We aimed to identify a prostate cancer DNA hypermethylation microarray signature (denoted as PHYMA) that differentiates prostate cancer from benign prostate hyperplasia (BPH), high from low-grade and lethal from non-lethal cancers. This is a non-randomized retrospective study in 111 local Asian men (87 prostate cancers and 24 BPH) treated from 1995 to 2009 in our institution. Archival prostate epithelia were laser-capture microdissected and genomic DNA extracted and bisulfite-converted. Samples were profiled using Illumina GoldenGate Methylation microarray, with raw data processed by GenomeStudio. A classification model was generated using support vector machine, consisting of a 55-probe DNA methylation signature of 46 genes. The model was independently validated on an internal testing dataset which yielded cancer detection sensitivity and specificity of 95.3% and 100% respectively, with overall accuracy of 96.4%. Second validation on another independent western cohort yielded 89.8% sensitivity and 66.7% specificity, with overall accuracy of 88.7%. A PHYMA score was developed for each sample based on the state of methylation in the PHYMA signature. Increasing PHYMA score was significantly associated with higher Gleason score and Gleason primary grade. Men with higher PHYMA scores have poorer survival on univariate (p = 0.0038, HR = 3.89) and multivariate analyses when controlled for (i) clinical stage (p = 0.055, HR = 2.57), and (ii) clinical stage and Gleason score (p = 0.043, HR = 2.61). We further performed bisulfite genomic sequencing on 2 relatively unknown genes to demonstrate robustness of the assay results. PHYMA is thus a signature with high sensitivity and specificity for discriminating tumors from BPH, and has a potential role in early detection and in predicting survival.
References
[1]
Howlader N NA, Krapcho M, Garshell J, Neyman N, et al. SEER Cancer Statistics Review, 1975–2010, National Cancer Institute. Bethesda, MD, based on November 2012 SEER data submission, posted to the SEER web site on April 2013, Available: ≤http://seer.cancer.gov/csr/1975_2010/>, Accessed: 2013 December 15.
[2]
Ferlay J, Shin HR, Bray F, Forman D, Mathers C, et al. (2010) Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. Int J Cancer 127: 2893–2917. doi: 10.1002/ijc.25516
[3]
Bailar JC 3rd, Mellinger GT, Gleason DF (1966) Survival rates of patients with prostatic cancer, tumor stage, and differentiation–preliminary report. Cancer Chemother Rep 50: 129–136.
[4]
Albertsen PC, Hanley JA, Fine J (2005) 20-year outcomes following conservative management of clinically localized prostate cancer. JAMA 293: 2095–2101. doi: 10.1001/jama.293.17.2095
[5]
McLean M, Srigley J, Banerjee D, Warde P, Hao Y (1997) Interobserver variation in prostate cancer Gleason scoring: are there implications for the design of clinical trials and treatment strategies? Clin Oncol (R Coll Radiol) 9: 222–225. doi: 10.1016/s0936-6555(97)80005-2
[6]
Potosky AL, Miller BA, Albertsen PC, Kramer BS (1995) The role of increasing detection in the rising incidence of prostate cancer. JAMA 273: 548–552. doi: 10.1001/jama.273.7.548
[7]
Epstein JI, Allsbrook WC Jr, Amin MB, Egevad LL (2005) The 2005 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma. Am J Surg Pathol 29: 1228–1242. doi: 10.1097/01.pas.0000173646.99337.b1
[8]
Mosse CA, Magi-Galluzzi C, Tsuzuki T, Epstein JI (2004) The prognostic significance of tertiary Gleason pattern 5 in radical prostatectomy specimens. Am J Surg Pathol 28: 394–398. doi: 10.1097/00000478-200403000-00014
[9]
Lowrance WT, Scardino PT (2009) Predictive models for newly diagnosed prostate cancer patients. Rev Urol 11: 117–126.
[10]
Bratt O (2006) Watching the face of Janus–active surveillance as a strategy to reduce overtreatment for localised prostate cancer. Eur Urol 50: 410–412. doi: 10.1016/j.eururo.2006.03.066
[11]
Fiorentino M, Capizzi E, Loda M (2010) Blood and tissue biomarkers in prostate cancer: state of the art. Urol Clin North Am 37: 131–141. doi: 10.1016/j.ucl.2009.11.006
[12]
Jones PA, Baylin SB (2007) The epigenomics of cancer. Cell 128: 683–692. doi: 10.1016/j.cell.2007.01.029
[13]
Jones PA, Baylin SB (2002) The fundamental role of epigenetic events in cancer. Nat Rev Genet 3: 415–428.
