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Updated: Jan 6, 2026
Rapid Identification of Chemical Genetic Interactions in Saccharomyces cerevisiae
Published on: April 5, 2015
A Humanized Yeast Phenomic Model of Deoxycytidine Kinase to Predict Genetic Buffering of Nucleoside Analog
Sean M Santos1, Mert Icyuz2, Ilya Pound3
1Department of Genetics, University of Alabama at Birmingham, Birmingham, AL 35294, USA . seansantos18@gmail.com.
Abstract:
Knowledge about synthetic lethality can be applied to enhance the efficacy of anticancer therapies in individual patients harboring genetic alterations in their cancer that specifically render it vulnerable. We investigated the potential for high-resolution phenomic analysis in yeast to predict such genetic vulnerabilities by systematic, comprehensive, and quantitative assessment of drug-gene interaction for gemcitabine and cytarabine, substrates of deoxycytidine kinase that have similar molecular structures yet distinct antitumor efficacy. Human deoxycytidine kinase (dCK) was conditionally expressed in the Saccharomycescerevisiae genomic library of knockout and knockdown (YKO/KD) strains, to globally and quantitatively characterize differential drug-gene interaction for gemcitabine and cytarabine. Pathway enrichment analysis revealed that autophagy, histone modification, chromatin remodeling, and apoptosis-related processes influence gemcitabine specifically, while drug-gene interaction specific to cytarabine was less enriched in gene ontology. Processes having influence over both drugs were DNA repair and integrity checkpoints and vesicle transport and fusion. Non-gene ontology (GO)-enriched genes were also informative. Yeast phenomic and cancer cell line pharmacogenomics data were integrated to identify yeast-human homologs with correlated differential gene expression and drug efficacy, thus providing a unique resource to predict whether differential gene expression observed in cancer genetic profiles are causal in tumor-specific responses to cytotoxic agents.
Insights
Yeast phenomic analysis identified genetic vulnerabilities to anticancer drugs gemcitabine and cytarabine. This approach aids in predicting patient responses to targeted cancer therapies based on genetic profiles.
Area of Science:
- Biochemistry
- Genetics
- Pharmacology
Background:
- Synthetic lethality offers a strategy to enhance anticancer therapies by targeting cancer-specific genetic vulnerabilities.
- Gemcitabine and cytarabine, deoxycytidine kinase substrates, exhibit distinct antitumor efficacies despite structural similarities.
Purpose of the Study:
- To investigate the utility of high-resolution yeast phenomic analysis for predicting genetic vulnerabilities to gemcitabine and cytarabine.
- To quantitatively assess drug-gene interactions for these two anticancer agents.
Main Methods:
- Conditional expression of human deoxycytidine kinase (dCK) in a yeast knockout/knockdown library.
- Systematic, comprehensive, and quantitative assessment of gemcitabine and cytarabine drug-gene interactions.
- Integration of yeast phenomic data with cancer cell line pharmacogenomics data.
Main Results:
- Pathway enrichment analysis revealed distinct gene ontology processes influencing gemcitabine (autophagy, histone modification, chromatin remodeling, apoptosis) versus cytarabine.
- DNA repair, integrity checkpoints, and vesicle transport influenced both drugs.
- Identified yeast-human homologs with correlated gene expression and drug efficacy.
Conclusions:
- Yeast phenomics provides a valuable platform for identifying drug-gene interactions relevant to cancer therapy.
- The study offers a resource for predicting how differential gene expression in cancer impacts response to cytotoxic agents.
- This approach can guide the development of personalized anticancer treatments.
