Review Article | Open Access
Research Progress of Abnormal DNA Methylation in the Development, Diagnosis, and Treatment of Prostate Cancer
Zhen Ren1, Ming Yu1, Yi Xia2
1Department of Ultrasound, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China.
2Department of Neurosurgery, Tangdu Hospital, Fourth Military Medical University, Xi'an 710038, China.
Correspondence: Yi Xia (Department of Neurosurgery, Tangdu Hospital, Fourth Military Medical University, Xinshi Road, Xi'an, Shaanxi Province, P.R. China, 710038; Email: firstname.lastname@example.org) and Ming Yu (Department of Ultrasound, Xijing Hospital, Fourth Military Medical University, Changle West Road, Xi'an, Shaanxi Province, P.R. China, 710000; Email: email@example.com).
Annals of Urologic Oncology 2023, 6(3): 96-103. https://doi.org/10.32948/auo.2023.09.30
Key words DNA methylation, epigenetics, prostate cancer, diagnosis, treatment
Early screening and diagnosis of PCa in clinic mainly rely on PSA detection.
However, the PSA level is affected by various factors, and the specificity and sensitivity are not optimal. DNA methylation is highly specific and stable in PCa, so it has its unique advantages in tumor diagnosis. Yao et al.  selected a methylation site on Y chromosome (cg05163709) as a potential biomarker for PCa diagnosis through cancer tissues and adjacent normal tissues of 66 PCa patients, and its sensitivity and specificity were 94.6% and 78.3% respectively. ROC analysis showed that the diagnostic efficiency of cg05163709 (AUC = 0.915) was significantly higher than that of PSA test (AUC = 0.769). Li et al.  identified 359 hypermethylation sites, 3 435 hypomethylation sites, 483 up-regulated genes and 1 341 down-regulated genes in PCa using a public database, and selected 17 hypermethylation sites (covering 13 genes) that could highly distinguish PCa from normal tissues. The prediction accuracy of PCa diagnosis was 88%-94%, respectively. These markers provided important clues for PCa diagnosis and prognosis assessment. Lan et al.  detected the methylation pattern of DACT-2 in serum of 64 PCa patients, 22 patients with benign prostatic hyperplasia (BPH) and 47 healthy subjects by methylation-specific PCR, and the results showed that DACT-2 was present in PCa patients. The promoter methylation level was significantly higher than that of BPH patients and healthy subjects, and the methylation rate of DACT-2 was 0.745. The sensitivity was 81.8% and the specificity was 75.0%. Meanwhile, the ROC curve results showed that DACT-2 was better than PSA in the diagnosis of PCa and was a potential biomarker for PCa diagnosis.
The combined methylation test of multiple genes is helpful to improve the sensitivity and specificity of PCa diagnosis. Brait et al.  found that the sensitivity and specificity of MCAM hypermethylation for the diagnosis of PCa was 66% and 73%, and when MCAM was combined with ERα and ERβ, the sensitivity was effectively increased to 75%, but the specificity was not significantly reduced. Haldrup et al.  analyzed the methylation of serum samples from 27 patients with PCa and 10 patients with BPH, and finally identified three hypermethylated genes (ST6GALNAC3 / CCDC181 / HAPLN3 genes) for the construction of PCa diagnostic model, with high sensitivity. The sensitivity was 67% and the specificity was 100%. Constancio et al.  found that the accuracy, sensitivity and specificity of the combined detection of FOXA1, GSTP1, HOXD3, RARβ2, RASSF1A, SEPT9 and SOX17 for PCa diagnosis was 72%. These studies indicate that polygene methylation detection is expected to become a new idea for PCa diagnosis. DNA methylation test combined with serum PSA also has a common role in PCa diagnosis. A Mexican cohort study  found that methylation tests for GSTP1 and RASSF1A genes had a positive predictive value of 73% and a negative predictive value of 59.6% for PCa diagnosis. When combined with serum PSA, the positive and negative predictive values increased to 81% and 66%, respectively. Reis et al.  compared serum GADD45 for a methylation levels in 22 PCa patients and 22 control patients, and found that the sensitivity and specificity of GADD45 methylation in serum samples were 38% and 98%. However, as a PCa biomarker combination consisting of PSA, circulating cell free DNA (cfDNA) level and GADD45a methylation was established, although the specificity was slightly decreased (87.5%), the diagnostic sensitivity was significantly improved (94.1%). ROC analysis showed that the combination had good diagnostic efficacy for PCa (AUC = 0.937). Figure 2 shows that cfDNA can be released in the bloodstream from tumor sites in prostate cancer patients.
