床关联模型构建

复方苦参注射液在胃癌的治疗中应用广泛且发挥着增效减毒的重要作用，但其临床疗效的精准评价和相关机制的深入研究尚属空白。本项目首次整合复方苦参注射液临床与生物信息数据并构建关联模型，深入分析临床指征变化与LncRNA表达相关性。.本项目的研究内容包括三个部分，即：“基于多维网状Meta分析的复方苦参注射液治疗胃癌优势临床指征研究”、“基于WGCNA的胃癌关键差异基因与临床指征相关性研究”、“基于整合生物信息学的复方苦参注射液干预胃癌LncRNA表达变化研究”。.本项目的创新点：①首次应用多维网状Meta分析方法对复方苦参注射液治疗胃癌的临床疗效进行多指标综合评价；②以LncRNA为机制研究核心切入点，运用加权基因共表达网络技术（WGCNA）优化经典网络药理学方法，构建微观分子表达与临床指征的关联模型；③探索基于“临床大数据与生物信息大数据联动模式”的中药上市后再评价新方法。

Compound kushen injection is widely used in the treatment of gastric cancer and plays an important role in enhancing efficacy and reducing toxicity. However, the precise evaluation of its clinical efficacy and in-depth research on related mechanisms are still blank. This project is the first time to integrate clinical and biological information data of compound Kushen injection and build a correlation model to analyze the correlation between clinical indication changes and LncRNA expression..The research content of this project mainly includes three parts, namely: “Research on Clinical Indication Evaluation of Compound Kushen Injection for Gastric Cancer Based on Multi-dimensional Mesh Meta-analysis", "Correlation study of core differential genes and clinical indications in gastric cancer based on WGCNA" and "Study on the change of expression of LncRNA in gastric cancer by Compound Kushen injection based on integrated bioinformatics"..The innovations of this project: ① The multi-dimensional network meta-analysis method pioneered by the research group was used to evaluate the clinical efficacy of Compound Kushen injection in treating gastric cancer with multiple indicators; ② LncRNA is used as the core entry point for mechanism research, and the weighted gene co-expression network technology (WGCNA) is used to optimize the classic network pharmacology method to build a correlation model between microscopic molecular expression and clinical indicators; ③ Exploring a new method for evaluating traditional Chinese medicines based on the "clinical big data-biological information big data linkage model".