Abstract
Epigenetic mechanisms control gene expression in a way that is stably propagated over multiple cell divisions, but which is also flexible enough to respond to environmental influences. This intermediate position between stability and plasticity renders epigenetic information highly useful for monitoring cellular states in the context of personalized medicine. Epigenetic alterations have also been identified as causal events for common diseases such as cancer and autoimmune disorders. The goal of epigenetic biomarker development is to design experimental assays that produce relevant information for diagnosis, prognosis and therapy optimization in routine clinical treatment and drug discovery. Here, I outline a systematic approach to epigenetic biomarker development and highlight key bioinformatic tools that facilitate discovery, optimization and validation of novel biomarkers.
Acknowledgements
The author wishes to thank Thomas Lengauer, Jörn Walter, Thomas Mikeska, Peter Schüffler, Yassen Assenov and the members of the CANCERDIP consortium (http://www.cancerdip.eu/) for helpful discussions.
Financial & competing interests disclosure
This work was partially funded by the European Union through the CANCERDIP project (HEALTH-F2-2007-200620). The author has no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.
No writing assistance was utilized in the production of this manuscript.