m6A RNA甲基化调控因子相关胃肠道肿瘤预后模型的构建与验证

IF 1.9 4区 生物学 Q4 CELL BIOLOGY IET Systems Biology Pub Date : 2022-02-17 DOI:10.1049/syb2.12040
Yandong Miao, Bin Su, Xiaolong Tang, Jiangtao Wang, Wuxia Quan, Yonggang Chen, Denghai Mi
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引用次数: 1

摘要

n6 -甲基腺苷(m6A) RNA甲基化与癌症发生相关,并通过m6A RNA甲基化调控因子动态实现。本文旨在探讨13种m6A RNA甲基化调节剂在胃肠道癌(GIC)中的作用,确定m6A RNA甲基化调节剂在GIC中的风险模型和预后价值。我们使用多种生物信息学方法鉴定了m6A RNA甲基化调控因子在GIC中的差异表达,构建了预后模型,并进行了功能富集分析。13个m6A RNA甲基化调节因子中有11个在GIC的不同临床病理特征中存在差异表达,m6A RNA甲基化调节因子与GIC几乎相关。我们基于5个m6A RNA甲基化调节因子(METTL3、FTO、YTHDF1、ZC3H13和WTAP)构建了风险模型;风险评分是一个独立的预后生物标志物。此外,5种m6A RNA甲基化调节因子也可以通过nomogram预测1、3和5年的总生存率。此外,氧化磷酸化、糖酵解、脂肪酸代谢和胆固醇同质平衡基因组在GIC中显著富集。m6A RNA甲基化调节因子与GIC的恶性临床病理特征有关,可用于预后分层和治疗策略的制定。
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Construction and validation of m6A RNA methylation regulators associated prognostic model for gastrointestinal cancer

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.

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来源期刊
IET Systems Biology
IET Systems Biology 生物-数学与计算生物学
CiteScore
4.20
自引率
4.30%
发文量
17
审稿时长
>12 weeks
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.
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