Bioinformatics-Assisted Extraction of All PCa miRNAs and their Target Genes.

Akilandeswari Ramu, Jayaprakash Chinnappan
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Abstract

Introduction: To retrieve, and classify PCa miRNAs and identify the functional relationship between miRNAs and their targets through literature collection with computational analysis.

Background: MicroRNAs play a role in gene regulation, which can either repress or activate the gene. Hence, the functions of miRNAs are dependent on the target gene. This study will be the first of its kind to combine computational analysis with corpus PCa data. Effectively, our study reported the huge number of miRNAs associated with PCa along with functional information.

Objective: The identification and classification of previously known full PCa miRNAs and their targets were made possible by mining the literature data. Systems Biology and curated data mining assisted in identifying optimum miRNAs and their target genes for PCa therapy.

Methods: PubMed database was used to collect the PCa literature up to December 2021. Pubmed. mineR package was used to extract the microRNAs associated articles and manual curation was performed to classify the microRNAs based on the function in PCa. PPI was constructed using the STRING database. Pathway analysis was performed using PANTHER and ToppGene Suite Software. Functional analysis was performed using ShinyGO software. Cluster analysis was performed using MCODE 2.0, and Hub gene analysis was performed using cytoHubba. The genemiRNA network was reconstructed using Cytoscape.

Results: Unique PCa miRNAs were retrieved and classified from mined PCa literature. Six hundred and five unique miRNAs from 250 articles were considered as oncomiRs to trigger PCa. One hundred and twenty unique miRNAs from 118 articles were considered Tumor Suppressor miRNAs to suppress the PCa. Twenty-four unique miRNAs from 22 articles were utilized as treatment miRNAs to treat PCa. miRNAs target genes and their significant pathways, functions and hub genes were identified.

Conclusion: miR-27a, miR-34b, miR-495, miR-23b, miR-100, miR-218, Let-7a family, miR-27a- 5p, miR-34c, miR-34a, miR-143/-145, miR-125b, miR-124 and miR-205 with their target genes AKT1, SRC, CTNNB1, HRAS, MYC and TP53 are significant PCa targets.

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生物信息学辅助提取所有 PCa miRNA 及其靶基因
目的:通过文献收集和计算分析,检索 PCa miRNAs,并对其进行分类,确定 miRNAs 与其靶标之间的功能关系:背景:microRNAs 在基因调控中起着抑制或激活基因的作用。因此,miRNA 的功能取决于靶基因。这项研究是首次将计算分析与 PCa 数据库相结合。实际上,我们的研究报告了与 PCa 相关的大量 miRNA 及其功能信息:目的:通过挖掘文献数据,对以前已知的PCa miRNA及其靶标进行了鉴定和分类。系统生物学和数据挖掘有助于确定治疗 PCa 的最佳 miRNA 及其靶基因:方法:使用 PubMed 数据库收集截至 2021 年 12 月的 PCa 文献。方法:使用 Pubmed.mineR 软件包提取与 microRNAs 相关的文章,并根据 microRNAs 在 PCa 中的功能对其进行人工分类。使用 STRING 数据库构建 PPI。使用 PANTHER 和 ToppGene Suite 软件进行通路分析。使用 ShinyGO 软件进行功能分析。使用 MCODE 2.0 进行聚类分析,使用 cytoHubba 进行 Hub 基因分析。使用 Cytoscape 重建基因 miRNA 网络:结果:从挖掘到的 PCa 文献中检索到了独特的 PCa miRNA,并对其进行了分类。250 篇文章中的 65 个独特 miRNA 被认为是诱发 PCa 的 oncomiRs。118篇文章中的120个独特miRNA被认为是抑制PCa的肿瘤抑制miRNA。22篇文章中的24个独特的miRNA被认为是治疗PCa的治疗miRNA。结论:miR-27a、miR-34b、miR-495、miR-23b、miR-100、miR-218、Let-7a 家族、miR27a-5p、miR-34c、miR-34a、miR-143/-145、miR-125b、miR-124 和 miR-205 及其靶基因 AKT1、SRC、CTNNB1、HRAS、MYC 和 TP53 是治疗 PCa 的重要靶点。
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