Development and Validation of a Novel Prognosis Prediction Model for Patients With Stomach Adenocarcinoma

被引:5
|
作者
Wang, Tong [1 ]
Wen, Weiwei [2 ]
Liu, Hongfei [3 ]
Zhang, Jun [1 ]
Zhang, Xiaofeng [4 ,5 ,6 ]
Wang, Yu [4 ,5 ,6 ]
机构
[1] Zhejiang Chinese Med Univ, Sch Life Sci, Hangzhou, Peoples R China
[2] Third Peoples Hosp Hangzhou, Dept Dermatol, Hangzhou, Peoples R China
[3] Ningbo Municipal Hosp Tradit Chinese Med, Dept Zhiweibing, Ningbo, Peoples R China
[4] Zhejiang Univ, Sch Med, Affiliated Hangzhou Peoples Hosp 1, Dept Gastroenterol, Hangzhou, Peoples R China
[5] Hangzhou Inst Digest Dis, Hangzhou, Peoples R China
[6] Key Lab Integrated Tradit Chinese & Western Med B, Hangzhou, Peoples R China
基金
中国博士后科学基金;
关键词
stomach adenocarcinoma; GEO; TCGA; differentially expressed genes; prognostic model; BIOMARKERS; PACKAGE; MFAP2;
D O I
10.3389/fmed.2021.793401
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background: Stomach adenocarcinoma (STAD) is a significant global health problem. It is urgent to identify reliable predictors and establish a potential prognostic model.Methods: RNA-sequencing expression data of patients with STAD were downloaded from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database. Gene expression profiling and survival analysis were performed to investigate differentially expressed genes (DEGs) with significant clinical prognosis value. Overall survival (OS) analysis and univariable and multivariable Cox regression analyses were performed to establish the prognostic model. Protein-protein interaction (PPI) network, functional enrichment analysis, and differential expression investigation were also performed to further explore the potential mechanism of the prognostic genes in STAD. Finally, nomogram establishment was undertaken by performing multivariate Cox regression analysis, and calibration plots were generated to validate the nomogram.Results: A total of 229 overlapping DEGs were identified. Following Kaplan-Meier survival analysis and univariate and multivariate Cox regression analysis, 11 genes significantly associated with prognosis were screened and five of these genes, including COL10A1, MFAP2, CTHRC1, P4HA3, and FAP, were used to establish the risk model. The results showed that patients with high-risk scores have a poor prognosis, compared with those with low-risk scores (p = 0.0025 for the training dataset and p = 0.045 for the validation dataset). Subsequently, a nomogram (including TNM stage, age, gender, histologic grade, and risk score) was created. In addition, differential expression and immunohistochemistry stain of the five core genes in STAD and normal tissues were verified.Conclusion: We develop a prognostic-related model based on five core genes, which may serve as an independent risk factor for survival prediction in patients with STAD.
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页数:16
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