Taken together, these studies suggest that abnormal DNA methylation may be a potential biomarker for early diagnosis of PCa. At the same time, detection of methylation sites based on body fluids or tissues has the characteristics of non-invasive, economical and convenient, which sets a new direction of cancer diagnosis in the future. However, whether DNA methylation is consistent in blood and tumor tissues needs further research.
Application of DNA methylation in PCa prognostic assessment
DNA methylation is not only involved in the initiation and development of PCa, but also closely related to poor prognosis of PCa. It can be used as an important marker for the assessment of PCa prognosis. In a prospective study, Wang et al.  found that the methylation pattern of serum cadherin-13 (CDH13) gene not only significantly correlated with Gleason score, tumor stage and PSA level, but also strongly correlated with survival outcomes and relative mortality risk (HR = 6.132, 95%CI: 3.160-12.187). Gao et al.  found that the promoter methylation level of CRMP4 gene could be used as a factor.
The sensitivity and specificity of this method was more than 90% and served as independent predictors of prognosis in PCa patients. The sensitivity of this method was significantly better than that of MRI in diagnosing lymph node metastasis of PCa (P < 0.001). Pellacani et al.  utilized a detection method based on 17 methylation markers for stratification of PCa prognosis based on whole-genome DNA methylation analysis in PCa tissues and normal tissues, and the diagnostic accuracy rate of this method was as high as 92%. Zhang et al.  divided PCa patients into hypermethylated and hypomethylated types based on DNA methylation patterns at CpG sites. The two subtypes showed significant differences in the epigenome, genome, transcriptome, disease state, immune cell infiltration and function, among which 8 were associated with high-risk subtypes. The PCa prognostic evaluation model constructed by AURKA, DLGAP5, FOXD1, KIF4A, MELK, MYBL2, SPAG5 and TPX2 showed that a higher risk score was associated with poor prognosis in PCa (P < 0.05). The validity of the model was 66%-84% in both internal and external validation sets. In conclusion, high specificitysensitivity and diagnostic accuracy of DNA methylation detection in PCa is applicable for prognosis assessment. In addition, a large number of studies have found that the level of DNA methylation was closely related to the biochemical recurrence of PCa. Goltz et al.  found that CXCL12 methylation significantly correlated with Gleason grade and biochemical relape-free survival after radical prostatectomy, and could be used as an active indicator of postoperative biochemical relapse in PCa patients.
Norgaard et al.  found that MEIS2 gene was significantly hypermethylated in PCa, and in 3 independent radical anterior adenectomy cohorts (700 patients in total), The expression level of MEIS2 significantly correlated with postoperative biochemical recurrence (P.0084, 0.001 and 0.01,). Holmes et al.  found that promoter methylation of PITX3 could effectively predict biochemical recurrence of PCa (training set: HR = 1.83, 95%CI: 1.07 ~ 3.11, P = 0.027; Validation set: HR = 2.56, 95%CI: 1.44 ~ 4.54, P = 0.001), and the combination of PITX2 detection could also perform risk stratification in PCa patients to better assess the risk of biochemical recurrence. In conclusion, detection of methylation markers can predict the risk of biochemical recurrence in PCa patients after surgery, which is of great significance for the prognosis and PCa monitoring.
At present, there are few clinical trials on DNMTi for PCa, and most of them are phase I and II clinical trials. Sonpavde et al.  recruited 36 patients with castration-resistant Pca for the phase II trial of azacytidine combined with androgen blocking agent, and results showed that the PSA doubling time of 19 patients was greater than 3 months, and the overall median PSA doubling time of patients was significantly longer than baseline (P < 0. 01), which is related to the reduction of DNALINE-1 methylation in plasma by azacitidine. A small Phase II clinical trial  involving 14 mCRPC patients using three intravenous doses of decitabine 75 mg/m2 every 8 hours, repeated every 5 to 8 weeks, showed that the patients were well tolerated, but only 2 patients had stable disease and disease progression takes longer than 10 weeks. Another phase I/ II study  used azacytidine plus docetaxel plus prednisone to treat mCRPC patients, with 15 and 7 patients enrolled in phase I and II trials, ultimately observed a complete response in 1 patient and a partial response in 2 patients out of 10 evaluable patients. There were five patients with stable disease. These clinical trials indicate that the safety and clinical efficacy of DNMTi need to be further studied and improved, and that targeted therapy for abnormal DNA methylation sites should be developed to achieve better results of PCa treatment.
All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study. Approval from institutional ethical committee was taken.
Availability of data and materials
All data generated or analysed during this study are included in this publication.
ZR: Conception, design of study and manuscript preparation; MY: Data collection and analysis; YX: Approval for the final version of the manuscript and funding supports.
The authors have no competing interest.
This article is funded by Shaanxi Province Project (2018JQ8075).
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