J Cancer 2020; 11(15):4352-4365. doi:10.7150/jca.44436

Research Paper

DNA methylation profiling to predict overall survival risk in gastric cancer: development and validation of a nomogram to optimize clinical management

Xianxiong Ma1,*, Hengyu Chen2,3,*, Guobin Wang1, Lei Li4✉, Kaixiong Tao1✉

1. Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
2. Department of Pancreatic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
3. NHC Key Laboratory of Hormones and Development, Tianjin Institute of Endocrinology, Tianjin Medical University Chu Hsien-I Memorial Hospital, Tianjin 300070, China.
4. Department of Breast and Thyroid Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
*Equal contribution and Co-first authors

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Citation:
Ma X, Chen H, Wang G, Li L, Tao K. DNA methylation profiling to predict overall survival risk in gastric cancer: development and validation of a nomogram to optimize clinical management. J Cancer 2020; 11(15):4352-4365. doi:10.7150/jca.44436. Available from http://www.jcancer.org/v11p4352.htm

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Abstract

DNA methylation has been reported to serve an important role in the carcinogenesis and development of gastric cancer. Our aim was to systematically develop an individualized prediction model of the survival risk combing clinical and methylation factors in gastric cancer. A univariate Cox proportional risk regression analysis was used to identify the prognosis-associated methylation sites based on the differentially expressed methylation sites between early and advanced gastric cancer group, then we applied least absolute shrinkage and selection operator (LASSO) Cox regression model to screen candidate methylation sites. Subsequently, multivariate Cox proportional risk regression analysis was conducted to identify predictive signature according to the candidate sites. Relative operating characteristic curve (ROC) analysis manifested that an 11-methylation signature exhibited great predictive efficiency for 1-, 3-, 5-year survival events. Patients in the low-risk group classified according to 11-methylation signature-based risk score yield significantly better survival than that in high-risk group. Moreover, Cox regression analysis combing methylation-based risk score and other clinical factors indicated that 11-methylation signature served as an independent risk factor. The predictive value of risk score was validated in the testing dataset. In addition, a nomogram was constructed and the ROC as well as calibration plots analysis demonstrated the good performance and clinical application of the nomogram. In conclusion, the result suggested the 11-DNA methylation signature may be potentially independent prognostic marker and functioned as a significant tool for guiding the clinical prediction of gastric cancer patients' overall survival.

Keywords: Signature, DNA methylation, gastric cancer, OS, Nomogram