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Updated: Nov 28, 2025
A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
Published on: May 27, 2021
Integrative omics analysis reveals relationships of genes with synthetic lethal interactions through a pan-cancer
Li Guo1, Sunjing Li1, Bowen Qian1
1Department of Bioinformatics, Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
Abstract:
Synthetic lethality is thought to play an important role in anticancer therapies. Herein, to understand the potential distributions and relationships between synthetic lethal interactions between genes, especially for pairs deriving from different sources, we performed an integrative analysis of genes at multiple molecular levels. Based on inter-species phylogenetic conservation of synthetic lethal interactions, gene pairs from yeast and humans were analyzed; a total of 37,588 candidate gene pairs containing 7,816 genes were collected. Of these, 49.74% of genes had 2-10 interactions, 22.93% were involved in hallmarks of cancer, and 21.61% were identified as core essential genes. Many genes were shown to have important biological roles via functional enrichment analysis, and 65 were identified as potentially crucial in the pathophysiology of cancer. Gene pairs with dysregulated expression patterns had higher prognostic values. Further screening based on mutation and expression levels showed that remaining gene pairs were mainly derived from human predicted or validated pairs, while most predicted pairs from yeast were filtered from analysis. Genes with synthetic lethality were further analyzed with their interactive microRNAs (miRNAs) at the isomiR level which have been widely studied as negatively regulatory molecules. The miRNA-mRNA interaction network revealed that many synthetic lethal genes contributed to the cell cycle (seven of 12 genes), cancer pathways (five of 12 genes), oocyte meiosis, the p53 signaling pathway, and hallmarks of cancer. Our study contributes to the understanding of synthetic lethal interactions and promotes the application of genetic interactions in further cancer precision medicine.
Insights
Synthetic lethality, crucial for cancer therapy, involves gene interactions. This study analyzed gene pairs across species, identifying key genes and pathways involved in cancer, paving the way for precision medicine.
Area of Science:
- Genomics
- Cancer Biology
- Bioinformatics
Background:
- Synthetic lethality is a key concept in anticancer drug development.
- Understanding gene interactions is vital for targeted cancer therapies.
Purpose of the Study:
- To analyze synthetic lethal gene interactions across species.
- To identify genes and pathways critical for cancer pathophysiology.
- To explore the role of microRNAs in synthetic lethality.
Main Methods:
- Integrative analysis of genes at multiple molecular levels.
- Inter-species phylogenetic conservation analysis of synthetic lethal interactions.
- Functional enrichment analysis and assessment of mutation/expression levels.
- miRNA-mRNA interaction network analysis.
Main Results:
- Identified 37,588 candidate gene pairs, with many linked to cancer hallmarks and core essential genes.
- Discovered 65 genes potentially crucial in cancer pathophysiology.
- Gene pairs with dysregulated expression showed higher prognostic value.
- miRNA-mRNA network analysis revealed synthetic lethal genes' roles in cell cycle, cancer pathways, and p53 signaling.
Conclusions:
- This study enhances the understanding of synthetic lethal interactions.
- Identified crucial genes and pathways for cancer precision medicine.
- Highlights the potential of miRNA-mRNA interactions in synthetic lethality.
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