Li Zhang1, Wenquan Kang2, Xiaolan Lu1, Shiyang Ma1, Lei Dong1, Baicang Zou3. 1. Department of Gastroenterology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, Shaanxi, China. 2. Department of Gastroenterology, Shenzhen Sixth People's Hospital (Nanshan Hospital), Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen 518052, Guangdong, China. 3. Department of Gastroenterology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, Shaanxi, China. Electronic address: 744526131@qq.com.
Abstract
OBJECTIVE: This study aimed to identifying and validating therapeutic compounds which might have positive effects on patients with gastric cancer (GC) based on weighted gene co-expression network analysis (WGCNA) and connectivity map (CMap). METHODS: We performed WGCNA to gain insights into the molecular aspects of GC. Raw microarray datasets (including 132 samples) were downloaded from the Gene Expression Omnibus (GEO) website. We utilized the WGCNA to identify the coexpressed genes (modules) and modular hub genes after non-specific filtering. Furthermore, these differentially expressed genes were submitted to CMap analysis to identify candidate therapeutic compounds for GC. In experimental part, cell growth inhibition was evaluated by Cell Counting Kit-8 (CCK-8) and colony formation assays. Tumor growth was assessed using nude mice with xenografts established in vivo. QRT-PCR and western blot were used for determination of HDAC2 expression level and immunohistochemistry was performed to quantify HDAC2 in gastric tumor samples. RESULTS: Through WGCNA and CMap analysis, we found two potential therapeutic compounds, the valproic acid (VPA), which is the histone deacetylase (HDAC) inhibitor and lovastatin. HDAC2 was overexpressed in gastric cancer cell lines including AGS, BGC-823, NCI-N87 and MKN28. Dose-dependent inhibition of gastric cancer cells by VPA and lovastatin was verified in vitro. Apoptosis of GC cells was induced after treatment with VPA and lovastatin through suppressing HDAC2 expression. Furthermore, the inhibition of VPA with cisplatin and lovastatin with cisplatin were also dose-dependent and cisplatin exhibited synergistic effects. In the xenografts, similar results were found. CONCLUSION: WGCNA was able to identify significant groups of genes associated with cancer prognosis. Moreover, analysis of gene expression signature using CMap is a powerful way to explore potential therapeutics for human diseases. For treating GC, lovastatin may be a potential drug.
OBJECTIVE: This study aimed to identifying and validating therapeutic compounds which might have positive effects on patients with gastric cancer (GC) based on weighted gene co-expression network analysis (WGCNA) and connectivity map (CMap). METHODS: We performed WGCNA to gain insights into the molecular aspects of GC. Raw microarray datasets (including 132 samples) were downloaded from the Gene Expression Omnibus (GEO) website. We utilized the WGCNA to identify the coexpressed genes (modules) and modular hub genes after non-specific filtering. Furthermore, these differentially expressed genes were submitted to CMap analysis to identify candidate therapeutic compounds for GC. In experimental part, cell growth inhibition was evaluated by Cell Counting Kit-8 (CCK-8) and colony formation assays. Tumor growth was assessed using nude mice with xenografts established in vivo. QRT-PCR and western blot were used for determination of HDAC2 expression level and immunohistochemistry was performed to quantify HDAC2 in gastric tumor samples. RESULTS: Through WGCNA and CMap analysis, we found two potential therapeutic compounds, the valproic acid (VPA), which is the histone deacetylase (HDAC) inhibitor and lovastatin. HDAC2 was overexpressed in gastric cancer cell lines including AGS, BGC-823, NCI-N87 and MKN28. Dose-dependent inhibition of gastric cancer cells by VPA and lovastatin was verified in vitro. Apoptosis of GC cells was induced after treatment with VPA and lovastatin through suppressing HDAC2 expression. Furthermore, the inhibition of VPA with cisplatin and lovastatin with cisplatin were also dose-dependent and cisplatin exhibited synergistic effects. In the xenografts, similar results were found. CONCLUSION: WGCNA was able to identify significant groups of genes associated with cancer prognosis. Moreover, analysis of gene expression signature using CMap is a powerful way to explore potential therapeutics for human diseases. For treating GC, lovastatin may be a potential drug.