[14]
Baylin SB, Jones PA (2011) A decade of exploring the cancer epigenome - biological and translational implications. Nat Rev Cancer 11: 726–734. doi: 10.1038/nrc3130
[15]
Baden J, Adams S, Astacio T, Jones J, Markiewicz J, et al. (2011) Predicting prostate biopsy result in men with prostate specific antigen 2.0 to 10.0 ng/ml using an investigational prostate cancer methylation assay. J Urol 186: 2101–2106. doi: 10.1016/j.juro.2011.06.052
[16]
Yu YP, Landsittel D, Jing L, Nelson J, Ren B, et al. (2004) Gene expression alterations in prostate cancer predicting tumor aggression and preceding development of malignancy. J Clin Oncol 22: 2790–2799. doi: 10.1200/jco.2004.05.158
[17]
Lapointe J, Li C, Higgins JP, van de Rijn M, Bair E, et al. (2004) Gene expression profiling identifies clinically relevant subtypes of prostate cancer. Proc Natl Acad Sci U S A 101: 811–816. doi: 10.1073/pnas.0304146101
[18]
Schwartzman J, Mongoue-Tchokote S, Gibbs A, Gao L, Corless CL, et al. (2011) A DNA methylation microarray-based study identifies ERG as a gene commonly methylated in prostate cancer. Epigenetics 6: 1248–1256. doi: 10.4161/epi.6.10.17727
[19]
Kron K, Pethe V, Briollais L, Sadikovic B, Ozcelik H, et al. (2009) Discovery of novel hypermethylated genes in prostate cancer using genomic CpG island microarrays. PLoS ONE 4: e4830. doi: 10.1371/journal.pone.0004830
[20]
Kim YJ, Yoon HY, Kim SK, Kim YW, Kim EJ, et al. (2011) EFEMP1 as a novel DNA methylation marker for prostate cancer: array-based DNA methylation and expression profiling. Clin Cancer Res 17: 4523–4530. doi: 10.1158/1078-0432.ccr-10-2817
[21]
Kobayashi Y, Absher DM, Gulzar ZG, Young SR, McKenney JK, et al. (2011) DNA methylation profiling reveals novel biomarkers and important roles for DNA methyltransferases in prostate cancer. Genome Res 21: 1017–1027. doi: 10.1101/gr.119487.110
[22]
Yu YP, Paranjpe S, Nelson J, Finkelstein S, Ren B, et al. (2005) High throughput screening of methylation status of genes in prostate cancer using an oligonucleotide methylation array. Carcinogenesis 26: 471–479. doi: 10.1093/carcin/bgh310
[23]
Risk MC, Knudsen BS, Coleman I, Dumpit RF, Kristal AR, et al. (2010) Differential gene expression in benign prostate epithelium of men with and without prostate cancer: evidence for a prostate cancer field effect. Clin Cancer Res 16: 5414–5423. doi: 10.1158/1078-0432.ccr-10-0272
[24]
Ang PW, Loh M, Liem N, Lim PL, Grieu F, et al. (2010) Comprehensive profiling of DNA methylation in colorectal cancer reveals subgroups with distinct clinicopathological and molecular features. BMC Cancer 10: 227. doi: 10.1186/1471-2407-10-227
[25]
Bibikova M, Lin Z, Zhou L, Chudin E, Garcia EW, et al. (2006) High-throughput DNA methylation profiling using universal bead arrays. Genome Res 16: 383–393. doi: 10.1101/gr.4410706
[26]
Goh L, Kasabov N (2005) An integrated feature selection and classification method to select minimum number of variables on the case study of gene expression data. J Bioinform Comput Biol 3: 1107–1136. doi: 10.1142/s0219720005001533
Pavlidis P, Wapinski I, Noble WS (2004) Support vector machine classification on the web. Bioinformatics 20: 586–587. doi: 10.1093/bioinformatics/btg461
[29]
Irsoy O, Yildiz OT, Alpaydin E (2012) Design and analysis of classifier learning experiments in bioinformatics: survey and case studies. IEEE/ACM Trans Comput Biol Bioinform 9: 1663–1675. doi: 10.1109/tcbb.2012.117
[30]
Nordlund J, Milani L, Lundmark A, Lonnerholm G, Syvanen AC (2012) DNA methylation analysis of bone marrow cells at diagnosis of acute lymphoblastic leukemia and at remission. PLoS One 7: e34513. doi: 10.1371/journal.pone.0034513
[31]
Hansen KD, Timp W, Bravo HC, Sabunciyan S, Langmead B, et al. (2011) Increased methylation variation in epigenetic domains across cancer types. Nat Genet 43: 768–775. doi: 10.1038/ng.865
[32]
Mazaris E, Tsiotras A (2013) Molecular Pathways in Prostate Cancer. Nephrourol Mon 5: 792–800. doi: 10.5812/numonthly.9430
[33]
Tawadros T, Brown MD, Hart CA, Clarke NW (2012) Ligand-independent activation of EphA2 by arachidonic acid induces metastasis-like behaviour in prostate cancer cells. Br J Cancer 107: 1737–1744.
