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Updated: Jun 14, 2025
07:23
Dual CRISPR-Interference Strategy for Targeting Synthetic Lethal Interactions Between Non-Coding RNAs in Cancer Cells
Published on: May 30, 2025
208
Non-Coding RNAs Extended Omnigenic Module of Cancers.
Jie Li1, Bingbo Wang1, Xiujuan Ma1
1School of Computer Science and Technology, Xidian University, Xi'an 710119, China.
Entropy (Basel, Switzerland)
|August 29, 2024
Summary
Non-coding RNAs (ncRNAs) significantly boost gene connectivity in cancer networks, revealing the Non-coding RNAs extended omnigenic module (NeOModule). This module offers new insights into cancer pathways and treatment targets.
Area of Science:
- Genomics and Bioinformatics
- Cancer Biology
- Systems Biology
Background:
- Cancer development involves complex interactions between coding and non-coding genes.
- Non-coding RNAs (ncRNAs) play a critical role in cancer, but their network involvement is understudied.
- Systematic investigation of ncRNAs in cancer gene interaction networks is lacking.
Purpose of the Study:
- To construct and analyze a gene interaction network incorporating ncRNAs in cancer.
- To evaluate the topological indicator of connectivity for cancer-affected genes.
- To identify and characterize a novel ncRNA-mediated module in cancer networks.
Main Methods:
- Construction of a comprehensive gene interaction network.
- Application of topological analysis, focusing on gene connectivity.
- Development of a connectivity-based method to identify the Non-coding RNAs extended omnigenic module (NeOModule).
Main Results:
- ncRNAs significantly increase the connectivity of genes within the cancer network.
- ncRNAs facilitate the integration of additional genes into cancer-associated modules.
- The NeOModule, identified via connectivity, topologically promotes cancer pattern formation and is biologically enriched with cancer pathways and therapeutic targets.
Conclusions:
- ncRNAs are crucial mediators in cancer gene networks, enhancing connectivity and module expansion.
- The NeOModule represents a significant cancer-associated network structure.
- Findings provide valuable insights into cancer relationships, pathways, and potential treatment strategies.
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