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Published on: April 25, 2022
Regulatory Network of MicroRNAs, Host Genes, Target Genes and Transcription Factors in Human Esophageal Squamous Cell
Tian-Yan Wang1, Zhi-Wen Xu, Kun-Hao Wang
1College of Software Engineering, Jilin University, Changchun, Jilin, China
Abstract:
Abnormally expressed microRNAs (miRNAs) and genes have been found to play key roles in esophageal squamous cell carcinoma (ESCC), but little is known about the underlying mechanisms. The aim of this paper was to assess inter-relationships and the regulatory mechanisms of ESCC through a network-based approach. We built three regulatory networks: an abnormally expressed network, a related network and a global network. Unlike previous examples, containing information only on genes or miRNAs, the prime focus was on relationships. It is worth noting that abnormally expressed network emerged as a fault map of ESCC. Theoretically, ESCC might be treated and prevented by correcting the included errors. In addition, the predicted transcription factors (TFs) obtained by the P-match method also warrant further study. Our results may further guide gene therapy researchers in the study of ESCC.
Insights
This study reveals how microRNAs (miRNAs) and genes interact in esophageal squamous cell carcinoma (ESCC) using network analysis. Understanding these relationships could lead to new treatments for ESCC.
Area of Science:
- Oncology
- Genetics
- Bioinformatics
Background:
- MicroRNAs (miRNAs) and genes are implicated in esophageal squamous cell carcinoma (ESCC) development.
- The intricate regulatory mechanisms underlying ESCC pathogenesis remain largely unelucidated.
- Existing research often focuses on individual genes or miRNAs, neglecting their complex interrelationships.
Purpose of the Study:
- To investigate the inter-relationships and regulatory mechanisms of ESCC using a network-based approach.
- To identify key molecular players and pathways involved in ESCC.
- To provide a foundation for novel therapeutic strategies targeting ESCC.
Main Methods:
- Construction of three distinct regulatory networks: abnormally expressed, related, and global networks.
- Focus on the relationships between genes and miRNAs, rather than individual components.
- Utilized the P-match method for predicting transcription factors (TFs).
Main Results:
- The abnormally expressed network serves as a "fault map" for ESCC, highlighting critical dysregulations.
- Identified complex inter-relationships between miRNAs and genes in ESCC.
- Predicted transcription factors (TFs) that warrant further investigation for their role in ESCC.
Conclusions:
- The network-based approach provides novel insights into ESCC regulatory mechanisms.
- Correcting identified "errors" in the abnormally expressed network may offer therapeutic and preventive strategies for ESCC.
- Findings can guide gene therapy researchers in developing targeted treatments for ESCC.
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