[34]
Sirma H, Broemel M, Stumm L, Tsourlakis T, Steurer S, et al. (2013) Loss of CDKN1B/p27Kip1 expression is associated with ERG fusion-negative prostate cancer, but is unrelated to patient prognosis. Oncol Lett 6: 1245–1252. doi: 10.3892/ol.2013.1563
[35]
Chen R, Ren S, Meng T, Aguilar J, Sun Y (2013) Impact of Glutathione-S-Transferases (GST) Polymorphisms and Hypermethylation of Relevant Genes on Risk of Prostate Cancer Biochemical Recurrence: A Meta-Analysis. PLoS One 8: e74775. doi: 10.1371/journal.pone.0074775
[36]
Hagglof C, Hammarsten P, Josefsson A, Stattin P, Paulsson J, et al. (2010) Stromal PDGFRbeta expression in prostate tumors and non-malignant prostate tissue predicts prostate cancer survival. PLoS One 5: e10747. doi: 10.1371/journal.pone.0010747
[37]
Jeronimo C, Henrique R (2014) Epigenetic biomarkers in urological tumors: A systematic review. Cancer Lett 342: 264–274. doi: 10.1016/j.canlet.2011.12.026
[38]
Van Neste L, Herman JG, Otto G, Bigley JW, Epstein JI, et al. (2012) The epigenetic promise for prostate cancer diagnosis. Prostate 72: 1248–1261. doi: 10.1002/pros.22459
[39]
Chiam K, Ricciardelli C, Bianco-Miotto T (2014) Epigenetic biomarkers in prostate cancer: Current and future uses. Cancer Lett 342: 248–256. doi: 10.1016/j.canlet.2012.02.011
[40]
Verma M, Patel P, Verma M (2011) Biomarkers in prostate cancer epidemiology. Cancers (Basel) 3: 3773–3798. doi: 10.3390/cancers3043773
[41]
Gupta A, Zhou CQ, Chellaiah MA (2013) Osteopontin and MMP9: Associations with VEGF Expression/Secretion and Angiogenesis in PC3 Prostate Cancer Cells. Cancers (Basel) 5: 617–638. doi: 10.3390/cancers5020617
[42]
Sim HG, Telesca D, Culp SH, Ellis WJ, Lange PH, et al. (2008) Tertiary Gleason pattern 5 in Gleason 7 prostate cancer predicts pathological stage and biochemical recurrence. J Urol 179: 1775–1779. doi: 10.1016/j.juro.2008.01.016
[43]
Zam NA, Tan PH, Sim HG, Lau WK, Yip SK, et al. (2008) Correlation between prostate needle biopsies and radical prostatectomy specimens: can we predict pathological outcome? Pathology 40: 586–591. doi: 10.1080/00313020802320671
[44]
Harkin DP (2006) Genomics and the impact of new technologies on the management of colorectal cancer. Oncologist 11: 988–991. doi: 10.1634/theoncologist.11-9-988
[45]
Albany C, Alva AS, Aparicio AM, Singal R, Yellapragada S, et al. (2012) Epigenetics in prostate cancer. Prostate Cancer 2011: 580318. doi: 10.1155/2011/580318
[46]
Aryee MJ, Liu W, Engelmann JC, Nuhn P, Gurel M, et al. (2013) DNA methylation alterations exhibit intraindividual stability and interindividual heterogeneity in prostate cancer metastases. Sci Transl Med 5: 169ra110. doi: 10.1126/scitranslmed.3005211
[47]
Roupret M, Hupertan V, Yates DR, Catto JW, Rehman I, et al. (2007) Molecular detection of localized prostate cancer using quantitative methylation-specific PCR on urinary cells obtained following prostate massage. Clin Cancer Res 13: 1720–1725. doi: 10.1158/1078-0432.ccr-06-2467
[48]
Vener T, Derecho C, Baden J, Wang H, Rajpurohit Y, et al. (2008) Development of a multiplexed urine assay for prostate cancer diagnosis. Clin Chem 54: 874–882. doi: 10.1373/clinchem.2007.094912
[49]
Ohgami RS, Ma L, Ren L, Weinberg OK, Seetharam M, et al. (2012) DNA methylation analysis of ALOX12 and GSTM1 in acute myeloid leukaemia identifies prognostically significant groups. Br J Haematol 159: 182–190. doi: 10.1111/bjh.12029
[50]
