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低级别胶质瘤中具有m6A修饰特征的新型三个枢纽长链非编码RNA的鉴定与验证

Identification and Validation of a Novel Three Hub Long Noncoding RNAs With m6A Modification Signature in Low-Grade Gliomas.

作者信息

Nguyen Quang-Huy, Nguyen Tin, Le Duc-Hau

机构信息

School of Computer Science and Engineering, Thuyloi University, Hanoi, Vietnam.

Department of Computer Science and Engineering, University of Nevada, Reno, NV, United States.

出版信息

Front Mol Biosci. 2022 Feb 14;9:801931. doi: 10.3389/fmolb.2022.801931. eCollection 2022.

Abstract

It has been evident that N6-methyladenosine (m6A)-modified long noncoding RNAs (m6A-lncRNAs) involves regulating tumorigenesis, invasion, and metastasis for various cancer types. In this study, we sought to pick computationally up a set of 13 hub m6A-lncRNAs in light of three state-of-the-art tools WGCNA, iWGCNA, and oCEM, and interrogated their prognostic values in brain low-grade gliomas (LGG). Of the 13 hub m6A-lncRNAs, we further detected three hub m6A-lncRNAs as independent prognostic risk factors, including and . Then, the m6ALncSig model was built based on these three hub m6A-lncRNAs. Patients with LGG next were divided into two groups, high- and low-risk, based on the median m6ALncSig score. As predicted, the high-risk group was more significantly related to mortality. The prognostic signature of m6ALncSig was validated using internal and external cohorts. In summary, our work introduces a high-confidence prognostic prediction signature and paves the way for using m6A-lncRNAs in the signature as new targets for treatment of LGG.

摘要

很明显,N6-甲基腺苷(m6A)修饰的长链非编码RNA(m6A-lncRNAs)参与调控多种癌症类型的肿瘤发生、侵袭和转移。在本研究中,我们试图根据三种先进工具WGCNA、iWGCNA和oCEM,通过计算筛选出一组13个枢纽m6A-lncRNAs,并研究它们在脑低级别胶质瘤(LGG)中的预后价值。在这13个枢纽m6A-lncRNAs中,我们进一步检测到三个枢纽m6A-lncRNAs作为独立的预后危险因素,包括 和 。然后,基于这三个枢纽m6A-lncRNAs构建了m6ALncSig模型。接下来,根据m6ALncSig评分中位数,将LGG患者分为高风险和低风险两组。正如预测的那样,高风险组与死亡率的相关性更显著。使用内部和外部队列验证了m6ALncSig的预后特征。总之,我们的工作引入了一个高可信度的预后预测特征,并为将特征中的m6A-lncRNAs用作LGG治疗的新靶点铺平了道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a9b8/8882983/87c6111432fb/fmolb-09-801931-g001.jpg

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