Cargando…

A seven-m(6)A regulator-related CpG site-based prognostic signature for endometrial carcinoma

BACKGROUND: Endometrial carcinoma (EC) has become a common gynecologic malignancy with a high mortality. The m(6)A regulators have been identified to be closely associated with multiple human cancers including EC. However, the CpG methylation signature related to m(6)A regulators in EC remains uncle...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Xiang, Pang, Xuecheng, Huang, Yue, Qian, Sumin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8294886/
https://www.ncbi.nlm.nih.gov/pubmed/34398021
http://dx.doi.org/10.1097/MD.0000000000026648
Descripción
Sumario:BACKGROUND: Endometrial carcinoma (EC) has become a common gynecologic malignancy with a high mortality. The m(6)A regulators have been identified to be closely associated with multiple human cancers including EC. However, the CpG methylation signature related to m(6)A regulators in EC remains unclear. METHOD: The methylation profiles of EC patients including cancer samples and adjacent normal samples were obtained from The Cancer Genome Atlas (TCGA) database. The CpG sites in 20 m(6)A regulators were identified. Univariate Cox regression and LASSO Cox regression analysis were used to screen key CpG sites which were located at m(6)A regulators and significantly related to the prognosis of EC. The predictive model for EC prognosis was constructed, and multivariate Cox regression analysis was applied to explore whether the risk score derived from the model could function as an independent signature for EC prognosis. Meanwhile, a nomogram model was constructed by combing the independent prognostic signatures for prediction of the long-term survival in EC patients. RESULTS: A total of 396 CpG sites located at 20 m(6)A regulators were identified. A specific predictive model for EC prognosis based on 7 optimal CpG sites was constructed, which presented good performance in prognosis prediction of EC patients. Moreover, risk score was determined to be an independent signature both in the training set and validation set. By bringing in three independent prognostic factors (age, risk score, and TNM stage), the nomogram was constructed and could effectively predict the 3- and 5-year survival rates of EC patients. CONCLUSION: Our study suggested that the CpG sites located at m(6)A regulators might be considered as potential prognostic signatures for EC patients.