Methyl-CpG-binding domain sequencing reveals a prognostic methylation signature in neuroblastoma
Jazyk angličtina Země Spojené státy americké Médium print
Typ dokumentu časopisecké články, multicentrická studie, Research Support, N.I.H., Extramural, práce podpořená grantem
Grantová podpora
R01 CA127496
NCI NIH HHS - United States
5R01CA127496
NCI NIH HHS - United States
Cancer Research UK - United Kingdom
PubMed
26646589
PubMed Central
PMC4811509
DOI
10.18632/oncotarget.6477
PII: 6477
Knihovny.cz E-zdroje
- Klíčová slova
- DNA methylation, biomarker, neuroblastoma, prognosis,
- MeSH
- biologické markery analýza MeSH
- CpG ostrůvky genetika MeSH
- DNA nádorová genetika MeSH
- kohortové studie MeSH
- kojenec MeSH
- kvantitativní polymerázová řetězová reakce MeSH
- lidé MeSH
- metylace DNA * MeSH
- nádorové buňky kultivované MeSH
- neuroblastom diagnóza genetika MeSH
- prognóza MeSH
- staging nádorů MeSH
- vazebná místa MeSH
- výpočetní biologie MeSH
- Check Tag
- kojenec MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- multicentrická studie MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
- Názvy látek
- biologické markery MeSH
- DNA nádorová MeSH
Accurate assessment of neuroblastoma outcome prediction remains challenging. Therefore, this study aims at establishing novel prognostic tumor DNA methylation biomarkers. In total, 396 low- and high-risk primary tumors were analyzed, of which 87 were profiled using methyl-CpG-binding domain (MBD) sequencing for differential methylation analysis between prognostic patient groups. Subsequently, methylation-specific PCR (MSP) assays were developed for 78 top-ranking differentially methylated regions and tested on two independent cohorts of 132 and 177 samples, respectively. Further, a new statistical framework was used to identify a robust set of MSP assays of which the methylation score (i.e. the percentage of methylated assays) allows accurate outcome prediction. Survival analyses were performed on the individual target level, as well as on the combined multimarker signature. As a result of the differential DNA methylation assessment by MBD sequencing, 58 of the 78 MSP assays were designed in regions previously unexplored in neuroblastoma, and 36 are located in non-promoter or non-coding regions. In total, 5 individual MSP assays (located in CCDC177, NXPH1, lnc-MRPL3-2, lnc-TREX1-1 and one on a region from chromosome 8 with no further annotation) predict event-free survival and 4 additional assays (located in SPRED3, TNFAIP2, NPM2 and CYYR1) also predict overall survival. Furthermore, a robust 58-marker methylation signature predicting overall and event-free survival was established. In conclusion, this study encompasses the largest DNA methylation biomarker study in neuroblastoma so far. We identified and independently validated several novel prognostic biomarkers, as well as a prognostic 58-marker methylation signature.
