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识别和潜在机制的 7 微 RNA 特征,预测预后患者的低级别胶质瘤。

Identification and Potential Mechanisms of a 7-MicroRNA Signature That Predicts Prognosis in Patients with Lower-Grade Glioma.

机构信息

Department of Neurosurgery, The First Affiliated Hospital of Nanchang University, Nanchang, China.

Department of Neurosurgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.

出版信息

J Healthc Eng. 2021 Nov 20;2021:3251891. doi: 10.1155/2021/3251891. eCollection 2021.

DOI:10.1155/2021/3251891
PMID:34845420
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8627350/
Abstract

BACKGROUND

Lower-grade glioma is an intracranial cancer that may develop into glioblastoma with high mortality. The main objective of our study is to develop microRNA for LGG patients which will provide novel prognostic biomarkers along with therapeutic targets.

METHODS

Clinicopathological data of LGG patients and their RNA expression profile were downloaded through The Cancer Genome Atlas Relevant expression profiles of RNA, and clinicopathological data of the LGG patients had been extracted from the database of "The Cancer Genome Atlas." Differential expression analysis had been conducted for identification of the differentially expressed microRNAs as well as mRNAs in LGG samples and normal ones. ROC curves and K-M plots were plotted to confirm performance and for predictive accuracy. For the confirmation of microRNAs as an independent prognostic factor, an independent prognosis analysis was conducted. Moreover, target differentially expressed genes of these identified prognostic microRNAs that were extracted and protein-protein interaction networks were developed. Moreover, the biological functions of signature were determined through Genome Ontology analysis, genome pathway analysis, and Kyoto Encyclopedia of Genes.

RESULTS

7-microRNA signature was identified that has the ability of categorization of individuals with LGG into high- and low-risk groups on the basis of significant difference in survival during training and testing cohorts ( < 0.001). The 7-microRNA signature had appeared to be robust in predictive accuracy (all AUC> 0.65). It was also approved with multivariate Cox regression along with some traditional clinical practices that we can use 7-microRNA signature for therapeutic purposes as a self-regulating predictive OS factor ( < 0.001). KEGG and Gene Ontology (GO) analyses reported that 7-microRNAs had mainly developed in important pathways related with glioma, e.g., the "cAMP signaling pathway," "glutamatergic synapses," and "calcium signaling pathway".

CONCLUSION

A newly discovered 7-microRNA signature could be a potential target for the diagnosis and treatment for LGG patients.

摘要

背景

低级别神经胶质瘤是一种颅内癌症,可能发展成死亡率较高的胶质母细胞瘤。我们研究的主要目的是为 LGG 患者开发 microRNA,为其提供新的预后生物标志物和治疗靶点。

方法

通过癌症基因组图谱相关表达谱,下载 LGG 患者的临床病理数据及其 RNA 表达谱,并从癌症基因组图谱数据库中提取 LGG 患者的临床病理数据。对 LGG 样本和正常样本中的差异表达 microRNA 和 mRNAs 进行差异表达分析。绘制 ROC 曲线和 K-M 图以确认性能和预测准确性。为了确认 microRNA 作为独立的预后因素,进行了独立预后分析。此外,还提取了这些鉴定的预后 microRNA 的差异表达靶基因,并构建了蛋白质-蛋白质相互作用网络。此外,通过基因组本体论分析、基因组途径分析和京都基因与基因组百科全书,确定特征的生物学功能。

结果

确定了 7 个 microRNA 特征,该特征能够根据训练和测试队列中生存差异将 LGG 个体分为高风险和低风险组(<0.001)。7 个 microRNA 特征在预测准确性方面表现出稳健(所有 AUC>0.65)。它还通过多变量 Cox 回归以及一些传统的临床实践得到了验证,我们可以将 7 个 microRNA 特征用作治疗目的的自我调节预测 OS 因素(<0.001)。KEGG 和基因本体论(GO)分析报告称,7 个 microRNAs 主要在与神经胶质瘤相关的重要途径中发育,例如“cAMP 信号通路”、“谷氨酸能突触”和“钙信号通路”。

结论

新发现的 7 个 microRNA 特征可能成为 LGG 患者诊断和治疗的潜在靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f750/8627350/b67964375f16/JHE2021-3251891.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f750/8627350/d2360a273c78/JHE2021-3251891.001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f750/8627350/625580cedf8a/JHE2021-3251891.008.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f750/8627350/d2360a273c78/JHE2021-3251891.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f750/8627350/8403b6f653c1/JHE2021-3251891.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f750/8627350/d3177d5034be/JHE2021-3251891.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f750/8627350/e485981a6b3b/JHE2021-3251891.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f750/8627350/783a250b782a/JHE2021-3251891.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f750/8627350/a68b31155788/JHE2021-3251891.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f750/8627350/dcbaf4b9d54f/JHE2021-3251891.007.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f750/8627350/b67964375f16/JHE2021-3251891.009.jpg

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