Computational Approaches for Cancer-Fighting: From Gene Expression to Functional Foods

Simple Summary It is today widely accepted that a healthy diet can be one of the fundamental approaches to prevent the risk of cancer. To this aim, nutrigenomics studies are indeed providing a precious source of information, favoring the search for compounds that could affect gene expression in a favorable way. Here we present a computational study to select candidate compounds that could play a role in cancer prevention and care. Starting from analyses of gene expression, we identified 7 genes that have opposite expression trends in apoptotic treatments when compared with 8 different cancer types. In addition, based on structure similarity with 6 compounds that affect the expression patterns of these genes in a favorable way against 8 cancer types, we selected 23 natural compounds as suitable candidates for further tests as possible novel drugs or for the design of functional food for cancer treatment and prevention. It is today widely accepted that a healthy diet is very useful to prevent the risk for cancer or its deleterious effects. Nutrigenomics studies are therefore taking place with the aim to test the effects of nutrients at molecular level and contribute to the search for anti-cancer treatments. These efforts are expanding the precious source of information necessary for the selection of natural compounds useful for the design of novel drugs or functional foods. Here we present a computational study to select new candidate compounds that could play a role in cancer prevention and care. Starting from a dataset of genes that are co-expressed in programmed cell death experiments, we investigated on nutrigenomics treatments inducing apoptosis, and searched for compounds that determine the same expression pattern. Subsequently, we selected cancer types where the genes showed an opposite expression pattern and we confirmed that the apoptotic/nutrigenomics expression trend had a significant positive survival in cancer-affected patients. Furthermore, we considered the functional interactors of the genes as defined by public protein-protein interaction data, and inferred on their involvement in cancers and/or in programmed cell death. We identified 7 genes and, from available nutrigenomics experiments, 6 compounds effective on their expression. These 6 compounds were exploited to identify, by ligand-based virtual screening, additional molecules with similar structure. We checked for ADME criteria and selected 23 natural compounds representing suitable candidates for further testing their efficacy in apoptosis induction. Due to their presence in natural resources, novel drugs and/or the design of functional foods are conceivable from the presented results.