Dataset Information

Gene Signatures and Prognostic Values of m⁶A Genes in Nasopharyngeal Carcinoma.

ABSTRACT: Nasopharyngeal carcinoma (NPC) is a malignant tumor with a high rate of local invasion and early distant metastasis. Accumulating studies suggest that N6-methyladenosine methylation (m⁶A) is closely related to tumorigenesis. However, the relationship between m⁶A-related genes and prognosis of NPC is poorly understood. Our research aims to discover the prognostic value of m⁶A RNA methylation genes in NPC. In this study, we analyzed the differentially expressed m⁶A-related genes between NPC samples and normal control samples and found that two upregulated genes (YTHDF3 and IGF2BP2) and one downregulated gene (METTL3) were overlapped in GSE68799 and GSE53819. Next, we found that high expression of IGF2BP1 and low expression of METTL3 and YTHDF3 in NPC patients showed poor progression-free survival (PFS). Subsequently, the four m⁶A genes were selected for consensus cluster analysis, and risk models were established. The risk signature, using three genes (GF2BP1 + IGF2BP2 + METTL3), was an independent prognostic factor and predicts the clinicopathological features of NPC. Additionally, the GO, KEGG analysis, and CIBERSORT algorithm revealed that the risk signature was closely associated to immune infiltration in NPC. Finally, the expression and clinical significance of METTL3 were successfully validated in NPC tissues using immunohistochemical techniques. In conclusion, our finding revealed the potential role of m⁶A modification in NPC, providing novel insight into NPC prognosis and therapeutic strategies.

SUBMITTER: Lu S

PROVIDER: S-EPMC7300221 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Gene Signatures and Prognostic Values of m6A Genes in Nasopharyngeal Carcinoma.

Lu Shanshan S Yu Zhengzheng Z Xiao Zhiqiang Z Zhang Yiya Y

Frontiers in oncology 20200611

Nasopharyngeal carcinoma (NPC) is a malignant tumor with a high rate of local invasion and early distant metastasis. Accumulating studies suggest that N6-methyladenosine methylation (m6A) is closely related to tumorigenesis. However, the relationship between m6A-related genes and prognosis of NPC is poorly understood. Our research aims to discover the prognostic value of m6A RNA methylation genes in NPC. In this study, we analyzed the differentially expressed m<s ...[more]

PMID: 32596151

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Project description:BackgroundDiagnostic models based on gene signatures of nasopharyngeal carcinoma (NPC) were constructed by random forest (RF) and artificial neural network (ANN) algorithms. Least absolute shrinkage and selection operator (Lasso)-Cox regression was used to select and build prognostic models based on gene signatures. This study contributes to the early diagnosis and treatment, prognosis, and molecular mechanisms associated with NPC.MethodsTwo gene expression datasets were downloaded from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) associated with NPC were identified by gene expression differential analysis. Subsequently, significant DEGs were identified by a RF algorithm. ANN were used to construct a diagnostic model for NPC. The performance of the diagnostic model was evaluated by area under the curve (AUC) values using a validation set. Lasso-Cox regression examined gene signatures associated with prognosis. Overall survival (OS) and disease-free survival (DFS) prediction models were constructed and validated from The Cancer Genome Atlas (TCGA) database and the International Cancer Genome Consortium (ICGC) database.ResultsA total of 582 DEGs associated with NPC were identified, and 14 significant genes were identified by the RF algorithm. A diagnostic model for NPC was successfully constructed using ANN, and the validity of the model was confirmed on the training set AUC =0.947 [95% confidence interval (CI): 0.911-0.969] and the validation set AUC =0.864 (95% CI: 0.828-0.901). The 24-gene signatures associated with prognosis were identified by Lasso-Cox regression, and prediction models for OS and DFS of NPC were constructed on the training set. Finally, the ability of the model was validated on the validation set.ConclusionsSeveral potential gene signatures associated with NPC were identified, and a high-performance predictive model for early diagnosis of NPC and a prognostic prediction model with robust performance were successfully developed. The results of this study provide valuable references for early diagnosis, screening, treatment and molecular mechanism research of NPC in the future.

Dataset Information

Gene Signatures and Prognostic Values of m⁶A Genes in Nasopharyngeal Carcinoma.

Publications

Gene Signatures and Prognostic Values of m<sup>6</sup>A Genes in Nasopharyngeal Carcinoma.

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