Abstract：
BACKGROUND: The Lauren classification of gastric tumors strongly correlates with prognosis. The purpose of this study was to explore the specific molecular mechanism of Lauren classification of gastric cancer and provide a possible theoretical basis for the treatment of gastric cancer.
METHODS: We standardized the gene expression data of five Gene Expression Omnibus gastric cancer databases and constructed a Weighted Co-expression Network Analysis (WGCNA) model based on clinicopathological information. The overall survival (OS) and disease-free survival (DFS) curves were extracted from the Cancer Genome Atlas (TCGA) and GSE62254 databases. Western blotting was used to measure protein expression in cells and tissues. Scratch and transwell experiments were used to test the migration ability of tumor cells. Immunohistochemistry was used to measure tissue protein expression in clinical tissue samples to correlate to survival data.
RESULTS: The WGCNA model demonstrated that blue cyan was highly correlated with the Lauren classification of the tumor (r = 0.24, P = 7 × 1016). A protein-protein interaction network was used to visualize the genes in the blue cyan module. The OS and PFS TCGA analysis revealed that LMOD1 was a gene of interest. The proportion of diffuse gastric cancer patients with high expression of LMOD1 was significantly higher than that of intestinal type patients. LMOD1 promoted the migration of gastric cancer cells by regulating the FAK-Akt/mTOR pathway in vitro. Additionally, a Gene Set Enrichment Analysis using the TCGA and GSE62254 databases, and western blot data, showed that LMOD1 could promote an epithelial-mesenchymal transition (EMT), thus potentially affecting the occurrence of peritoneal metastasis of gastric cancer. Immunohistochemistry showed that LMOD1 was highly expressed in cancer tissues, and the prognosis of patients with high LMOD1 expression was poor.
CONCLUSIONS: LMOD1 is an oncogene associated with diffuse gastric cancer and can affect the occurrence and development of EMT by regulating the FAK-Akt/mTOR pathway. LMOD1 can therefore promote peritoneal metastasis of gastric cancer cells and can be used as a novel therapeutic target for gastric cancer.
METHODS: We standardized the gene expression data of five Gene Expression Omnibus gastric cancer databases and constructed a Weighted Co-expression Network Analysis (WGCNA) model based on clinicopathological information. The overall survival (OS) and disease-free survival (DFS) curves were extracted from the Cancer Genome Atlas (TCGA) and GSE62254 databases. Western blotting was used to measure protein expression in cells and tissues. Scratch and transwell experiments were used to test the migration ability of tumor cells. Immunohistochemistry was used to measure tissue protein expression in clinical tissue samples to correlate to survival data.
RESULTS: The WGCNA model demonstrated that blue cyan was highly correlated with the Lauren classification of the tumor (r = 0.24, P = 7 × 1016). A protein-protein interaction network was used to visualize the genes in the blue cyan module. The OS and PFS TCGA analysis revealed that LMOD1 was a gene of interest. The proportion of diffuse gastric cancer patients with high expression of LMOD1 was significantly higher than that of intestinal type patients. LMOD1 promoted the migration of gastric cancer cells by regulating the FAK-Akt/mTOR pathway in vitro. Additionally, a Gene Set Enrichment Analysis using the TCGA and GSE62254 databases, and western blot data, showed that LMOD1 could promote an epithelial-mesenchymal transition (EMT), thus potentially affecting the occurrence of peritoneal metastasis of gastric cancer. Immunohistochemistry showed that LMOD1 was highly expressed in cancer tissues, and the prognosis of patients with high LMOD1 expression was poor.
CONCLUSIONS: LMOD1 is an oncogene associated with diffuse gastric cancer and can affect the occurrence and development of EMT by regulating the FAK-Akt/mTOR pathway. LMOD1 can therefore promote peritoneal metastasis of gastric cancer cells and can be used as a novel therapeutic target for gastric cancer.
摘要：
背景：胃肿瘤的Lauren分类与预后密切相关。目的探讨胃癌Lauren分型的具体分子机制,为胃癌的治疗提供可能的理论依据。
方法：我们对5个基因表达综合胃癌数据库的基因表达数据进行了标准化，并基于临床病理信息构建了加权共表达网络分析（WGCNA）模型。从癌症基因组图谱(TCGA)和GSE62254数据库中提取总生存期(OS)和无病生存期(DFS)曲线。Western印迹用于测量细胞和组织中的蛋白质表达。Scratch和transwell实验用于测试肿瘤细胞的迁移能力。免疫组织化学用于测量临床组织样品中的组织蛋白表达以与存活数据相关联。
结果：WGCNA模型显示蓝青与肿瘤的Lauren分类高度相关（r=0.24，P=7×1016）。使用蛋白质-蛋白质相互作用网络来可视化蓝青色模块中的基因。OS和PFSTCGA分析揭示LMOD1是感兴趣的基因。弥漫性胃癌患者中LMOD1高表达的比例明显高于肠型患者。LMOD1通过体外调控FAK-Akt/mTOR通路促进胃癌细胞的迁移。此外,使用TCGA和GSE62254数据库的基因集富集分析，和蛋白质印迹数据，显示LMOD1可以促进上皮-间质转化（EMT），从而可能影响胃癌腹膜转移的发生。免疫组化显示LMOD1在癌组织中高表达,LMOD1高表达患者预后较差。
结论：LMOD1是与弥漫性胃癌相关的癌基因，可通过调节FAK-Akt/mTOR通路影响EMT的发生发展。因此,LMOD1可促进胃癌细胞的腹膜转移,可作为胃癌治疗的新靶点。
方法：我们对5个基因表达综合胃癌数据库的基因表达数据进行了标准化，并基于临床病理信息构建了加权共表达网络分析（WGCNA）模型。从癌症基因组图谱(TCGA)和GSE62254数据库中提取总生存期(OS)和无病生存期(DFS)曲线。Western印迹用于测量细胞和组织中的蛋白质表达。Scratch和transwell实验用于测试肿瘤细胞的迁移能力。免疫组织化学用于测量临床组织样品中的组织蛋白表达以与存活数据相关联。
结果：WGCNA模型显示蓝青与肿瘤的Lauren分类高度相关（r=0.24，P=7×1016）。使用蛋白质-蛋白质相互作用网络来可视化蓝青色模块中的基因。OS和PFSTCGA分析揭示LMOD1是感兴趣的基因。弥漫性胃癌患者中LMOD1高表达的比例明显高于肠型患者。LMOD1通过体外调控FAK-Akt/mTOR通路促进胃癌细胞的迁移。此外,使用TCGA和GSE62254数据库的基因集富集分析，和蛋白质印迹数据，显示LMOD1可以促进上皮-间质转化（EMT），从而可能影响胃癌腹膜转移的发生。免疫组化显示LMOD1在癌组织中高表达,LMOD1高表达患者预后较差。
结论：LMOD1是与弥漫性胃癌相关的癌基因，可通过调节FAK-Akt/mTOR通路影响EMT的发生发展。因此,LMOD1可促进胃癌细胞的腹膜转移,可作为胃癌治疗的新靶点。
