Data mining of nutrigenomics experiments: Identification of a cancer protective gene signature

Regular consumption of certain foods has shown beneficial effects on cardiometabolic health. However, it is not clear by which molecular mechanisms they may exert their beneficial effects. Many genomic experiments available in public databases have generated gene expression data following the treatment of human cells with different food nutrients. Exploration of such data offers great possibilities for gaining insights into the molecular effects of nutrients at cellular level. In this work, we explored the genomic responses triggered by food bioactive compounds with well-known healthy properties. We show that human cell lines treated with different food compounds tend to cluster in a cell type dependent manner based on gene expression, with an influence of the physiological attributes of cells. Finally, we identify a genomic signature of 18 genes implicated in cell cycle, which may characterize a protective effect of certain food compounds against cancer. Our data provides evidence that nutrigenomic studies found in public databases can be used to discover novel signatures of gene expression and identify common mechanism of actions of food bioactive compounds.