目的：探讨结直肠癌（colorectal cancer, CRC）肝转移的关键基因和分子机制，为CRC肝转移的治疗提供潜在靶点和生物标志物。方法: 基于生物信息学方法从GEO 数据库下载CRC 肝转移基因表达数据集，筛选差异表达基因（differentially expressed gene, DEG），利用DAVID 在线工具对DEG进行GO和KEGG富集分析，构建蛋白互作（protein-protein interaction, PPI）网络图，筛选出CRC关键基因并进行预后分析。结果: 从183 例CRC组织标本和39 例CRC肝转移组织标本中筛选出321 个DEG，其中上调基因153 个、下调基因168 个。GO和KEGG富集分析结果显示，DEG的功能主要涉及蛋白质激活级联反应、炎症反应、细胞外基质、血小板脱颗粒、补体与凝血级联反应等。PPI 网络图筛选出8 个CRC 关键基因为ALB、APOB、FGA、F2、APOA1、SERPINC1、FGG和AHSG。生存分析发现，SERPINC1、FGG表达高的患者预后不良（均P<0.05）。结论: DEG的生物学功能和信号通路与CRC肝转移的发生发展相关，8 个CRC关键基因可能是CRC肝转移治疗的潜在靶点，SERPINC1、FGG可能成为新的预后标志物。

Objective: To explore the key genes and molecular mechanisms of liver metastasis in colorectal cancer (CRC), and to provide potential targets and biomarkers for the treatment of CRC with liver metastasis. Methods: Based on the bioinformatics method,the gene data sets of CRC liver metastasis were downloaded from the GEO database to screen the differentially expressed genes (DEGs); the GO and KEGG enrichment analyses of DEGs were performed by using DAVID online tool, and the protein-protein interaction (PPI) network was constructed to screen out the key genes, and subsequently the prognosis was analyzed. Results: A total of 321 DEGs were selected from 183 CRC specimens and 39 liver metastasis specimens, including 153 up-regulated genes and 168 downregulated genes. The results of enrichment analysis of GO and KEGG showed that the functions of DEGs were mainly related to protein activation cascade, inflammatory response, extracellular matrix, platelet degranulation, complement and coagulation cascade reaction etc. 8 key CRC genes (ALB, APOB, FGA, F2,APOA1, SERPINC1, FGG andAHSG) were screened by PPI network. Survival analysis showed that patients with high expressions of SERPINC1 and FGG had poor prognosis (all P<0.05). Conclusion: The biological functions and signaling pathways of DEGs are related to the occurrence and development of liver metastasis. The 8 key genes may be the potential therapeutic targets of CRC liver metastasis, and SERPINC1 and FGG may be new prognostic markers.

国家自然科学基金资助项目（No.81573915）