Epigenetic Epidemiology of Cancer

Abstract

Epigenetic changes occur in all types of cancers and include alterations in deoxyribonucleic acid (DNA) methylation, histone modification, or expression changes of non-coding ribonucleic acid (RNA). There is now evidence that epigenetic alterations influence cancer risk and could be developed into useful biomarkers. While it is clear that epigenetic mechanisms can play a key role in mediating environmental influences including dietary folate intake, smoking, other environmental stressors, and age, many of the mechanisms involved remain obscure. There are numerous mechanisms by which genetic and epigenetic factors interact and thus the field of epigenetic epidemiology of cancer faces considerable challenges in tearing apart gene-epigene-environment interactions and in determining how they modulate individual cancer risk. An important question for epigenetic epidemiology of cancer is whether epigenetic changes can be identified in surrogate tissues; e.g., DNA isolated from peripheral lymphocytes, plasma samples, urine, or buccal swabs. The current state of the art of cancer epigenetic epidemiology studies as relating to epigenetic cancer risk factors and markers of diagnostic and prognostic significance is reviewed. In the past, epigenetic work has been carried out in comparative studies of primary human normal/tumor tissue pairs, but recent advances in technologies have made large scale analyses on surrogate tissues within defined cohorts possible. Interindividual variations exist in epigenetic markers, but their origin and relevance needs to be determined. In future studies it will be important to characterize the interaction between environmental, dietary, genetic, and epigenetic factors. Echoing the development in the field of genetics, candidate gene approaches employed thus far will be replaced by genome-wide epigenome analyses in the future. Approaches integrating genetic, epigenetic, and well-documented epidemiological and clinical data are most promising and may improve the currently available risk models for cancer in the future.