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Co-expression network analysis identified CDH11 in association with progression and prognosis in gastric cancer.
Chen, Peng-Fei; Wang, Fan; Nie, Jia-Yan; Feng, Jue-Rong; Liu, Jing; Zhou, Rui; Wang, Hong-Ling; Zhao, Qiu.
Affiliation
  • Chen PF; Department of Gastroenterology, Zhongnan Hospital of Wuhan University, Wuhan, China, zhaoqiuwhu@163.com; shwh312@163.com.
  • Wang F; Hubei Clinical Center & Key Laboratory of Intestinal & Colorectal Diseases, Wuhan, China, zhaoqiuwhu@163.com; shwh312@163.com.
  • Nie JY; Department of Gastroenterology, The Central Hospital of Enshi Autonomous Prefecture, Enshi, China.
  • Feng JR; Department of Gastroenterology, Zhongnan Hospital of Wuhan University, Wuhan, China, zhaoqiuwhu@163.com; shwh312@163.com.
  • Liu J; Hubei Clinical Center & Key Laboratory of Intestinal & Colorectal Diseases, Wuhan, China, zhaoqiuwhu@163.com; shwh312@163.com.
  • Zhou R; Department of Gastroenterology, Zhongnan Hospital of Wuhan University, Wuhan, China, zhaoqiuwhu@163.com; shwh312@163.com.
  • Wang HL; Hubei Clinical Center & Key Laboratory of Intestinal & Colorectal Diseases, Wuhan, China, zhaoqiuwhu@163.com; shwh312@163.com.
  • Zhao Q; Department of Gastroenterology, Zhongnan Hospital of Wuhan University, Wuhan, China, zhaoqiuwhu@163.com; shwh312@163.com.
Onco Targets Ther ; 11: 6425-6436, 2018.
Article in En | MEDLINE | ID: mdl-30323620
BACKGROUND AND AIMS: Gastric cancer (GC) is one of the most common cancers worldwide, and its pathogenesis is related to a complex network of gene interactions. The aims of our study were to find hub genes associated with the progression and prognosis of GC and illustrate the underlying mechanisms. METHODS: Weighted gene co-expression network analysis (WGCNA) was conducted using the microarray dataset and clinical data of GC patients from Gene Expression Omnibus (GEO) database to identify significant gene modules and hub genes associated with TNM stage in GC. Functional enrichment analysis and protein-protein interaction network analysis were performed using the significant module genes. We regarded the common hub genes in the co-expression network and protein-protein interaction (PPI) network as "real" hub genes for further analysis. Hub gene was validated in another independent dataset and The Cancer Genome Atlas (TCGA) dataset. RESULTS: In the significant purple module (R 2=0.35), a total of 12 network hub genes were identified, among which six were also hub nodes in the PPI network of the module genes. Functional annotation revealed that the genes in the purple module focused on the biological processes of system development, biological adhesion, extracellular structure organization and metabolic process. In terms of validation, CDH11 had a higher correlation with the TNM stage than other hub genes and was strongly correlated with biological adhesion based on GO functional enrichment analysis. Data obtained from the Gene Expression Profiling Interactive Analysis (GEPIA) showed that CDH11 expression had a strong positive correlation with GC stages (P<0.0001). In the testing set and Oncomine dataset, CDH11 was highly expressed in GC tissues (P<0.0001). Survival analysis indicated that samples with a high CDH11 expression showed a poor prognosis. Cox regression analysis demonstrated an independent predictor of CDH11 expression in GC prognosis (HR=1.482, 95% CI: 1.015-2.164). Furthermore, gene set enrichment analysis (GSEA) demonstrated that multiple tumor-related pathways, especially focal adhesion, were enriched in CDH11 highly expressed samples. CONCLUSION: CDH11 was identified and validated in association with progression and prognosis in GC, probably by regulating biological adhesion and focal adhesion-related pathways.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Onco Targets Ther Year: 2018 Document type: Article Country of publication: New Zealand

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Onco Targets Ther Year: 2018 Document type: Article Country of publication: New Zealand