Genetic determinants underlying the variation in response to cancer chemoprevention agents


Session type:


Salwa Almayouf1,David B.H. Barton1,Yue Hu1,Edward J. Louis1,Steven S. Foster1
1University of Leicester



Cancer chemoprevention is the use of natural or chemical agents to prevent or delay the development of cancer. However, there is variation in response to chemopreventive agents amongst individuals because it is a complex trait controlled by multiple genes and environmental factors. Here, we aimed to decipher the genetic factors controlling the variation in response to aspirin, metformin, curcumin and eicosapentaenoic acid using a yeast-based genetic screen before translating findings to humans. This approach was feasible due to the conservation of genes between these two organisms.


A multiparent quantitative trait loci (QTL) mapping approach was applied. A panel of 111 F12 meiotic segregants generated from a cross of four S. cerevisiae wildtype isolates were genotyped by whole genome sequencing. Segregants were phenotyped using an automated pipeline which measured yeast growth in different chemopreventive agent treatments. Subsequently, linkage-based fine QTL mapping strategies were performed to locate regions of the genome correlating to the observed phenotype and the identification of causative genes.


Linkage analysis has mapped hundreds of genetic loci in the yeast genome responsible for the variation in response to the agents tested. Conserved homologues to human genes with DNA damage repair, histone modification and kinase functions were identified. Some hits have been previously supported in the literature such as the effect of aspirin and metformin on MTOR thus validating this screening approach. Novel genes identified revealed different pathways by which these agents may exhibit their anti-cancer properties.


Detection of genetic variants influencing the differences in drug response could help identify individuals at risk or benefit of using chemoprevention agents. Current work includes validating the alleles of causative genes in human cells to assess their biological relevance. This study could aid the development of biomarkers for drug response and validate the repurposing of drugs for prevention of cancer and cancer recurrence.