Bioinformatics Institute Ghent From Nucleotides to Networks De Pintelaan Ghent Belgium
Cancer Research Institute Ghent De Pintelaan Ghent Belgium
Center for Medical Genetics Ghent University De Pintelaan Ghent Belgium
Centre Léon Bérard Laboratoire de Recherche Translationnelle rue Laennec Lyon France
Children's Cancer Institute Lowy Cancer Research Centre UNSW Randwick NSW Australia
DAMBI VIB Inflammation Research Center Technologiepark Ghent Belgium
Department of Pediatric Hematology and Oncology Ghent University Hospital De Pintelaan Ghent Belgium
Department of Pediatric Oncology Institut Curie rue d'Ulm Paris France
Department of Respiratory Medicine Ghent University De Pintelaan Ghent Belgium
National Children's Research Centre Our Lady's Children's Hospital Crumlin Dublin Ireland
Pediatric Hemato oncology CHR Citadelle Liège Belgium
Unité de Génétique Somatique Institut Curie rue d'Ulm Paris France
Zobrazit více v PubMed
Cohn SL, Pearson ADJ, London WB, Monclair T, Ambros PF, Brodeur GM, Faldum A, Hero B, Iehara T, Machin D, Mosseri V, Simon T, Garaventa A, et al. The International Neuroblastoma Risk Group (INRG) classification system: an INRG Task Force report. Journal of Clinical Oncology. 2009;27:289–297. PubMed PMC
Park JR, Bagatell R, London WB, Maris JM, Cohn SL, Mattay KM, Hogarty MD, COG Neuroblastoma Committee Children's Oncology Group's 2013 blueprint for research: neuroblastoma. Pediatric Blood and Cancer. 2013;60:985–993. PubMed
Berthold F, Hero B, Kremens B, Handgretinger R, Henze G, Schilling FH, Schrappe M, Simon T, Spix C. Long-term results and risk profiles of patients in five consecutive trials (1979-1997) with stage 4 neuroblastoma over 1 year of age. Cancer Letters. 2003;197:11–17. PubMed
Pearson ADJ, Pinkerton CR, Lewis IJ, Imeson J, Ellershaw C, Machin D, European Neuroblastoma Study Group; Children's Cancer and Leukaemia Group (CCLG formerly United Kingdom Children's Cancer Study Group) High-dose rapid and standard induction chemotherapy for patients aged over 1 year with stage 4 neuroblastoma: a randomised trial. Lancet Oncology. 2008;9:247–256. PubMed
How Kit A, Nielsen HM, Tost J. DNA methylation based biomarkers: practical considerations and applications. Biochimie. 2012;94:2314–2337. PubMed
Misawa A, Tanaka S, Yagyu S, Tsuchiya K, Iehara T, Sugimoto T, Hosoi H. RASSF1A hypermethylation in pretreatment serum DNA of neuroblastoma patients: a prognostic marker. British Journal of Cancer. 2009;100:399–404. PubMed PMC
Carén H, Djos A, Nethander M, Sjöberg RM, Kogner P, Enström C, Nilsson S, Martinsson T. Identification of epigenetically regulated genes that predict patient outcome in neuroblastoma. BMC Cancer. 2011;11:66. PubMed PMC
Grau E, Martinez F, Orellana C, Canete A, Yáñez Y, Oltra S, Noguera R, Hernandez M, Bermúdez JD, Castel V. Hypermethylation of apoptotic genes as independent prognostic factor in neuroblastoma disease. Molecular Carcinogenesis. 2011;50:153–162. PubMed
Decock A, Ongenaert M, Vandesompele J, Speleman F. Neuroblastoma epigenetics: from candidate gene approaches to genome-wide screenings. Epigenetics. 2011;6:962–970. PubMed
Decock A, Ongenaert M, Hoebeeck J, De Preter K, Van Peer G, Van Criekinge W, Ladenstein R, Schulte JH, Noguera R, Stallings RL, Van Damme A, Laureys G, Vermeulen J, et al. Genome-wide promoter methylation analysis in neuroblastoma identifies prognostic methylation biomarkers. Genome Biology. 2012;13:R95. PubMed PMC
