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Clinical Trial
. 2018 Apr;12(4):545-560.
doi: 10.1002/1878-0261.12183. Epub 2018 Mar 13.

Biomarker potential of ST6GALNAC3 and ZNF660 promoter hypermethylation in prostate cancer tissue and liquid biopsies

Affiliations
Clinical Trial

Biomarker potential of ST6GALNAC3 and ZNF660 promoter hypermethylation in prostate cancer tissue and liquid biopsies

Christa Haldrup et al. Mol Oncol. 2018 Apr.

Abstract

Current diagnostic and prognostic tools for prostate cancer (PC) are suboptimal, leading to overdiagnosis and overtreatment. Aberrant promoter hypermethylation of specific genes has been suggested as novel candidate biomarkers for PC that may improve diagnosis and prognosis. We here analyzed ST6GALNAC3 and ZNF660 promoter methylation in prostate tissues, and ST6GALNAC3, ZNF660, CCDC181, and HAPLN3 promoter methylation in liquid biopsies. First, using four independent patient sample sets, including a total of 110 nonmalignant (NM) and 705 PC tissue samples, analyzed by methylation-specific qPCR or methylation array, we found that hypermethylation of ST6GALNAC3 and ZNF660 was highly cancer-specific with areas under the curve (AUC) of receiver operating characteristic (ROC) curve analysis of 0.917-0.995 and 0.846-0.903, respectively. Furthermore, ZNF660 hypermethylation was significantly associated with biochemical recurrence in two radical prostatectomy (RP) cohorts of 158 and 392 patients and remained significant also in the subsets of patients with Gleason score ≤7 (univariate Cox regression and log-rank tests, P < 0.05), suggesting that ZNF660 methylation analysis can potentially help to stratify low-/intermediate-grade PCs into indolent vs. more aggressive subtypes. Notably, ZNF660 hypermethylation was also significantly associated with poor overall and PC-specific survival in the RP cohort (n = 158) with long clinical follow-up available. Moreover, as proof of principle, we successfully detected highly PC-specific hypermethylated circulating tumor DNA (ctDNA) for ST6GALNAC3, ZNF660, HAPLN3, and CCDC181 in liquid biopsies (serum) from 27 patients with PC vs. 10 patients with BPH, using droplet digital methylation-specific PCR analysis. Finally, we generated a three-gene (ST6GALNAC3/CCDC181/HAPLN3) ctDNA hypermethylation model, which detected PC with 100% specificity and 67% sensitivity. In conclusion, we here for the first time demonstrate diagnostic biomarker potential of ST6GALNAC3 and ZNF660 methylation, as well as prognostic biomarker potential of ZNF660. Furthermore, we show that hypermethylation of four genes can be detected in ctDNA in liquid biopsies (serum) from patients with PC.

Keywords: ST6GALNAC3; ZNF660; biomarker; epigenetics; liquid biopsy; prostate cancer.

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Figures

Figure 1
Figure 1
Promoter methylation and RNA expression of ST6GALNAC3 and ZNF660 in prostate tissue samples. (A, B) ST6GALNAC3 and ZNF660 qMSP data for samples of adjacent normal (AN), benign prostatic hyperplasia (BPH), prostatic intraepithelial neoplasia (PIN), localized prostate cancer from radical prostatectomies (PC, RP cohort 1), primary tumors from metastatic PC (MPC), and primary tumors from castrate‐resistant PC (CRPC). **< 0.001, *< 0.05 compared to PC samples. Gray lines: median methylation. P‐values from Mann–Whitney U‐tests. (C–J) Receiver operating characteristic (ROC) analysis comparing promoter methylation in nonmalignant and malignant tissue samples assayed by qMSP (C–D) or Illumina 450K DNA methylation array (E–J). 450K probes cg21526205 and cg22598028 for ST6GALNAC3 and ZNF660, respectively, are shown. (C, D) 28 benign (16 AN and 12 BPH) versus 169 RP samples. (E, F) 11 AN versus 19 PC. (G, H) 21 benign (9 N and 12 AN) versus 20 PC. (I, J) 50 AN versus 497 PC. (K, L) mRNA expression in the TCGA cohort, 52 AN and 495 PC. (M, N) Correlation between promoter methylation and mRNA expression. In TCGA samples, 35 AN (gray dots) and 494 PC (black dots), Spearman correlation rho and P‐values are given.
Figure 2
Figure 2
Kaplan–Meier plots. (A, B) ST6GALNAC3 and ZNF660 promoter methylation assayed by qMSP in RP cohort 1 divided into high and low methylation at the median; endpoint: biochemical recurrence after radical prostatectomy. (C, D) ST6GALNAC3 and ZNF660 promoter methylation assayed by 450K array in the TCGA cohort, samples divided into high and low methylation at the median; endpoint: biochemical recurrence after radical prostatectomy. (E, F) ZNF660 promoter methylation in patients with Gleason score ≤7 in RP cohort 1 and the TCGA cohort. (G) ZNF660 promoter methylation, dichotomized at top 5% most methylated; endpoint: overall survival. (H) ZNF660 promoter methylation, dichotomized at top 5% most methylated; endpoint: PC‐specific survival. P‐values from log‐rank tests.
Figure 3
Figure 3
Promoter methylation in cfDNA from serum. (A) Heatmap of promoter methylation detected in cfDNA extracted from serum samples for single genes and combinations of genes. White: no methylation detected; gray: methylation detected; red box: best minimal combination of markers (highest AUC). (B) Copies per mL of hypermethylated ST6GALNAC3,ZNF660,CCDC181, and HAPLN3 in serum samples from 10 patients with BPH and 27 patients with PC analyzed by droplet digital PCR. P‐values for trend of methylation in BPH<pT2 < pT3‐4 are given. (C) ROC curve analysis of the three‐gene panel ST6GALNAC3/CCDC181/HAPLN3 comparing serum from patients with BPH to patients with PC. *< 0.05, test for trend BPH<pT2 < pT3‐4.

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