Cancer Biology and Nutrigenomics

1. Current cancer models comprise those that are inherited through the germline and represent only ~5% of total cases of human cancers. These tumors originate because of mutational events. The remaining ~95% originate as sporadic events and evolve as a result of exposure to the environment, which includes exposure to both environmental contaminants and dietary agents. 2. The multistage model of carcinogenesis identifies various phases, initiation, promotion, and progression, which determine the evolution of normal somatic cells to heterogeneous populations with cancer potential. This process appears to be influenced by tissue microenvironment and organization. Significant opportunities in nutrition and cancer prevention exist in the early stages of initiation and promotion prior to clonal expansion of heterogeneous populations. Targeting initiators, cocarcinogens, and promoters may provide the best opportunity in cancer prevention since the majority of advanced solid tumors are resistant to therapy. 3. Nutrigenomics represents a strategy that can be applied to the study and prevention of many diseases including cancer. It has been defined as a pyramidal approach that encompasses the study of molecular relationships between nutrients and genes (nutrigenetics), how these interactions influence changes in the profile of transcripts (transcriptomics), proteins (proteomics), and metabolites (metabolomics). DNA methylation and histone modifications are epigenetic events that mediate heritable changes in gene expression and chromatin organization in the absence of changes in the DNA sequence. The age-increased susceptibility to cancer may derive from accumulation of epigenetic changes and represents a potential target for therapies with bioactive compounds. 4. Factors that mediate the response to dietary factors include nuclear receptors and transcription factors, which function as sensors to dietary components and determine changes in the profile of transcripts. 5. Integration of high-throughput proteomic and metabolomic approaches with computational techniques is necessary to understand the complexity of the biological response to specific bioactive compounds or associations of nutrients and identify key molecular targets in cancer prevention and treatment.