LINE-1 methylation status in prostate cancer and non-neoplastic tissue adjacent to tumor in association with mortality

AbstractBackgroundRASSF1A promoter methylation is consistent with clinicopathological data and has good accuracy in distinguishing tumors. However, the diagnostic parameters vary among previous studies. A systematic review was conducted to explore the diagnostic value of RASSF1A promoter methylation in prostate cancer.MethodsA comprehensive search of the literature in the PubMed, Medline, Cochrane Library, Embase and ISI Web of Science databases up to May 21, 2020 was performed. STATA software version 12.0 and Meta-disc version 1.4 were used to analyze the data.ResultsThe pooled sensitivity was 0.64 (95% CI 0.61–0.66), the pooled specificity was 0.80 (95% CI 0.77–0.83), the PLR was 3.82 (95% CI 1.96–7.44), and the NLR was 0.29 (95% CI 0.16–0.52). Furthermore, the pooled DOR of RASSF1A promoter methylation for prostate cancer was 13.08 (95% CI: 6.56–26.08). The area under the summary ROC curve was 0.87 (95% CI: 0.84–0.90). The results of the meta-regression suggested that heterogeneity was mainly derived from publication year. Fagan’s nomogram showed that the predictive accuracy was increased significantly by detecting RASSF1A promoter methylation for diagnosing prostate cancer.ConclusionThis meta-analysis suggests that detection of the RASSF1A promoter methylation status can be used for the diagnosis of PCa. In the future, further analyses and studies of larger sample sizes in large centers are needed to confirm our conclusion.

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Gene set based systematic analysis of prostate cancer and its subtypes

Future Oncology ◽

10.2217/fon-2019-0459 ◽

2020 ◽

Vol 16 (2) ◽

pp. 4381-4393

Author(s):

Senlin Ye ◽

Haohui Wang ◽

Kancheng He ◽

Hongwei Shen ◽

Mou Peng ◽

...

Keyword(s):

Gene Expression ◽

Prostate Cancer ◽

Expression Patterns ◽

Methylation Status ◽

Gene Expression Patterns ◽

Biological Functions ◽

Systematic Analysis ◽

Gene Set ◽

Analysis Strategy ◽

Similarities And Differences

Aim: A gene set based systematic analysis strategy is used to investigate prostate tumors and its subclusters with focuses on similarities and differences of biological functions. Results: Dysregulation of methylation status, as well as RAS/RAF/ERK and PI3K-ATK signaling pathways, were found to be the most dramatic changes during prostate cancer tumorigenesis. Besides, neural and inflammation microenvironment is also significantly divergent between tumor and adjacent tissues. Insights of subclasses within prostate tumor cohorts revealed four different clusters with distinct gene expression patterns. We found that samples are mainly clustered by immune environments and proliferation traits. Conclusion: The findings of this article may help to advance the progress of identifying better diagnosis biomarkers and therapeutic targets.

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Methylation of APC and GSTP1 in Non-Neoplastic Tissue Adjacent to Prostate Tumour and Mortality from Prostate Cancer

PLoS ONE ◽

10.1371/journal.pone.0068162 ◽

2013 ◽

Vol 8 (7) ◽

pp. e68162 ◽

Cited By ~ 26

Author(s):

Lorenzo Richiardi ◽

Valentina Fiano ◽

Chiara Grasso ◽

Daniela Zugna ◽

Luisa Delsedime ◽

...

Keyword(s):

Prostate Cancer ◽

Neoplastic Tissue ◽

Prostate Tumour

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Characterization of DNA methylation of the promoters CTCF and BORIS (CTCFL) in breast and ovarian cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2013.31.15_suppl.e22151 ◽

2013 ◽

Vol 31 (15_suppl) ◽

pp. e22151-e22151 ◽

Cited By ~ 1

Author(s):

Ernesto Soto Reyes Solis ◽

Daniela Morales-Espinosa ◽

David Cantu ◽

Gabriela Alvarado-luna ◽

Dan Green ◽

...

