The combined analysis of DNA methylation profiles in DLBCL and normal B-cell populations provides an opportunity to discriminate de novo
DNA methylation arising during tumorigenesis from DNA methylation occurring in normal B-cells. A subset of de novo
DNA methylation events could be of functional significance in the development and/or progression of disease. However, the identification of functional de novo
DNA methylation will be challenging, even when both tumor and normal progenitor cell DNAs can be obtained from the same individual to help control for age, gender, and/or environmental exposures [Foley et al., 2009
; Fraga et al., 2005
; Woo et al., 2009
In our attempts to identify epigenetic changes of functional significance, we observed that de novo
DNA methylation occurred most frequently in CpG islands proximal to or within genes that are already poorly expressed in normal B-cell populations. This supports a model in which de novo
DNA methylation is most frequently involved in the maintenance, as opposed to the initiation, of gene silencing [Weber and Schubeler, 2007
]. Overall, our data is consistent with similar observations of pervasive epigenetic remodeling in FL, wherein genes that are poorly expressed in normal B-cells were proximal to loci that were methylated in tumors [Killian et al., 2009
]. Analyses in aggressive B-cell non-Hodgkin lymphomas have also demonstrated that genes proximal to or encompassing de novo
methylated loci are expressed at low levels in lymphomas and normal hematopoietic tissues [Martin-Subero et al., 2009
Furthermore, there is increasing evidence that the above observations can be generalized to other cancers. For example, genes proximal to or containing methylated loci in colon tumor samples have been shown to be expressed at low levels in normal colon as well as in colorectal adenocarcinomas [Keshet et al., 2006
]. Functional studies in cultured human colon cancer [Bachman et al., 2003
] and prostate cancer cells [Gal-Yam et al., 2008
] and mouse erythroleukemia (MEL) cells [Feng et al., 2006
] reached a similar conclusion that de novo
DNA methylation locks in rather than initiates gene silencing (de novo
repression). Gel-Yam and colleagues provide compelling evidence of frequent epigenetic switching in PC3 prostate cancer cell cultures by which DNA methylation replaces Polycomb repressive complex (PRC) marks found in normal prostate epithelial cells [Gal-Yam et al., 2008
]. Given the overlap in PRC targets and the de novo
methylation found in our studies and in a different survey of maB-NHLs, we agree with the speculation that epigenetic switching can frequently occur in DLBCL [Martin-Subero et al., 2009
]. However, rigorous functional studies in primary tumor cells are needed to validate these speculations.
Nevertheless, it has been recently reported that the methylation status of CpG island shore sequences, located on the edges of CpG islands, is strongly associated with the transcription of associated genes (within 2-kb) in normal tissues and colon cancer [Irizarry et al., 2009
]. The BeadArray assays used in our study are not optimal for addressing the methylation status of CpG island shore sequences. Thus, large-scale, comprehensive analyses of DNA methylation and gene expression profiles are needed to elucidate the likely complex nature of their relationships. Although this will require further technology development, continued advances in sequencing technologies could make this more feasible in the future.
We note that there are multiple scenarios by which maintaining the silence of an otherwise normal gene (i.e. one not carrying genetic mutations that compromise its activity) would have functional significance in tumorigenesis. For example, the epigenetic silencing of genes whose primary function is to prevent the division or promote the death of cells with genetic instability could have a profound impact in cancer development. In principle, such genes could be poorly expressed in normal cells under non-stressful physiological conditions.
In our attempts to identify epigenetic changes of functional significance, we observed a limited numbers of cases in which de novo
DNA methylation was associated with a chromosomal deletion. For tumor suppressor genes, the association of gene deletions and epigenetic silencing would be consistent with Knudson's two-hit hypothesis of cancer [Knudson, 1971
]. It is possible that some loci showing de novo
DNA methylation are proximal to functionally significant genes that are haploinsufficient or have inactivating point mutations or deletions not detected by array CGH analyses in their second copy.
Even taking into consideration the caveats discussed above, the relationships among de novo
DNA methylation, gene expression, and locus copy number call into question the functional significance of de novo
DNA methylation uncovered in this study and others [Martin-Subero et al., 2009
]. This would be in keeping with genetic studies suggesting that `driver' mutations that are causally involved in cancer development and progression can be significantly less numerous than `passenger' mutations that have little to no functional significance [Greenman et al., 2007
; Sjoblom et al., 2006
]. The discrimination between epigenetic `driver' and `passenger' changes in tumors will require functional analyses. Although challenging, the development of novel technologies to introduce specific epigenetic changes into cancer and normal cells would provide a powerful tool to facilitate such studies.
Regardless of their functional significance, de novo DNA methylation could represent epigenetic biomarkers that are useful for monitoring residual disease levels in body fluids, especially during remission periods. The decreasing costs of sequencing technologies bode well for the development of personalized genetic and epigenetic biomarkers of this type based on data acquired from individual tumors. We believe the combined analysis and application of genetic and epigenetic data will lead to a more sophisticated understanding of the molecular etiology of cancer and the development of more sensitive and specific clinical biomarkers.