Related Experiment Video
Updated: Apr 1, 2026
A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
Published on: May 27, 2021
Inferring synthetic lethal interactions from mutual exclusivity of genetic events in cancer
Sriganesh Srihari1, Jitin Singla2, Limsoon Wong3
1Institute for Molecular Bioscience, The University of Queensland, St. Lucia, Queensland, 4072, Australia.
Background:
Synthetic lethality (SL) refers to the genetic interaction between two or more genes where only their co-alteration (e.g. by mutations, amplifications or deletions) results in cell death. In recent years, SL has emerged as an attractive therapeutic strategy against cancer: by targeting the SL partners of altered genes in cancer cells, these cells can be selectively killed while sparing the normal cells. Consequently, a number of studies have attempted prediction of SL interactions in human, a majority by extrapolating SL interactions inferred through large-scale screens in model organisms. However, these predicted SL interactions either do not hold in human cells or do not include genes that are (frequently) altered in human cancers, and are therefore not attractive in the context of cancer therapy.
Results:
Here, we develop a computational approach to infer SL interactions directly from frequently altered genes in human cancers. It is based on the observation that pairs of genes that are altered in a (significantly) mutually exclusive manner in cancers are likely to constitute lethal combinations. Using genomic copy-number and gene-expression data from four cancers, breast, prostate, ovarian and uterine (total 3980 samples) from The Cancer Genome Atlas, we identify 718 genes that are frequently amplified or upregulated, and are likely to be synthetic lethal with six key DNA-damage response (DDR) genes in these cancers. By comparing with published data on gene essentiality (~16000 genes) from ten DDR-deficient cancer cell lines, we show that our identified genes are enriched among the top quartile of essential genes in these cell lines, implying that our inferred genes are highly likely to be (synthetic) lethal upon knockdown in these cell lines. Among the inferred targets are tousled-like kinase 2 (TLK2) and the deubiquitinating enzyme ubiquitin-specific-processing protease 7 (USP7) whose overexpression correlates with poor survival in cancers.
Conclusion:
Mutual exclusivity between frequently occurring genetic events identifies synthetic lethal combinations in cancers. These identified genes are essential in cell lines, and are potential candidates for targeted cancer therapy. Availability: http://bioinformatics.org.au/tools-data/underMutExSL
Insights
Synthetic lethality (SL) identifies gene pairs lethal when mutated together. This study uses mutual exclusivity of gene alterations in human cancers to predict novel SL interactions, offering new therapeutic targets for cancer treatment.
Area of Science:
- Genomics
- Computational Biology
- Cancer Therapeutics
Background:
- Synthetic lethality (SL) describes genetic interactions where co-altering genes cause cell death.
- SL is a promising cancer therapy strategy, targeting cancer-specific gene alterations.
- Existing methods often fail to identify human-relevant SL interactions or those involving frequently altered cancer genes.
Purpose of the Study:
- To develop a computational method for predicting SL interactions directly from frequently altered genes in human cancers.
- To identify potential SL partners for key DNA-damage response (DDR) genes.
- To find novel therapeutic targets for cancer treatment.
Main Methods:
- Utilized genomic copy-number and gene-expression data from The Cancer Genome Atlas (TCGA) for four cancer types.
- Applied a computational approach based on the mutual exclusivity of gene alterations.
- Validated identified genes for essentiality in DDR-deficient cancer cell lines.
Main Results:
- Identified 718 genes likely to be synthetic lethal with six key DNA-damage response (DDR) genes in human cancers.
- Found that these identified genes are enriched among essential genes in DDR-deficient cancer cell lines.
- Highlighted tousled-like kinase 2 (TLK2) and ubiquitin-specific-processing protease 7 (USP7) as potential therapeutic targets.
Conclusions:
- Mutual exclusivity of genetic events effectively identifies synthetic lethal combinations in cancer.
- The identified genes are essential in cancer cell lines and represent promising candidates for targeted cancer therapy.
- A computational tool and dataset are available for further research.
Related Concept Videos
01:05Cancer-Critical Genes II: Tumor Suppressor Genes
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...
01:05Cancer-Critical Genes II: Tumor Suppressor Genes
01:12Loss of Tumor Suppressor Gene Functions
When the tumor suppressor genes develop mutations or are lost, cells start growing out of control, leading to cancer. However, a single functional copy of the tumor suppressor gene is enough for the cells to maintain their normal functions and cell...
01:12Loss of Tumor Suppressor Gene Functions
02:41Lethal Alleles
Lucien Cuénot discovered lethal alleles in 1905 while studying the inheritance of coat color in mice. The agouti gene is responsible for the color of the coat in mice. This gene codes for an agouti-signaling protein, which is responsible for melanin distribution in mammals. The wild-type allele gives rise to gray-brown coat color in mice, while the mutant allele gives rise to yellow coat color. In addition to coat color, the agouti gene is associated with the yellow...
02:50Combination Therapies and Personalized Medicine
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...