Keyword(s):

Breast Cancer ◽

Ovarian Cancer ◽

Dna Methylation ◽

Methylation Status ◽

Dna Hypomethylation ◽

Rt Pcr ◽

Breast And Ovarian Cancer ◽

Neoplastic Tissue ◽

Tissue Samples ◽

Over Expression

e22151 Background: Genetic and epigenetic alterations may promote the initiation or development of cancer. Global DNA hypomethylation and local hypermethylation have been observed, particularly in cell cycle control-associated genes, such as tumor suppressor genes like CTCF. The dissociation of CTCF is associated with hypermethylation of several promoters; its paralogue gene (BORIS) is normally expressed in testicular tissue during spermatogenesis. BORIS over-expression has been identified in multiple neoplasms such as melanoma, gynecological cancer, glioblastoma and – recently – breast cancer. The aim of this study was to characterize the methylation status of the promoter regions of CTCF and BORIS in samples from breast and ovarian cancer compared to non-neoplastic tissue, and correlate it to its expression. Methods: Tissue samples from breast and ovarian cancer, as well as healthy controls were analyzed by MS-PCR for CTCF and BORIS. BorismRNA expression was also analyzed by RT-PCR. Results: A total of 8 ovarian and 16 breast tumors, as well as 10 tumor-adjacent breast tissue samples were prospectively obtained. In non-neoplastic tissue, BORIS was found to be hypermethylated, while in ovarian tumors a loss of methylation was identified in 75% of the samples. The same phenomenon was observed in 68% of breast cancer samples when compared to non-neoplastic tissue. A correlation between loss of DNA methylation of the promoter and gene over-expression was found by RT-PCR, thus suggesting that methylation is an epigenetic phenomenon associated to the over-expression of the oncogene BORIS. The methylation analysis of CTCF did not show any differences between neoplastic and non-neoplastic tissue, suggesting that epigenetic changes mainly affect BORIS. Conclusions: Loss of methylation of the promoter region of BORIS is associated with the over-expression of the gene. No differences were found in the methylation status between healthy and neoplastic tissue for CTCF.

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Frequent DNA Hypermethylation at the RASSF1A and APC Gene Loci in Prostate Cancer Patients of Pakistani Origin

ISRN Urology ◽

10.1155/2013/627249 ◽

2013 ◽

Vol 2013 ◽

pp. 1-4

Author(s):

Ahmed Yaqinuddin ◽

Sohail A. Qureshi ◽

Shahid Pervez ◽

Mohammed Umair Bashir ◽

Ressam Nazir ◽

...

Keyword(s):

Prostate Cancer ◽

Dna Methylation ◽

Cancer Patients ◽

Methylation Status ◽

Transurethral Resection Of Prostate ◽

Gene Promoters ◽

Dna Hypermethylation ◽

Pakistani Population ◽

Specific Pcr ◽

Pakistani Origin

DNA methylation has emerged as a potentially robust biomarker for prostate cancer (PCa). Since DNA methylomes appear to be disease as well as population specific, we have assessed the DNA methylation status of RASSF1A, APC, and p16 (potential biomarkers of PCa) in Pakistani population. Primary prostate cancer tissues were obtained from 27 formalin-fixed paraffin-embedded blocks (FFPE) of cancer patients who underwent radical prostatectomy and transurethral resection of prostate (TURP) during 2003–2008. As controls, twenty-four benign prostatic FFPE tissues were obtained from patients who underwent TURP for benign prostatic hyperplasia during 2008. DNA was extracted, and methylation-specific PCR was used to assess the methylation status for RASSF1A, APC, and p16 gene promoters. Our results revealed that the RASSF1A promoter was hypermethylated in all the tested cancer samples but was also hypermethylated in 3 out of 24 control tissues. The APC promoter was hypermethylated in 15 out of 27 cancer samples and in none of the control samples. Strikingly, none of the samples showed methylation at the p16 promoter. Our findings suggest that RASSF1A and APC gene promoters are frequently hypermethylated in the Pakistani population and therefore have the potential to develop into universally dependable biomarkers for detecting PCa.

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Increased Sensitivity of Detection of RASSF1A and GSTP1 DNA Fragments in Serum of Prostate Cancer Patients: Optimisation of Diagnostics Using OBBPA-ddPCR

Cancers ◽

10.3390/cancers13174459 ◽

2021 ◽

Vol 13 (17) ◽

pp. 4459

Author(s):

Markus Friedemann ◽

Friederike Horn ◽

Katharina Gutewort ◽

Lars Tautz ◽

Carsten Jandeck ◽

...

