Development and Validation of a Prognostic Nomogram for Gastric Cancer Based on DNA Methylation-Driven Genes
2019
Background: The aim of this study was to develop and validate a nomogram for predicting the overall survival of patients with gastric cancer (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 analysis, the least absolute shrinkage and selector operation (LASSO), and multivariate Cox regression analysis. After analyzing with clinical parameters, a nomogram was conducted and assessed with respect to its calibration, discrimination, and clinical usefulness. Another cohort (GSE62254), retrieved from the Gene Expression Omnibus (GEO), was used for external validation at last.
Findings: We built a six-gene signature (PODN, NPY, MICU3, TUBB6 and RHOJ were hypermethylated, and MYO1A was hypomethylated) associated with overall survival (OS) status (P < 0·05). Cox regression analysis indicated that risk score, age, and number of positive lymph nodes were significantly and independently associated with survival time in GC patients. A nomogram including these variables was constructed, which performed well in predicting the 1-, 3- and 5-year survival of GC patients. 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" ones.
Interpretation: 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 the risk score, age and number of positive lymph nodes, can be conveniently used to facilitate the individualized prediction of OS in patients with GC after surgery.
Funding Statement: This work was supported by the International Science and Technology Cooperation Projects (2016YFE0107100), the Capital Special Research Project for Health Development (2014-2-4012), the Beijing Natural Science Foundation (L172055 and 7192158), the National Ten-thousand Talent Program, the Fundamental Research Funds for the Central Universities (3332018032), the CAMS Innovation Fund for Medical Science (CIFMS) (2017-I2M-4-003 and 2018-I2M-3-001), the Support Project of High-level Teachers in Beijing Municipal Universities in the Period of 13th Five-year Plan (IDHT20190510), the Ministry of Science and Technology of People's Republic of China (2014CB910100), and the National Natural Science Foundation of China (81171899 and 81372230).
Declaration of Interests: The authors declare that they have no competing interests.
Ethics Approval Statement: Not required.
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