lncRNA通过调控miR-708-5p和miR-135b-5p增强胰腺癌上皮-间质转化：一种生物信息学方法

The lncRNA Enhances Pancreatic Cancer EMT by Regulating miR-708-5p and miR-135b-5p: A Bioinformatics Approach.

作者信息

Askari Nahid, Pirouz Marziye Shad, Mafikandi Vida, Hadizadeh Morteza, Mousavi Seyedeh Zahra

机构信息

Department of Biotechnology, Institute of Sciences and High Technology and Environmental Sciences, Graduate University of Advanced Technology, Kerman, Iran.

Laboratory of Complex Biological Systems and Bioinformatics (CBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.

出版信息

Iran J Public Health. 2024 Jul;53(7):1659-1669. doi: 10.18502/ijph.v53i7.16060.

DOI:10.18502/ijph.v53i7.16060

PMID:39086404

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11287582/

Abstract

BACKGROUND

Pancreatic cancer (PC) is an exceedingly malignant ailment that is not only characterized by its insidious onset and rapid progression but also by its poor therapeutic effects. Recently, emerging evidence has shed light on the significant role that non-coding RNAs (ncRNAs), particularly long ncRNAs (lncRNAs) and microRNAs (miRNAs), play in the pathogenesis of PC. This investigation aimed to construct a network of interactions between miRNAs, lncRNAs, and mRNAs, as well as to perform correlation analyses in the context of PC.

METHODS

This study carried out in Kerman City, southeastern Iran in 2023. We utilized the GSE119794 dataset from the Gene Expression Omnibus (GEO) to analyze differentially expressed lncRNAs (DE-lncRNAs), miRNAs (DE-miRNAs), and mRNAs (DE-mRNAs). Following the identification of the DE-lncRNAs, DE-mRNAs, and DE-miRNAs, we proceeded to examine differentially expressed epithelialmesenchymal transition (EMT) genes. Subsequently, we utilized the RNAInter database to predict interactions among lncRNAs, miRNAs, and mRNAs. Finally, we employed Cytoscape to visualize and analyze the constructed network.

RESULTS

14 DE-lncRNAs, 14 DE-miRNAs, 545 DE-mRNAs, and 65 DE-EMT from pancreatic cancer and its adjacent tissue RNA-Seq data were identified. 1184 EMT genes from dbEMT were obtained, among which 65 DE-EMT were assigned as EMT genes and correlated with tumor progression. One functional lncRNA () was identified as a key functional lncRNA. The area under the ROC curve (AUC) of and miR-708-5p were 0.79 and 0.86, respectively. Thus, it is reasonable to believe that this prognostic risk model helps predict PC metastasis.

CONCLUSION

is a new lncRNA linked with EMT in PC and contributes to a better knowledge of the regulatory mechanisms related to lncRNAs in PC.

摘要

背景

胰腺癌（PC）是一种恶性程度极高的疾病，不仅起病隐匿、进展迅速，而且治疗效果不佳。最近，越来越多的证据表明非编码RNA（ncRNAs），特别是长链非编码RNA（lncRNAs）和微小RNA（miRNAs）在胰腺癌的发病机制中发挥着重要作用。本研究旨在构建miRNAs、lncRNAs和mRNAs之间的相互作用网络，并在胰腺癌背景下进行相关性分析。

方法

本研究于2023年在伊朗东南部的克尔曼市开展。我们利用基因表达综合数据库（GEO）中的GSE119794数据集来分析差异表达的lncRNAs（DE-lncRNAs）、miRNAs（DE-miRNAs）和mRNAs（DE-mRNAs）。在鉴定出DE-lncRNAs、DE-mRNAs和DE-miRNAs后，我们接着研究差异表达的上皮-间质转化（EMT）基因。随后，我们利用RNAInter数据库预测lncRNAs、miRNAs和mRNAs之间的相互作用。最后，我们使用Cytoscape软件对构建的网络进行可视化和分析。

结果

从胰腺癌及其相邻组织的RNA测序数据中鉴定出14个DE-lncRNAs、14个DE-miRNAs、545个DE-mRNAs和65个DE-EMT。从dbEMT数据库中获得了1184个EMT基因，其中65个DE-EMT被指定为EMT基因并与肿瘤进展相关。鉴定出一个功能性lncRNA（）为关键功能性lncRNA。和miR-708-5p的ROC曲线下面积（AUC）分别为0.79和0.86。因此，有理由认为这个预后风险模型有助于预测胰腺癌转移。