Yáñez Y, Grau E, Rodríguez-Cortez VC, Hervás D, Vidal E, Noguera R, Hernández M, Segura V, Cañete A, Conesa A, Font de Mora J, Castel V. Two independent epigenetic biomarkers predict survival in neuroblastoma. Clinical Epigenetics. 2015;7:16. PubMed PMC
Abe M, Ohira M, Kaneda A, Yagi Y, Yamamoto S, Kitano Y, Takato T, Nakagawara A, Ushijima T. CpG island methylator phenotype is a strong determinant of poor prognosis in neuroblastomas. Cancer Research. 2005;65:828–834. PubMed
Abe M, Westermann F, Nakagawara A, Takato T, Schwab M, Ushijima T. Marked and independent prognostic significance of the CpG island methylator phenotype in neuroblastomas. Cancer Letters. 2007;247:253–258. PubMed
Abe M, Watanabe N, McDonell N, Takato T, Ohira M, Nakagawara A, Ushijima T. Identification of genes targeted by CpG island methylator phenotype in neuroblastomas, and their possible integrative involvement in poor prognosis. Oncology. 2008;74:50–60. PubMed
Banelli B, Brigati C, Di Vinci A, Casciano I, Forlani A, Borzì L, Allemanni G, Romani M. A pyrosequencing assay for the quantitative methylation analysis of the PCDHB gene cluster, the major factor in neuroblastoma methylator phenotype. Laboratory Investigation. 2012;92:458–465. PubMed
Banelli B, Merlo DF, Allemanni G, Forlani A, Romani M. Clinical potentials of methylator phenotype in stage 4 high-risk neuroblastoma: an open challenge. PLoS One. 2013;8:e63253. PubMed PMC
Xiao Y, Hsiao TH, Suresh U, Chen HIH, Wu X, Wolf SE, Chen Y. A novel significance score for gene selection and ranking. Bioinformatics. 2014;30:801–807. PubMed PMC
Huss M. Introduction into the analysis of high-throughput-sequencing based epigenome data. Briefings in bioinformatics. 2010;11:512–523. PubMed
Brodeur GM, Pritchard J, Berthold F, Carlsen NLT, Castel V, Castleberry RP, De Bernardi B, Evans AE, Favrot M, Hedborg F, Kaneko M, Kemshead J, Lampert F, et al. Revisions of the international criteria for neuroblastoma diagnosis, staging, and response to treatment. Journal of Clinical Oncology. 1993;11:1466–1477. PubMed
Molenaar JJ, Koster J, Zwijnenburg DA, van Sluis P, Valentijn LJ, van der Ploeg I, Hamdi M, van Nes J, Westerman BA, van Arkel J, Ebus ME, Haneveld F, Lakeman A, et al. Sequencing of neuroblastoma identifies chromothripsis and defects in neuritogenesis genes. Nature. 2012;483:589–593. PubMed
De Preter K, Mestdagh P, Vermeulen J, Zeka F, Naranjo A, Bray I, Castel V, Chen C, Drozynska E, Eggert A, Hogarty MD, Izycka-Swieszewska E, London WB, et al. miRNA expression profiling enables risk stratification in archived and fresh neuroblastoma tumor samples. Clinical Cancer Research. 2011;17:7684–7692. PubMed PMC
Vermeulen J, De Preter K, Naranjo A, Vercruysse L, Van Roy N, Hellemans J, Swerts K, Bravo S, Scaruffi P, Tonini GP, De Bernardi B, Noguera R, Piqueras M, et al. Predicting outcomes for children with neuroblastoma using a multigene-expression signature: a retrospective SIOPEN/COG/GPOH study. Lancet Oncology. 2009;10:663–671. PubMed PMC
Stirzaker C, Taberlay PC, Statham AL, Clark SJ. Mining cancer methylomes: prospects and challenges. Trends in Genetics. 2014;30:75–84. PubMed
Bock C, Tomazou EM, Brinkman AB, Müller F, Simmer F, Gu H, Jäger N, Gnirke A, Stunnenberg HG, Meissner A. Quantitative comparison of genome-wide DNA methylation mapping technologies. Nature Biotechnology. 2010;28:1106–1114. PubMed PMC
Lou S, Lee HM, Qin H, Li JW, Gao Z, Liu X, Chan LL, Kl Lam V, So WY, Wang Y, Lok S, Wang J, Ma RC, et al. Whole-genome bisulfite sequencing of multiple individuals reveals complementary roles of promoter and gene body methylation in transcriptional regulation. Genome Biology. 2014;15:408. PubMed PMC
