Yuen Tan1,2, Qingchuan Chen2, Siwei Pan2, Wen An2, Huimian Xu3, Yao Xing4, Jianjun Zhang5. 1. Department of Gastric Surgery, Liaoning Cancer Hospital and Institute, Cancer Hospital of China Medical University, No 44 of Xiaoheyan Road, Dadong District, Shenyang, 110042, China. 2. Department of Surgical Oncology, First Affiliated Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, China. 3. Department of Surgical Oncology, First Affiliated Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, China. xuhuimian@126.com. 4. Department of Cell Biology, Key Laboratory of Cell Biology of Ministry of Public Health, and Key Laboratory of Medical Cell Biology of Ministry of Education, China Medical University, No. 77, Puhe Road, Shenyang North New Area, Shenyang, 110122, Liaoning, China. 1163623517@qq.com. 5. Department of Gastric Surgery, Liaoning Cancer Hospital and Institute, Cancer Hospital of China Medical University, No 44 of Xiaoheyan Road, Dadong District, Shenyang, 110042, China. zhangjianjun@cancerhosp-ln-cmu.com.
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. CONCLUSION: 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.
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. CONCLUSION: 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.
Authors: Gunter von Minckwitz; Marion Procter; Evandro de Azambuja; Dimitrios Zardavas; Mark Benyunes; Giuseppe Viale; Thomas Suter; Amal Arahmani; Nathalie Rouchet; Emma Clark; Adam Knott; Istvan Lang; Christelle Levy; Denise A Yardley; Jose Bines; Richard D Gelber; Martine Piccart; Jose Baselga Journal: N Engl J Med Date: 2017-06-05 Impact factor: 91.245
Authors: Gunter von Minckwitz; Chiun-Sheng Huang; Max S Mano; Sibylle Loibl; Eleftherios P Mamounas; Michael Untch; Norman Wolmark; Priya Rastogi; Andreas Schneeweiss; Andres Redondo; Hans H Fischer; William Jacot; Alison K Conlin; Claudia Arce-Salinas; Irene L Wapnir; Christian Jackisch; Michael P DiGiovanna; Peter A Fasching; John P Crown; Pia Wülfing; Zhimin Shao; Elena Rota Caremoli; Haiyan Wu; Lisa H Lam; David Tesarowski; Melanie Smitt; Hannah Douthwaite; Stina M Singel; Charles E Geyer Journal: N Engl J Med Date: 2018-12-05 Impact factor: 176.079