Derepression of Cancer/testis antigens in cancer is associated with distinct patterns of DNA hypomethylation

Abstract

Background: The Cancer/Testis Antigens (CTAs) are a heterogeneous group of proteins whose expression is typically restricted to the testis. However, they are aberrantly expressed in most cancers that have been examined to date. Broadly speaking, the CTAs can be divided into two groups: the CTX antigens that are encoded by the X-linked genes and the non-X CT antigens that are encoded by the autosomes. Unlike the non-X CTAs, the CTX antigens form clusters of closely related gene families and their expression is frequently associated with advanced disease with poorer prognosis. Regardless however, the mechanism(s) underlying their selective derepression and stage-specific expression in cancer remain poorly understood, although promoter DNA demethylation is believed to be the major driver.

Methods: Here, we report a systematic analysis of DNA methylation profiling data from various tissue types to elucidate the mechanism underlying the derepression of the CTAs in cancer. We analyzed the methylation profiles of 501 samples including sperm, several cancer types, and their corresponding normal somatic tissue types.

Results: We found strong evidence for specific DNA hypomethylation of CTA promoters in the testis and cancer cells but not in their normal somatic counterparts. We also found that hypomethylation was clustered on the genome into domains that coincided with nuclear lamina-associated domains (LADs) and that these regions appeared to be insulated by CTCF sites. Interestingly, we did not observe any significant differences in the hypomethylation pattern between the CTAs without CpG islands and the CTAs with CpG islands in the proximal promoter.

Conclusion: Our results corroborate that widespread DNA hypomethylation appears to be the driver in the derepression of CTA expression in cancer and furthermore, demonstrate that these hypomethylated domains are associated with the nuclear lamina-associated domains (LADS). Taken together, our results suggest that wide-spread methylation changes in cancer are linked to derepression of germ-line-specific genes that is orchestrated by the three dimensional organization of the cancer genome.

Figure 1

Scheme to determine prototypical methylation pattern (PMP) and PMP-sim. PMP is a vector or length 501 corresponding to 501 samples. For each sample, if it is cancer or sperm sample, the corresponding PMP vector element is assigned the minimum methylation value among all 27578 CG loci for that sample, and if the sample is from normal somatic tissue cancer the corresponding PMP vector element is assigned the maximum methylation value among all 27578 CG loci for that sample. For any CG locus, given its methylation pattern across 501 samples, the Pearson correlation between the methylation pattern and the PMP-vector is used to estimate PMP-sim for the CG locus.

Figure 2

Pearson correlation values for the CTX and CTA genes are significantly high. (A-B) Pearson correlation distribution in three groups: all the loci (n = 27578), CTX loci (n = 47), and CTA loci (n = 92). A box and whisker plot comparing the correlation values among the three loci groups is shown in (B). The plot shows the median, the mean (crosses inside the boxes), 25^th percentile (bottom line of the box), 75^th percentile (top line of the box), and minimum and maximum values as whiskers. (C-D) Pearson correlation distribution in three groups: all the loci (n = 27578), CTX loci in CGI regions (n = 4), and CTA loci in CGI regions (n = 36). (E-F) Pearson correlation distribution in three groups: all the loci (n = 27578), CTX loci in non-CGI regions (n = 43), and CTA loci in non-CGI regions (n = 56).

Figure 3

PMP run lengths for CGIs and non-CGIs were higher than the random control. Distribution of runs with length of two or greater are shown for (A) CGIs, (B) randomized CGIs as a control group for (A), (C) non-CGIs, and (D) randomized non-CGIs as a control group for (C).

Figure 4

Delta-PMP values for the CTCF sites in CGIs and non-CGIs were higher than the random control. (A) delta-PMP distribution for the CTCF sites in CGIs (red) and its control (blue). (B) delta-PMP distribution for the CTCF sites in non-CGIs (red) and its control (blue).

Figure 5

CTA and CTX loci intersect with LAD regions more frequently. Out of 92 CTA loci, 47 (51.09%) resided within a LAD (red bar); Out of 19 CTA loci in PMP runs, 12 (64.16%) of them resided within a LAD (blue bar); Out of 47 CTX loci, 32 (68.09%) resided within a LAD (purple bar); Out of 12 CTX loci in PMP runs, 8 (66.67%) of them resided within a LAD (green bar). Out of 1000 loci randomly selected, 173 (17.30%) resided within a LAD (orange bar).