Napieralski R, Ott K, Kremer M, Becker K, Boulesteix AL, et al. (2007) Methylation of tumor-related genes in neoadjuvant-treated gastric cancer: relation to therapy response and clinicopathologic and molecular features. Clin Cancer Res 13: 5095–5102. doi: 10.1158/1078-0432.ccr-07-0241
[51]
Yagi K, Akagi K, Hayashi H, Nagae G, Tsuji S, et al. (2010) Three DNA methylation epigenotypes in human colorectal cancer. Clin Cancer Res 16: 21–33. doi: 10.1158/1078-0432.ccr-09-2006
[52]
Ammerpohl O, Pratschke J, Schafmayer C, Haake A, Faber W, et al. (2012) Distinct DNA methylation patterns in cirrhotic liver and hepatocellular carcinoma. Int J Cancer 130: 1319–1328. doi: 10.1002/ijc.26136
[53]
Oue N, Mitani Y, Motoshita J, Matsumura S, Yoshida K, et al. (2006) Accumulation of DNA methylation is associated with tumor stage in gastric cancer. Cancer 106: 1250–1259. doi: 10.1002/cncr.21754
[54]
Raffoux E, Cras A, Recher C, Boelle PY, de Labarthe A, et al. (2010) Phase 2 clinical trial of 5-azacitidine, valproic acid, and all-trans retinoic acid in patients with high-risk acute myeloid leukemia or myelodysplastic syndrome. Oncotarget 1: 34–42.
[55]
Krishnamoorthy S, Jin R, Cai Y, Maddipati KR, Nie D, et al. (2010) 12-Lipoxygenase and the regulation of hypoxia-inducible factor in prostate cancer cells. Exp Cell Res 316: 1706–1715. doi: 10.1016/j.yexcr.2010.03.005
[56]
Zawada AM, Rogacev KS, Hummel B, Grun OS, Friedrich A, et al. (2012) SuperTAG methylation-specific digital karyotyping reveals uremia-induced epigenetic dysregulation of atherosclerosis-related genes. Circ Cardiovasc Genet 5: 611–620. doi: 10.1161/circgenetics.112.963207
[57]
Andrae J, Gallini R, Betsholtz C (2008) Role of platelet-derived growth factors in physiology and medicine. Genes Dev 22: 1276–1312. doi: 10.1101/gad.1653708
[58]
Ustach CV, Huang W, Conley-LaComb MK, Lin CY, Che M, et al. (2010) A novel signaling axis of matriptase/PDGF-D/ss-PDGFR in human prostate cancer. Cancer Res 70: 9631–9640. doi: 10.1158/0008-5472.can-10-0511
[59]
Gallick GE, Corn PG, Zurita AJ, Lin SH (2012) Small-molecule protein tyrosine kinase inhibitors for the treatment of metastatic prostate cancer. Future Med Chem 4: 107–119. doi: 10.4155/fmc.11.161
[60]
Hewitt KJ, Shamis Y, Knight E, Smith A, Maione A, et al. (2012) PDGFRbeta expression and function in fibroblasts derived from pluripotent cells is linked to DNA demethylation. J Cell Sci 125: 2276–2287. doi: 10.1242/jcs.099192
[61]
Bruna A, Darken RS, Rojo F, Ocana A, Penuelas S, et al. (2007) High TGFbeta-Smad activity confers poor prognosis in glioma patients and promotes cell proliferation depending on the methylation of the PDGF-B gene. Cancer Cell 11: 147–160. doi: 10.1016/j.ccr.2006.11.023
[62]
Lennartsson J, Ronnstrand L (2006) The stem cell factor receptor/c-Kit as a drug target in cancer. Curr Cancer Drug Targets 6: 65–75. doi: 10.2174/156800906775471725
[63]
Di Lorenzo G, Autorino R, D’Armiento FP, Mignogna C, De Laurentiis M, et al. (2004) Expression of proto-oncogene c-kit in high risk prostate cancer. Eur J Surg Oncol 30: 987–992. doi: 10.1016/j.ejso.2004.07.017
[64]
Gao XN, Lin J, Li YH, Gao L, Wang XR, et al. (2012) MicroRNA-193a represses c-kit expression and functions as a methylation-silenced tumor suppressor in acute myeloid leukemia. Oncogene 30: 3416–3428. doi: 10.1038/onc.2011.62
[65]
Yang B, Wu J, Maddodi N, Ma Y, Setaluri V, et al. (2007) Epigenetic control of MAGE gene expression by the KIT tyrosine kinase. J Invest Dermatol 127: 2123–2128. doi: 10.1038/sj.jid.5700836
