11 December 2019 : Laboratory Research
The Prognostic Value of m6A RNA Methylation Regulators in Colon Adenocarcinoma
Tao Liu1ABCDEF, Chenyao Li1AB, Lipeng Jin1BD, Chao Li1ACDEF*, Lei Wang1ABCDEFGDOI: 10.12659/MSM.920381
Med Sci Monit 2019; 25:9435-9445
Abstract
BACKGROUND: The RNA-seq FPKM data of 331 colorectal adenocarcinoma samples in The Cancer Genome Atlas database with matching clinical data were analyzed in order to reveal the prognostic value of m6A RNA methylation regulators in colon adenocarcinoma.
MATERIAL AND METHODS: The expression of 13 m6A RNA methylated regulators in samples were analyzed. The samples were classified into Cluster I and II by consistent clustering. The gene distribution was analyzed by principal component analysis. Further functional analysis of selected m6A RNA genes was performed and potential risk characteristics was developed using Lasso Cox regression algorithm. Using minimum criteria, the risk coefficients of YTHDF1 and HNRNPC were detected for Cluster II. Patients were divided into high-risk and low-risk subgroups based on the risk characteristics. The clinical data were analyzed by univariate and multivariate Cox regression analysis.
RESULTS: Expression of the detected m6A RNA methylated regulators except YTHDC2 in tumors were significantly different from their adjacent mucosa. Among them, only ALKBH5 and METTL4 were downregulated in tumors. The gene distribution between the 2 subgroups were different. The expression of m6A RNA methylation regulators including YTHDF1, HNRNPC, YTHDC2, YTHDC1, ZC3H13, and RBM15 were different between the 2 groups (P<0.05). The prognostic characteristics between the high-risk and low-risk groups were significant different (P<0.05), which had a good predictive significance of prognosis area under the curve (AUC)=0.62). Risk scores were less than 0.05, suggesting risk score was an independent prognostic factor for colon adenocarcinoma.
CONCLUSIONS: m6A RNA methylation regulators YTHDF1 and HNRNPC can be used as prognostic factors of colon cancer, which has potential value for colon cancer treatment.
Keywords: Colorectal Neoplasms, Hereditary Nonpolyposis, Methyltransferases, RNA Processing, Post-Transcriptional, Adenosine Triphosphatases, Algorithms, Cluster Analysis, Colon, Colonic Neoplasms, Databases, Genetic, Gene Expression Profiling, Heterogeneous-Nuclear Ribonucleoprotein Group C, Methylation, Multivariate Analysis, RNA, RNA Helicases, RNA-Binding Proteins, tRNA Methyltransferases
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