Giorgia Gurioli et al., Methylation pattern analysis in prostate cancer tissue: identification of biomarkers using an MS-MLPA approach. Journal of Translational Medicine
Giorgia Gurioli1†, Samanta Salvi1†, Filippo Martignano1, Flavia Foca2, Roberta Gunelli3, Matteo Costantini4, Giacomo Cicchetti5, Ugo De Giorgi6, Persio Dello Sbarba7, Daniele Calistri1 and Valentina Casadio1
1Biosciences Laboratory, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS
2Unit of Biostatistics and Clinical Trials, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCC
3Department of Urology, Morgagni Pierantoni Hospital
4Pathology Unit, Morgagni Pierantoni Hospital
5Department of Urology, Bufalini Hospital
6Department of Medical Oncology, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS
7Dipartimento di Scienze Biomediche, Sperimentali e Cliniche, University of Florence
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.
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.
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.
Our preliminary results highlighted that hypermethylation of GSTP1, RARB, RASSF1, SCGB3A1 and CCND2 was highly tumour-specific in prostate cancer tissue.
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