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Author Spotlight: RNA FISH for Locating lncRNA-SNHG6 in Osteosarcoma Cells
Published on: June 16, 2023
Network analysis of microRNAs and genes in human osteosarcoma
Tianyan Wang1, Zhiwen Xu2, Kunhao Wang3
1College of Software Engineering, Jilin University, Changchun, Jilin 130012, P.R. China ; Key Laboratory of Symbolic Computation and Knowledge Engineering of The Ministry of Education, Jilin University, Changchun, Jilin 130012, P.R. China.
Abstract:
To date, numerous studies have suggested that microRNAs (miRNAs) and genes play key roles in osteosarcoma (OS); however, the majority of these studies have been conducted with a specific focus on either the genes or the miRNAs, which has made the regulatory mechanisms of OS difficult to decipher. The aim of the present study was to systematically investigate the elements [genes, miRNAs and transcription factors (TFs)] associated with the morbidity of OS and to explore the associations among these elements, instead of focusing on one or several elements. The scattered data were collected from existing studies of OS, and three regulatory networks (abnormally expressed, related and global) were constructed to explore OS at a macroscopic level. The abnormally expressed network showed the numerous incorrect data linkages that are present when OS emerges, making it useful as a map of the faults in OS. In theory, the correction of these errors could lead to the prevention and even cure of the disease. Unlike studies in which cancer networks have been formed based purely on gene data, the present study focused on genes and miRNAs, as well as the associations among them, to form the regulatory networks of OS. The constructed regulatory networks were shown to contain numerous self-adaptation associations, which may aid in the analysis of the pathogenesis of OS. By comparing and analyzing the similarities and differences, a number of important pathways were highlighted. A notable finding was the predicted TFs obtained by the P-Match method, which could be used to further study the pathogenesis of OS. In the present study, the mechanism of OS has been systematically analyzed and a theoretical foundation for the mechanism has been provided, which may assist the development of gene therapy targeting OS.
Insights
This study investigates genes, microRNAs (miRNAs), and transcription factors (TFs) in osteosarcoma (OS) by building regulatory networks. Understanding these complex interactions offers a new theoretical foundation for OS mechanisms and potential gene therapies.
Area of Science:
- Oncology
- Molecular Biology
- Bioinformatics
Background:
- Osteosarcoma (OS) pathogenesis is complex, involving microRNAs (miRNAs) and genes.
- Previous studies often focused narrowly on either genes or miRNAs, hindering a comprehensive understanding of OS regulatory mechanisms.
Purpose of the Study:
- To systematically investigate genes, miRNAs, and transcription factors (TFs) associated with osteosarcoma (OS).
- To explore the intricate associations among these elements by constructing regulatory networks.
- To provide a theoretical foundation for understanding OS mechanisms and developing targeted therapies.
Main Methods:
- Collected scattered data from existing osteosarcoma (OS) studies.
- Constructed three regulatory networks: abnormally expressed, related, and global.
- Utilized the P-Match method for predicting transcription factors (TFs).
Main Results:
- The abnormally expressed network highlighted data errors in OS, serving as a map of disease-related faults.
- Constructed regulatory networks integrated genes and miRNAs, revealing self-adaptation associations crucial for OS pathogenesis analysis.
- Identified important pathways and predicted TFs, offering insights into OS mechanisms.
Conclusions:
- This study provides a systematic analysis of osteosarcoma (OS) mechanisms by integrating genes, miRNAs, and TFs.
- The developed regulatory networks offer a macroscopic view of OS, aiding in understanding disease pathogenesis.
- The findings may assist in the development of novel gene therapies targeting osteosarcoma (OS).
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