Keyword(s):

Prostate Cancer ◽

Dna Methylation ◽

Methylation Status ◽

High Signal ◽

Tumour Suppressor Genes ◽

Analytical Sensitivity ◽

Grey Zone ◽

Dna Fragments ◽

Step Method ◽

Rassf1a Methylation

Identification of aberrant DNA methylation is a promising tool in prostate cancer (PCa) diagnosis and treatment. In this study, we evaluated a two-step method named optimised bias-based preamplification followed by digital PCR (OBBPA-dPCR). The method was used to identify promoter hypermethylation of 2 tumour suppressor genes RASSF1A and GSTP1 in the circulating cell-free DNA (cfDNA) from serum samples of PCa patients (n = 75), benign prostatic hyperplasia (BPH, n = 58), and healthy individuals (controls, n = 155). The PCa cohort was further subdivided into subgroups comprising (I) patients with Gleason Scores (GS) ≤ 7 (n = 55), (II) GS ≥ 8 (n = 10), and (III) patients with metastatic PCa diagnosis (n = 10). We found that RASSF1A methylation levels were significantly increased in all 3 PCa subgroups compared to the controls and BPH cohorts (p < 0.01 for all comparisons). Fractional abundances of methylated GSTP1 DNA fragments were significantly increased in subgroup III of metastatic PCa patients (p < 0.001). RASSF1A methylation analysis was found to be beneficial as a complementary biomarker where further diagnostic validation is most crucial. In combination with free PSA, RASSF1A methylation status helps to identify PCa patients with GS ≥ 8 and grey-zone total PSA values between 2–10 ng/mL. In our study, PCR biases between 80–90% were sufficient to detect minute amounts of tumour DNA with high signal-to-noise ratios as well as high analytical sensitivity and specificity. Both RASSF1A and GSTP1 exhibited strongly increased DNA methylation levels in all metastatic PCa patients. Our data indicates a superior sensitivity of epigenetic biomarker analyses in early detection of PCa metastases that should also help to improve PCa therapy.

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Identification of prostate cancer specific methylation biomarkers from a multi-cancer analysis

BMC Bioinformatics ◽

10.1186/s12859-021-04416-w ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Yiyi Pu ◽

Chao Li ◽

Haining Yuan ◽

Xiaoju Wang

Keyword(s):

Prostate Cancer ◽

Dna Methylation ◽

In Silico ◽

Prostate Cancer Screening ◽

Methylation Status ◽

The Cancer Genome Atlas ◽

Translation Rate ◽

Normal Prostate ◽

Cancer Data ◽

Significant Difference

Abstract Background Detecting prostate cancer at a non-aggressive stage is the main goal of prostate cancer screening. DNA methylation has been widely used as biomarkers for cancer diagnosis and prognosis, however, with low clinical translation rate. By taking advantage of multi-cancer data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), we aimed to identify prostate cancer specific biomarkers which can separate between non-aggressive and aggressive prostate cancer based on DNA methylation patterns. Results We performed a comparison analysis of DNA methylation status between normal prostate tissues and prostate adenocarcinoma (PRAD) samples at different Gleason stages. The candidate biomarkers were selected by excluding the biomarkers existing in multiple cancers (pan-cancer) and requiring significant difference between PRAD and other urinary samples. By least absolute shrinkage and selection operator (LASSO) selection, 8 biomarkers (cg04633600, cg05219445, cg05796128, cg10834205, cg16736826, cg23523811, cg23881697, cg24755931) were identified and in-silico validated by model constructions. First, all 8 biomarkers could separate PRAD at different stages (Gleason 6 vs. Gleason 3 + 4: AUC = 0.63; Gleason 6 vs. Gleason 4 + 3 and 8–10: AUC = 0.87). Second, 5 biomarkers (cg04633600, cg05796128, cg23523811, cg23881697, cg24755931) effectively detected PRAD from normal prostate tissues (AUC ranged from 0.88 to 0.92). Last, 6 biomarkers (cg04633600, cg05219445, cg05796128, cg23523811, cg23881697, cg24755931) completely distinguished PRAD with other urinary samples (AUC = 1). Conclusions Our study identified and in-silico validated a panel of prostate cancer specific DNA methylation biomarkers with diagnosis value.

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