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Published on: May 27, 2021
SL-Miner: a web server for mining evidence and prioritization of cancer-specific synthetic lethality
Xin Liu1, Jieni Hu2, Jie Zheng1,3
1School of Information Science and Technology, ShanghaiTech University, Shanghai 201210, China.
Summary:
Synthetic lethality (SL) refers to a type of genetic interaction in which the simultaneous inactivation of two genes leads to cell death, while the inactivation of a single gene does not affect cell viability. It significantly expands the range of potential therapeutic targets for anti-cancer treatments. SL interactions are primarily identified through experimental screening and computational prediction. Although various computational methods have been proposed, they tend to ignore providing evidence to support their predictions of SL. Besides, they are rarely user-friendly for biologists who likely have limited programming skills. Moreover, the genetic context specificity of SL interactions is often not taken into consideration. Here, we introduce a web server called SL-Miner, which is designed to mine the evidence of SL relationships between a primary gene and a few candidate SL partner genes in a specific type of cancer, and to prioritize these candidate genes by integrating various types of evidence. For intuitive data visualization, SL-Miner provides a range of charts (e.g. volcano plot and box plot) to help users get insights from the data.
Availability And Implementation:
SL-Miner is available at https://slminer.sist.shanghaitech.edu.cn.
Insights
Synthetic lethality (SL) interactions offer new cancer therapy targets. SL-Miner is a user-friendly web server that mines and prioritizes SL gene partners with supporting evidence for specific cancers.
Area of Science:
- Genomics
- Computational Biology
- Cancer Therapeutics
Background:
- Synthetic lethality (SL) is a genetic interaction where simultaneous gene inactivation causes cell death, expanding anti-cancer treatment targets.
- Current computational methods for identifying SL interactions often lack supporting evidence, user-friendliness for biologists, and consideration of genetic context specificity.
Purpose of the Study:
- To introduce SL-Miner, a web server for mining and prioritizing SL gene-cancer relationships.
- To provide evidence-based predictions and intuitive data visualization for SL interactions.
Main Methods:
- Developed a web server (SL-Miner) to mine SL relationships.
- Integrated various evidence types for prioritizing candidate SL partner genes.
- Implemented intuitive data visualizations, including volcano and box plots.
Main Results:
- SL-Miner effectively mines evidence for SL relationships.
- The server prioritizes candidate SL partner genes within specific cancer contexts.
- Provides user-friendly data visualization for biological insights.
Conclusions:
- SL-Miner enhances the identification of potential therapeutic targets by providing evidence-based SL predictions.
- The tool addresses limitations of existing methods by being user-friendly and context-specific.
- Facilitates deeper understanding of SL interactions in cancer through integrated data visualization.
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