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Prognostic value of sorting nexin 10 weak expression in stomach adenocarcinoma revealed by weighted gene co-expression network analysis
AIM: To detect significant clusters of co-expressed genes associated with tumorigenesis that might help to predict stomach adenocarcinoma (SA) prognosis. METHODS: The Cancer Genome Atlas database was used to obtain RNA sequences as well as complete clinical data of SA and adjacent normal tissues fro...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6250920/ https://www.ncbi.nlm.nih.gov/pubmed/30487700 http://dx.doi.org/10.3748/wjg.v24.i43.4906 |
Sumario: | AIM: To detect significant clusters of co-expressed genes associated with tumorigenesis that might help to predict stomach adenocarcinoma (SA) prognosis. METHODS: The Cancer Genome Atlas database was used to obtain RNA sequences as well as complete clinical data of SA and adjacent normal tissues from patients. Weighted gene co-expression network analysis (WGCNA) was used to investigate the meaningful module along with hub genes. Expression of hub genes was analyzed in 362 paraffin-embedded SA biopsy tissues by immunohistochemical staining. Patients were classified into two groups (according to expression of hub genes): Weak expression and over-expression groups. Correlation of biomarkers with clinicopathological factors indicated patient survival. RESULTS: Whole genome expression level screening identified 6,231 differentially expressed genes. Twenty-four co-expressed gene modules were identified using WGCNA. Pearson’s correlation analysis showed that the tan module was the most relevant to tumor stage (r = 0.24, P = 7 × 10(-6)). In addition, we detected sorting nexin (SNX)10 as the hub gene of the tan module. SNX10 expression was linked to T category (P = 0.042, χ(2) = 8.708), N category (P = 0.000, χ(2) = 18.778), TNM stage (P = 0.001, χ(2) = 16.744) as well as tumor differentiation (P = 0.000, χ(2) = 251.930). Patients with high SNX10 expression tended to have longer disease-free survival (DFS; 44.97 mo vs 33.85 mo, P = 0.000) as well as overall survival (OS; 49.95 vs 40.84 mo, P = 0.000) in univariate analysis. Multivariate analysis showed that dismal prognosis could be precisely predicted clinicopathologically using SNX10 [DFS: P = 0.014, hazard ratio (HR) = 0.698, 95% confidence interval (CI): 0.524-0.930, OS: P = 0.017, HR = 0.704, 95%CI: 0.528-0.940]. CONCLUSION: This study provides a new technique for screening prognostic biomarkers of SA. Weak expression of SNX10 is linked to poor prognosis, and is a suitable prognostic biomarker of SA. |
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