Prognostic DNA Methylation Markers for Prostate Cancer

Strand, Siri H.; Ørntoft, Torben F.; Sørensen, Karina Dalsgaard

doi:10.3390/ijms150916544

Cited by 93 publications

(91 citation statements)

References 109 publications

(261 reference statements)

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“…41 Additional emerging candidate markers for prognosis were also published. 42,43 Cross validation of these potential prognostic markers in various cohorts will be important to confirm truly useful methylation markers for clinical practice.…”

Section: Discussionmentioning

confidence: 99%

Methylation profiling identified novel differentially methylated markers includingOPCMLandFLRT2in prostate cancer

Davison

et al. 2016

Epigenetics

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To develop new methods to distinguish indolent from aggressive prostate cancers (PCa), we utilized comprehensive high-throughput array-based relative methylation (CHARM) assay to identify differentially methylated regions (DMRs) throughout the genome, including both CpG island (CGI) and non-CGI regions in PCa patients based on Gleason grade. Initially, 26 samples, including 8 each of low [Gleason score (GS) 6] and high (GS 7) grade PCa samples and 10 matched normal prostate tissues, were analyzed as a discovery cohort. We identified 3,567 DMRs between normal and cancer tissues, and 913 DMRs distinguishing low from high-grade cancers. Most of these DMRs were located at CGI shores. The top 5 candidate DMRs from the low vs. high Gleason comparison, including OPCML, ELAVL2, EXT1, IRX5, and FLRT2, were validated by pyrosequencing using the discovery cohort. OPCML and FLRT2 were further validated in an independent cohort consisting of 20 low-Gleason and 33 high-Gleason tissues. We then compared patients with biochemical recurrence (nD70) vs. those without (nD86) in a third cohort, and they showed no difference in methylation at these DMR loci. When GS 3C4 cases and GS 4C3 cases were compared, OPCML-DMR methylation showed a trend of lower methylation in the recurrence group (nD30) than in the no-recurrence (nD52) group. We conclude that whole-genome methylation profiling with CHARM revealed distinct patterns of differential DNA methylation between normal prostate and PCa tissues, as well as between different risk groups of PCa as defined by Gleason scores. A panel of selected DMRs may serve as novel surrogate biomarkers for Gleason score in PCa.

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Section: Discussionmentioning

confidence: 99%

Methylation profiling identified novel differentially methylated markers includingOPCMLandFLRT2in prostate cancer

Davison

et al. 2016

Epigenetics

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“…Hypermethylation of PITX2 is associated with poor survival in breast cancer, and it is a prognostic marker of biochemical recurrence in prostate cancer. 74,75 Propero homeobox 1 (PROX1) is a homeobox transcription factor and is associated with breast angiosarcoma and kaposiform hemangioendothelioma. 76 PROX1 is a tumor suppressor gene often hypermethylated in hematological malignancies, sporadic breast cancer, and oral cancer.…”

Section: Discussionmentioning

confidence: 99%

Aberrant gene-specific DNA methylation signature analysis in cervical cancer

et al. 2017

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Multicomponent molecular modifications such as DNA methylation may offer sensitive and specific cervical intraepithelial neoplasia and cervical cancer biomarkers. In this study, we tested cervical tissues at various stages of tumor progression for 5-methylcytosine and 5-hydroxymethylcytosine levels and also DNA promoter methylation profile of a panel of genes for its diagnostic potential. In total, 5-methylcytosine, 5-hydroxymethylcytosine, and promoter methylation of 33 genes were evaluated by reversed-phase high-performance liquid chromatography, enzyme-linked immunosorbent assay based technique, and bisulfate-based next generation sequencing. The 5-methylcytosine and 5-hydroxymethylcytosine contents were significantly reduced in squamous cell carcinoma and receiver operating characteristic curve analysis showed a significant difference in (1) 5-methylcytosine between normal and squamous cell carcinoma tissues (area under the curve = 0.946) and (2) 5-hydroxymethylcytosine levels among normal, squamous intraepithelial lesions and squamous cell carcinoma. Analyses of our next generation sequencing results and data from five independent published studies consisting of 191 normal, 10 low-grade squamous intraepithelial lesions, 21 high-grade squamous intraepithelial lesions, and 335 malignant tissues identified a panel of nine genes (ARHGAP6, DAPK1, HAND2, NKX2-2, NNAT, PCDH10, PROX1, PITX2, and RAB6C) which could effectively discriminate among the various groups with sensitivity and specificity of 80%-100% (p < 0.05). Furthermore, 12 gene promoters (ARHGAP6, HAND2, LHX9, HEY2, NKX2-2, PCDH10, PITX2, PROX1, TBX3, IKBKG, RAB6C, and DAPK1) were also methylated in one or more of the cervical cancer cell lines tested. The global and gene-specific methylation of the panel of genes identified in our study may serve as useful biomarkers for the early detection and clinical management of cervical cancer.

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“…Currently, detection of PCa mainly involves testing of serum prostatespecic antigen (PSA) level. [3][4][5] However, recent studies suggested that PSA is not a specic biomarker of PCa and the diagnostic paradigm suffers from low specicity of PSA. There are further concerns regarding possible over-diagnosis of PCa by PSA in patients with limited potential for disease progression.…”

Section: Introductionmentioning

confidence: 99%

Plasma metabolic profiling and novel metabolite biomarkers for diagnosing prostate cancer

Zhao

Qiu

et al. 2017

RSC Adv.

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Prostate cancer (PCa) is the second leading cause of cancer death among men and associated with profound metabolic changes. It is important to discover new biomarkers for the diagnosis of PCa and metabolomics technology has made progress toward identifying metabolic alterations in diseases that may provide clinically useful biomarkers. The purpose of this work was to determine the distinctive metabolic signatures from PCa. Plasma samples from PCa patients and age-matched healthy controls were investigated using high resolution ultrahigh performance liquid chromatography-mass spectrometry (UPLC/MS) and the datasets were analyzed using pattern recognition methods. Metabolic differences among PCa and control subjects were identified based on multivariate statistical analyses. As a result, 19 distinguishable metabolites were detected and 11 metabolic pathways were established. The altered metabolic pathways were associated with synthesis and degradation of ketone bodies, and phenylalanine metabolism, etc. To demonstrate the utility of plasma biomarkers for the diagnosis of PCa, three metabolites comprising sarcosine, acetylglycine and coreximine that contributed to the combined model were selected as candidate biomarkers. Distinctive signature with these metabolites could significantly increase the diagnostic performance of PCa. In this study, metabolomics technology has proved to be a powerful tool for the discovery of new biomarkers for disease and suggest that panels of metabolites may be valuable to translate our findings to clinically useful diagnostic tests.

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Prognostic DNA Methylation Markers for Prostate Cancer

Cited by 93 publications

References 109 publications

Methylation profiling identified novel differentially methylated markers includingOPCMLandFLRT2in prostate cancer

Methylation profiling identified novel differentially methylated markers includingOPCMLandFLRT2in prostate cancer

Aberrant gene-specific DNA methylation signature analysis in cervical cancer

Plasma metabolic profiling and novel metabolite biomarkers for diagnosing prostate cancer

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