Development and Validation of a Prognostic Nomogram for Gastric Cancer Based on DNA Methylation-Driven Differentially Expressed Genes

被引:74
作者
Bai, Yi [1 ,4 ]
Wei, Chunlian [2 ]
Zhong, Yuxin [3 ]
Zhang, Yamin [4 ]
Long, Junyu [1 ]
Huang, Shan [2 ]
Xie, Fucun [1 ]
Tian, Yantao [3 ]
Wang, Xi [2 ]
Zhao, Haitao [1 ]
机构
[1] Chinese Acad Med Sci & Peking Union Med Coll, Peking Union Med Coll Hosp, Dept Liver Surg, Beijing, Peoples R China
[2] Capital Med Univ, Adv Innovat Ctr Human Brain Protect, Sch Basic Med Sci, Dept Immunol,Beijing Key Lab Canc Invas & Metasta, Beijing, Peoples R China
[3] Chinese Acad Med Sci & Peking Union Med Coll, Dept Pancreat & Gastr Surg, Natl Canc Ctr, Natl Clin Res Ctr Canc,Canc Hosp, Beijing, Peoples R China
[4] First Cent Hosp, Dept Hepatobiliary Surg, Tianjin, Peoples R China
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
nomogram; risk score; gastric cancer; DNA methylation; prognosis; BORDER MYOSIN IA; PROLIFERATION; ASSOCIATION; PROGRESSION; STATISTICS; BIOMARKER; PATTERNS; SURVIVAL; CELLS;
D O I
10.7150/ijbs.41587
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
070307 [化学生物学]; 071010 [生物化学与分子生物学];
摘要
Background/Aims: The incidence of gastric cancer (GC) ranks fifth among common tumors and GC is the third leading cause of cancer-related death worldwide. The aim of this study was to develop and validate a nomogram for predicting the overall survival (OS) of patients with GC. Methods: DNA methylation (DNAm)-driven genes were identified by integrating DNAm and gene expression profiling analyses from The Cancer Genome Atlas (TCGA) GC cohort. Then, a risk score model was built based on Kaplan-Meier (K-M), least absolute shrinkage and selector operation (LASSO), and multivariate Cox regression analyses. After analyzing the clinical parameters, a nomogram was constructed and assessed. Another cohort (GSE62254) was used for external validation. Results: Thirteen differentially expressed DNAm-driven genes were narrowed down to a six-gene signature (PODN, NPY, MICU3, TUBB6 and RHOJ were hypermethylated, and MYO1A was hypomethylated), which was associated with OS (P < 0.05) after survival and LASSO regression analyses. These differentially expressed genes (DEGs) with altered DNAm statuses were included in the prognostic risk score model. The univariate Cox regression analysis indicated that risk score, age, and number of positive lymph nodes were significantly associated with survival time in GC patients. The multivariate Cox regression analysis also indicated that these variables were significant prognostic factors for GC. A nomogram including these variables was constructed, and its performance in predicting the 1-, 3- and 5-year survival outcomes of GC patients was estimated through time-dependent receiver operating characteristic (ROC) curves. In addition, the clinical benefit of this model was revealed by decision curve analysis (DCA). Pathway enrichment analysis suggested that these DNAm-driven genes might impact tumor progression by affecting signaling pathways such as the "ECM RECEPTOR INTERACTION" and "DNA REPLICATION" pathways. Conclusions: The altered status of the DNAm-driven gene signature (PODN, MYO1A, NPY, MICU3, TUBB6 and RHOJ) was significantly associated with the OS of GC patients. A nomogram incorporating risk score, age and number of positive lymph nodes can be conveniently used to facilitate the individualized prediction of OS in patients with GC.
引用
收藏
页码:1153 / 1165
页数:13
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