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Methylation pattern analysis in prostate cancer tissue: identification of biomarkers using an MS-MLPA approach

BACKGROUND: Epigenetic silencing mediated by CpG island methylation is a common feature of many cancers. Characterizing aberrant DNA methylation changes associated with prostate carcinogenesis could potentially identify a tumour-specific methylation pattern, facilitating the early diagnosis of prost...

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Autores principales: Gurioli, Giorgia, Salvi, Samanta, Martignano, Filippo, Foca, Flavia, Gunelli, Roberta, Costantini, Matteo, Cicchetti, Giacomo, De Giorgi, Ugo, Sbarba, Persio Dello, Calistri, Daniele, Casadio, Valentina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5006561/
https://www.ncbi.nlm.nih.gov/pubmed/27576364
http://dx.doi.org/10.1186/s12967-016-1014-6
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author Gurioli, Giorgia
Salvi, Samanta
Martignano, Filippo
Foca, Flavia
Gunelli, Roberta
Costantini, Matteo
Cicchetti, Giacomo
De Giorgi, Ugo
Sbarba, Persio Dello
Calistri, Daniele
Casadio, Valentina
author_facet Gurioli, Giorgia
Salvi, Samanta
Martignano, Filippo
Foca, Flavia
Gunelli, Roberta
Costantini, Matteo
Cicchetti, Giacomo
De Giorgi, Ugo
Sbarba, Persio Dello
Calistri, Daniele
Casadio, Valentina
author_sort Gurioli, Giorgia
collection PubMed
description BACKGROUND: Epigenetic silencing mediated by CpG island methylation is a common feature of many cancers. Characterizing aberrant DNA methylation changes associated with prostate carcinogenesis could potentially identify a tumour-specific methylation pattern, facilitating the early diagnosis of prostate cancer. The objective of the study was to assess the methylation status of 40 tumour suppressor genes in prostate cancer and healthy prostatic tissues. METHODS: We used methylation specific-multiplex ligation probe amplification (MS-MLPA) assay in two independent case series (training and validation set). The training set comprised samples of prostate cancer tissue (n = 40), healthy prostatic tissue adjacent to the tumor (n = 26), and healthy non prostatic tissue (n = 23), for a total of 89 DNA samples; the validation set was composed of 40 prostate cancer tissue samples and their adjacent healthy prostatic tissue, for a total of 80 DNA samples. Methylation specific-polymerase chain reaction (MSP) was used to confirm the results obtained in the validation set. RESULTS: We identified five highly methylated genes in prostate cancer: GSTP1, RARB, RASSF1, SCGB3A1, CCND2 (P < 0.0001), with an area under the ROC curve varying between 0.89 (95 % CI 0.82–0.97) and 0.95 (95 % CI 0.90–1.00). Diagnostic accuracy ranged from 80 % (95 % CI 70–88) to 90 % (95 % CI 81–96). Moreover, a concordance rate ranging from 83 % (95 % CI 72–90) to 89 % (95 % CI 80–95) was observed between MS-MLPA and MSP. CONCLUSIONS: Our preliminary results highlighted that hypermethylation of GSTP1, RARB, RASSF1, SCGB3A1 and CCND2 was highly tumour-specific in prostate cancer tissue. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12967-016-1014-6) contains supplementary material, which is available to authorized users.
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spelling pubmed-50065612016-09-01 Methylation pattern analysis in prostate cancer tissue: identification of biomarkers using an MS-MLPA approach Gurioli, Giorgia Salvi, Samanta Martignano, Filippo Foca, Flavia Gunelli, Roberta Costantini, Matteo Cicchetti, Giacomo De Giorgi, Ugo Sbarba, Persio Dello Calistri, Daniele Casadio, Valentina J Transl Med Research BACKGROUND: Epigenetic silencing mediated by CpG island methylation is a common feature of many cancers. Characterizing aberrant DNA methylation changes associated with prostate carcinogenesis could potentially identify a tumour-specific methylation pattern, facilitating the early diagnosis of prostate cancer. The objective of the study was to assess the methylation status of 40 tumour suppressor genes in prostate cancer and healthy prostatic tissues. METHODS: We used methylation specific-multiplex ligation probe amplification (MS-MLPA) assay in two independent case series (training and validation set). The training set comprised samples of prostate cancer tissue (n = 40), healthy prostatic tissue adjacent to the tumor (n = 26), and healthy non prostatic tissue (n = 23), for a total of 89 DNA samples; the validation set was composed of 40 prostate cancer tissue samples and their adjacent healthy prostatic tissue, for a total of 80 DNA samples. Methylation specific-polymerase chain reaction (MSP) was used to confirm the results obtained in the validation set. RESULTS: We identified five highly methylated genes in prostate cancer: GSTP1, RARB, RASSF1, SCGB3A1, CCND2 (P < 0.0001), with an area under the ROC curve varying between 0.89 (95 % CI 0.82–0.97) and 0.95 (95 % CI 0.90–1.00). Diagnostic accuracy ranged from 80 % (95 % CI 70–88) to 90 % (95 % CI 81–96). Moreover, a concordance rate ranging from 83 % (95 % CI 72–90) to 89 % (95 % CI 80–95) was observed between MS-MLPA and MSP. CONCLUSIONS: Our preliminary results highlighted that hypermethylation of GSTP1, RARB, RASSF1, SCGB3A1 and CCND2 was highly tumour-specific in prostate cancer tissue. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12967-016-1014-6) contains supplementary material, which is available to authorized users. BioMed Central 2016-08-30 /pmc/articles/PMC5006561/ /pubmed/27576364 http://dx.doi.org/10.1186/s12967-016-1014-6 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Gurioli, Giorgia
Salvi, Samanta
Martignano, Filippo
Foca, Flavia
Gunelli, Roberta
Costantini, Matteo
Cicchetti, Giacomo
De Giorgi, Ugo
Sbarba, Persio Dello
Calistri, Daniele
Casadio, Valentina
Methylation pattern analysis in prostate cancer tissue: identification of biomarkers using an MS-MLPA approach
title Methylation pattern analysis in prostate cancer tissue: identification of biomarkers using an MS-MLPA approach
title_full Methylation pattern analysis in prostate cancer tissue: identification of biomarkers using an MS-MLPA approach
title_fullStr Methylation pattern analysis in prostate cancer tissue: identification of biomarkers using an MS-MLPA approach
title_full_unstemmed Methylation pattern analysis in prostate cancer tissue: identification of biomarkers using an MS-MLPA approach
title_short Methylation pattern analysis in prostate cancer tissue: identification of biomarkers using an MS-MLPA approach
title_sort methylation pattern analysis in prostate cancer tissue: identification of biomarkers using an ms-mlpa approach
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5006561/
https://www.ncbi.nlm.nih.gov/pubmed/27576364
http://dx.doi.org/10.1186/s12967-016-1014-6
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