Yandong Miao, Bin Su, Xiaolong Tang, Jiangtao Wang, Wuxia Quan, Yonggang Chen, Denghai Mi
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引用次数: 1
Abstract
N6-methyladenosine (m6A) RNA methylation is correlated with carcinogenesis and dynamically possessed through the m6A RNA methylation regulators. This paper aimed to explore 13 m6A RNA methylation regulators' role in gastrointestinal cancer (GIC) and determine the risk model and prognosis value of m6A RNA methylation regulators in GIC. We used several bioinformatics methods to identify the differential expression of m6A RNA methylation regulators in GIC, constructed a prognostic model, and carried out functional enrichment analysis. Eleven of 13 m6A RNA methylation regulators were differentially expressed in different clinicopathological characteristics of GIC, and m6A RNA methylation regulators were nearly associated with GIC. We constructed a risk model based on five m6A RNA methylation regulators (METTL3, FTO, YTHDF1, ZC3H13, and WTAP); the risk score is an independent prognosis biomarker. Moreover, the five m6A RNA methylation regulators can also forecast the 1-, 3- and 5-year overall survival through a nomogram. Furthermore, four hallmarks of oxidative phosphorylation, glycolysis, fatty acid metabolism, and cholesterol homoeostasis gene sets were significantly enriched in GIC. m6A RNA methylation regulators were related to the malignant clinicopathological characteristics of GIC and may be used for prognostic stratification and development of therapeutic strategies.
期刊介绍:
IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells.
The scope includes the following topics:
Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.