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Identification of Candidate MicroRNA-mRNA Subnetwork for Predicting the Osteosarcoma Progression by Bioinformatics Analysis.

Authors :
Lu, Dejie
Huang, Hanji
Zheng, Li
Li, Kanglu
Cui, Xiaofei
Qin, Xiong
Zheng, Mingjun
Huang, Nanchang
Chen, Chaotao
Zhao, Jinmin
Zhu, Bo
Source :
Computational & Mathematical Methods in Medicine. 9/22/2022, p1-13. 13p.
Publication Year :
2022

Abstract

Osteosarcoma (OS) is the pretty common primary cancer of the bone among the malignancies in adolescents. A single molecular component or a limited number of molecules is insufficient as a predictive biomarker of OS progression. Hence, it is necessary to find novel network biomarkers to improve the prediction and therapeutic effect for OS. Here, we identified 230 DE-miRNAs and 821 DE-mRNAs through two miRNA expression-profiling datasets and three mRNA expression-profiling datasets. We found that hsa-miR-494 is closely linked with the survival of OS patients. In addition, we analyzed GO and KEGG enrichment for targets of hsa-miR-494-5p and hsa-miR-494-3p through R programming. And five mRNAs were predicted as common targets of hsa-miR-494-5p and hsa-miR-494-3p. We further revealed that upregulated TRPS1 was strongly correlated with poor outcomes in OS patients through the survival analysis based on the TARGET database. The qRT-PCR study verified that the expression of hsa-miR-494-5p and hsa-miR-494-3p was declined considerably, while TRPS1 was notably raised in OS cells when compared to the osteoblasts. Thus, we generated a new regulatory subnetwork of key miRNAs and target mRNAs using Cytoscape software. These results indicate that the novel miRNA-mRNA subnetwork composed of hsa-miR-494-5p, hsa-miR-494-3p, and TRPS1 might be a characteristic molecule for assessing the prognostic value of OS patients. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1748670X
Database :
Academic Search Index
Journal :
Computational & Mathematical Methods in Medicine
Publication Type :
Academic Journal
Accession number :
159271124
Full Text :
https://doi.org/10.1155/2022/1821233