DNA methylation array analysis identifies profiles of blood-derived DNA methylation associated with bladder cancer

Abstract

Purpose: Epigenetic alterations in tissues targeted for cancer play a causal role in carcinogenesis. Changes in DNA methylation in nontarget tissues, specifically peripheral blood, can also affect risk of malignant disease. We sought to identify specific profiles of DNA methylation in peripheral blood that are associated with bladder cancer risk and therefore serve as an epigenetic marker of disease susceptibility.

Methods: We performed genome-wide DNA methylation profiling on participants involved in a population-based incident case-control study of bladder cancer.

Results: In a training set of 112 cases and 118 controls, we identified a panel of 9 CpG loci whose profile of DNA methylation was significantly associated with bladder cancer in a masked, independent testing series of 111 cases and 119 controls (P < .0001). Membership in three of the most methylated classes was associated with a 5.2-fold increased risk of bladder cancer (95% CI, 2.8 to 9.7), and a model that included the methylation classification, participant age, sex, smoking status, and family history of bladder cancer was a significant predictor of bladder cancer (area under the curve, 0.76; 95% CI, 0.70 to 0.82). CpG loci associated with bladder cancer and aging had neighboring sequences enriched for transcription-factor binding sites related to immune modulation and forkhead family members.

Conclusion: These results indicate that profiles of epigenetic states in blood are associated with risk of bladder cancer and signal the potential utility of epigenetic profiles in peripheral blood as novel markers of susceptibility to this and other malignancies.

Fig 1.

Diagram of the analysis strategy used in defining the methylation profiles in the training set and applying those profiles for classification in the testing set. RPMM, recursively partitioned mixture model.

Fig 2.

DNA methylation profiles defined by a panel of nine loci are significantly associated with bladder cancer. (A) The recursively partitioned mixture model–based classification of methylation of nine loci (columns) in the peripheral blood–derived DNA of the 230 participants (rows) in the testing data set is depicted in the heat map, with the seven classes separated by red lines. The overall mean methylation and CIs (error bars) by class are depicted in the bar graph on the right. (B) The prevalence of cases and controls (y-axis) in each of the predicted classes (x-axis). A permutation-based χ² test suggests that case-control prevalence is significantly different by methylation class (P < .0001).

Fig 3.

Receiver operating characteristic (ROC) curve analysis of methylation profiles. (A) ROC curve based on methylation class only results in a significant area under the curve (AUC) of 0.70 (95% CI, 0.63 to 0.77). (B) ROC curve including methylation classes, patient sex, age, smoking status (never, former, current), and family history of bladder cancer results in a significant AUC of 0.76 (95% CI, 0.70 to 0.82).

Fig 4.

Diagram of the gene-set enrichment analysis on DNA methylation data. The upper panel depicts the transcription factor binding sites (TFBS) within 1 kB of differentially methylated loci associated with aging, bladder cancer, and their overlap grouped by functional role or family. The lower panel depicts the KEGG pathways that are over-represented among the loci with differential methylation associated with aging, bladder cancer, and their overlap, grouped by higher level pathways.