Establishment of a prognostic model of Wnt signaling pathway related genes in gastric cancer
- VernacularTitle:胃癌Wnt信号通路相关基因预后模型的构建
- Author:
Lianlian TIAN
1
;
Jun ZHU
2
;
Qian MA
2
;
Han PENG
3
;
Yiran ZHANG
4
;
Zhaoxi WANG
4
;
Rui CHEN
5
Author Information
- Publication Type:Journal Article
- Keywords: gastric cancer; Wnt signaling pathway; prognosis-related risk model
- From: Journal of Xi'an Jiaotong University(Medical Sciences) 2022;43(2):252-257
- CountryChina
- Language:Chinese
- Abstract: 【Objective】 To confirm the role of Wnt signaling pathway in the occurrence and development of gastric cancer （GC）， establish a prognostic model composed of Wnt pathway related genes， and then evaluate the predictive value of the model. 【Methods】 We downloaded the gene expression data and survival data of GC in TCGA database， and used GSEA enrichment analysis to verify the enrichment of Wnt pathway in GC and para-cancer samples. In this study， univariable COX regression analysis and survival curve analysis were used to select the prognosis-related genes of GC. Then the multivariate COX proportional hazard regression model was used to obtain the prognostic model of Wnt signaling pathway related genes. Then， receiver operating characteristic （ROC） curve and forest plot were used to verify the clinical predictive value of the model. The model was then validated in GEO external database. Finally， by utilizing quantitative real-time PCR （qPCR）， we detected the expressions of Wnt signaling pathway related genes in 8 pairs of clinical GC and para-cancer samples. 【Results】 We downloaded 32 samples of normal para-cancer samples and 375 cancer samples and their corresponding clinical data. GSEA enrichment showed that compared with normal samples， Wnt pathway was significantly enriched in GC samples （P<0.05）. The results of univariate COX analysis showed that 13 Wnt pathway genes were closely related to the prognosis of GC patients. Multivariate COX determined that the model was multiplied and accumulated by ETV2， SERPINE1， CPZ， VPS35 and IGFBP1 and their corresponding coefficient β. The survival curve and ROC curve showed that the model could accurately predict the prognosis of GC patients， and the 1-year， 3-year， and 5-year areas under the curve （AUC） were 68.0%， 69.4% and 78.5%， respectively. Clinical univariate and multivariate COX analyses showed that the model could become an independent prognostic factor other than TNM system of GC. The external data set （GSE84437） validation results of GC showed that the model could better predict the prognosis of GC patients. qPCR results indicated that ETV2， SERPINE1， CPZ， VPS35 and IGFBP1 expressions were upregulated in GC samples compared with para-cancer samples. 【Conclusion】 This study further confirmed that Wnt pathway plays an important role in the progress of GC from the perspective of bioinformatics， and we have established a prognosis-related risk model， providing a new perspective for clinical genetic testing， targeted therapy and individualized therapy.