Faryna M, Konermann C, Aulmann S, Bermejo JL, Brugger M, Diederichs S, Rom J, Weichenhan D, Claus R, Rehli M, Schirmacher P, Sinn HP, Plass C, et al. Genome-wide methylation screen in low-grade breast cancer identifies novel epigenetically altered genes as potential biomarkers for tumor diagnosis. FASEB Journal. 2012;26:4937–4950. PubMed
Ashktorab H, Daremipouran M, Goel A, Varma S, Leavitt R, Sun X, Brim H. DNA methylome profiling identifies novel methylated genes in African American patients with colorectal neoplasia. Epigenetics. 2014;9:503–512. PubMed PMC
Koga Y, Pelizzola M, Cheng E, Krauthammer M, Sznol M, Ariyan S, Narayan D, Molinaro AM, Halaban R, Weissman SM. Genome-wide screen of promoter methylation identifies novel markers in melanoma. Genome Research. 2009;19:1462–1470. PubMed PMC
Kroeger H, Jelinek J, Estécio MRH, He R, Kondo K, Chung W, Zhang L, Shen L, Kantarjian HM, Bueso-Ramos CE, Issa JP. Aberrant CpG island methylation in acute myeloid leukemia is accentuated at relapse. Blood. 2008;112:1366–1373. PubMed PMC
Vitale L, Frabetti F, Huntsman SA, Canaider S, Casadei R, Lenzi L, Facchin F, Carinci P, Zannotti M, Coppola D, Strippoli P. Sequence, “subtle” alternative splicing and expression of the CYYR1 (cysteine/tyrosine-rich 1) mRNA in human neuroendocrine tumors. BMC Cancer. 2007;7:66. PubMed PMC
Muley PD, McNeill EM, Marzinke MA, Knobel KM, Barr MM, Clagett-Dame M. The atRA-responsive gene neuron navigator 2 functions in neurite outgrowth and axonal elongation. Developmental Neurobiology. 2008;68:1441–1453. PubMed PMC
De Meyer T, Mampaey E, Vlemmix M, Denil S, Trooskens G, Renard JP, De Keulenaer S, Dehan P, Menschaert G, Van Criekinge W. Quality evaluation of methyl binding domain based kits for enrichment DNA-methylation sequencing. PloS One. 2013;8(3):e59068. PubMed PMC
Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nature Methods. 2012;9:357–359. PubMed PMC
Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R, 1000 Genome Project Data Processing Subgroup The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25:2078–2079. PubMed PMC
Lassmann T, Hayashizaki Y, Daub CO. SAMStat: monitoring biases in next generation sequencing data. Bioinformatics. 2011;27:130–131. PubMed PMC
Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, Nusbaum C, Myers RM, Brown M, Li W, Liu XS. Model-based analysis of ChIP-Seq (MACS) Genome Biology. 2008;9:R137. PubMed PMC
Anders S, Huber W. Differential expression analysis for sequence count data. Genome Biology. 2010;11:R106. PubMed PMC
Morgan M, Anders S, Lawrence M, Aboyoun P, Pagès H, Gentleman R. ShortRead: a bioconductor package for input, quality assessment and exploration of high-throughput sequence data. Bioinformatics. 2009;25:2607–2608. PubMed PMC
Lawrence M, Gentleman R, Carey V. rtracklayer: an R package for interfacing with genome browsers. Bioinformatics. 2009;25:1841–1842. PubMed PMC
Liben-Nowell D, Kleinberg J. The link prediction problem for social networks. Journal of the American Society for Information Science and Technology. 2007;58:1019–1031.
London WB, Castleberry RP, Matthay KK, Look AT, Seeger RC, Shimada H, Thorner P, Brodeur GM, Maris JM, Reynolds CP, Cohn SL. Evidence for an age cutoff greater than 365 days for neuroblastoma risk group stratification in the Children's Oncology Group. Journal of Clinical Oncology. 2005;23:6459–6465. PubMed