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The methylation modification of m6A regulators contributes to the prognosis of ovarian cancer

BACKGROUND: Ovarian cancer (OV) is the leading cause of death in gynecological cancer. The dysregulation of N6-methyladenosine (m6A) modification is commonly found in cancers. However, there is a lack of research into m6A RNA methylation regulators in OV. METHODS: The RNA-Seq of 379 OV tissues and 8...

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Detalles Bibliográficos
Autores principales: Zhu, Wenjing, Zhao, Long, Kong, Beihua, Liu, Ying, Zou, Xin, Han, Tongqin, Shi, Yongmei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8848366/
https://www.ncbi.nlm.nih.gov/pubmed/35282121
http://dx.doi.org/10.21037/atm-21-6462
Descripción
Sumario:BACKGROUND: Ovarian cancer (OV) is the leading cause of death in gynecological cancer. The dysregulation of N6-methyladenosine (m6A) modification is commonly found in cancers. However, there is a lack of research into m6A RNA methylation regulators in OV. METHODS: The RNA-Seq of 379 OV tissues and 88 healthy ovarian tissues was downloaded from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases, respectively. A Gene Ontology (GO) functional analysis was performed to verify the function of m6A RNA methylation regulators. Kaplan-Meier (K-M) curves and the log-rank (Mantel-Cox) test were used for the survival analysis. A Cox regression analysis was used to identify the genes related to overall survival (OS) and build the prediction model. RESULTS: m6A RNA methylation regulators were dysregulated in OV tissues compared with normal tissues (P<0.05), and patients with a high expression of KIAA1429 and YTHDC2 had a poor prognosis (P<0.05). A prognostic model was constructed based on the m6A RNA methylation regulators. Based on the risk signature, the patients were classified into high- and low-risk groups. The low-risk group’s OS rate was significantly better than that of the high-risk group. The validity and accuracy of the prognostic model were verified by using TCGA and Gene Expression Omnibus (GEO) datasets, and the risk score from the prognostic model acted as an independent prognostic indicator in predicting the survival of OV patients. CONCLUSIONS: m6A RNA methylation regulators were dysregulated in OV tissues. More importantly, the prognostic model comprising the five selected m6A RNA methylation regulators could be a valuable tool for predicting the prognosis of OV patients.