Anthropology and Health Informatics Lab, Department of Bioinformatics, Bharathiar University, Coimbatore, Tamil Nadu, India.
Microrna. 2024;13(1):33-55. doi: 10.2174/0122115366253242231020053221.
To retrieve, and classify PCa miRNAs and identify the functional relationship between miRNAs and their targets through literature collection with computational analysis.
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.
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.
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.
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.
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.
通过文献收集和计算分析,检索和分类前列腺癌 miRNAs,并识别 miRNA 与其靶基因之间的功能关系。
MicroRNAs 在基因调控中发挥作用,可以抑制或激活基因。因此,miRNA 的功能取决于靶基因。这项研究将首次结合计算分析和语料库前列腺癌数据。实际上,我们的研究报告了大量与前列腺癌相关的 miRNAs 及其功能信息。
通过挖掘文献数据,对已知的全前列腺癌 miRNAs 及其靶基因进行鉴定和分类。系统生物学和经过验证的数据挖掘有助于确定前列腺癌治疗的最佳 miRNAs 和其靶基因。
使用 PubMed 数据库收集截至 2021 年 12 月的前列腺癌文献。使用 Pubmed.mineR 软件包提取与 microRNAs 相关的文章,并进行手动分类,根据在前列腺癌中的功能对 microRNAs 进行分类。使用 STRING 数据库构建 PPI。使用 PANTHER 和 ToppGene Suite 软件进行途径分析。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 进行枢纽基因分析。使用 Cytoscape 重建 genemiRNA 网络。
从挖掘的前列腺癌文献中检索和分类了独特的前列腺癌 miRNAs。从 250 篇文章中提取了 605 个独特的 miRNAs,被认为是触发前列腺癌的致癌 miRNA。从 118 篇文章中提取了 120 个独特的 miRNAs,被认为是抑制前列腺癌的肿瘤抑制 miRNA。从 22 篇文章中提取了 24 个独特的 miRNAs,被用于治疗前列腺癌的治疗 miRNA。鉴定了 miRNA 靶基因及其显著途径、功能和枢纽基因。
miR-27a、miR-34b、miR-495、miR-23b、miR-100、miR-218、Let-7a 家族、miR-27a-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 是显著的前列腺癌靶基因。