Affiliation:
1. Anthropology and Health Informatics Lab, Department of Bioinformatics, Bharathiar University, Coimbatore, Tamil Nadu,
India
Abstract
Introduction:
To retrieve, and classify PCa miRNAs and identify the functional relation-ship 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. Pub-med.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 per-formed using MCODE 2.0, and Hub gene analysis was performed using cytoHubba. The gene-miRNA 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 hun-dred 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.
Funder
Bharathiar Cancer Theranostic Research Centre), India
Publisher
Bentham Science Publishers Ltd.