{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T05:59:26Z","timestamp":1770357566225,"version":"3.49.0"},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T00:00:00Z","timestamp":1705881600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T00:00:00Z","timestamp":1705881600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Clin Epigenet"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Changes in DNA methylation are common events in the pathogenesis of acute myeloid leukemia (AML) and have been repeatedly reported as associated with prognosis. However, studies integrating these numerous and potentially prognostically relevant DNA methylation changes are lacking. Therefore, we aimed for an overall evaluation of these epigenetic aberrations to provide a comprehensive NGS-based approach of DNA methylation assessment for AML prognostication.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>We designed a sequencing panel targeting 239 regions (approx. 573\u00a0kb of total size) described in the literature as having a prognostic impact or being associated with AML pathogenesis. Diagnostic whole-blood DNA samples of adult AML patients divided into a training (<jats:italic>n<\/jats:italic>\u2009=\u2009128) and a testing cohort (<jats:italic>n<\/jats:italic>\u2009=\u200950) were examined. The libraries were prepared using SeqCap Epi Enrichments System (Roche) and sequenced on MiSeq instrument (Illumina). Altogether, 1935 CpGs affecting the survival (<jats:italic>p<\/jats:italic>\u2009&lt;\u20090.05) were revealed in the training cohort. A summarizing value MethScore was then calculated from these significant CpGs. Patients with lower MethScore had markedly longer overall survival (OS) and event-free survival (EFS) than those with higher MethScore (<jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001). The predictive ability of MethScore was verified on the independent testing cohort for OS (<jats:italic>p<\/jats:italic>\u2009=\u20090.01). Moreover, the proof-of-principle validation was performed using the TCGA dataset.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>We showed that comprehensive NGS-based approach of DNA methylation assessment revealed a robust epigenetic signature relevant to AML outcome. We called this signature MethScore and showed it might serve as a strong prognostic marker able to refine survival probability of AML patients.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s13148-024-01625-x","type":"journal-article","created":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T09:02:23Z","timestamp":1705914143000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["MethScore as a new comprehensive DNA methylation-based value refining the prognosis in acute myeloid leukemia"],"prefix":"10.1186","volume":"16","author":[{"given":"\u0160\u00e1rka","family":"\u0160est\u00e1kov\u00e1","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cyril","family":"\u0160\u00e1lek","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"D\u00e1vid","family":"Kundr\u00e1t","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ela","family":"Cerovsk\u00e1","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jan","family":"Vydra","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ivana","family":"Je\u017e\u00ed\u0161kov\u00e1","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adam","family":"Folta","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ji\u0159\u00ed","family":"Mayer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Petr","family":"Cetkovsk\u00fd","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hana","family":"Reme\u0161ov\u00e1","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,1,22]]},"reference":[{"issue":"1","key":"1625_CR1","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1111\/ejh.13172","volume":"102","author":"S Kayser","year":"2019","unstructured":"Kayser S, Levis MJ. Clinical implications of molecular markers in acute myeloid leukemia. Eur J Haematol. 2019;102(1):20\u201335.","journal-title":"Eur J Haematol"},{"issue":"10","key":"1625_CR2","doi-asserted-by":"publisher","first-page":"1267","DOI":"10.1002\/ajh.25214","volume":"93","author":"EH Estey","year":"2018","unstructured":"Estey EH. Acute myeloid leukemia: 2019 update on risk-stratification and management. Am J Hematol. 2018;93(10):1267\u201391.","journal-title":"Am J Hematol"},{"issue":"1","key":"1625_CR3","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1038\/s41392-019-0090-5","volume":"5","author":"H Jiang","year":"2020","unstructured":"Jiang H, Ou Z, He Y, Yu M, Wu S, Li G, et al. DNA methylation markers in the diagnosis and prognosis of common leukemias. Signal Transduct Target Ther. 2020;5(1):3.","journal-title":"Signal Transduct Target Ther"},{"issue":"28","key":"1625_CR4","doi-asserted-by":"publisher","first-page":"7414","DOI":"10.1073\/pnas.1703577114","volume":"114","author":"X Hao","year":"2017","unstructured":"Hao X, Luo H, Krawczyk M, Wei W, Wang W, Wang J, et al. DNA methylation markers for diagnosis and prognosis of common cancers. Proc Natl Acad Sci USA. 2017;114(28):7414\u20139.","journal-title":"Proc Natl Acad Sci USA"},{"key":"1625_CR5","doi-asserted-by":"publisher","DOI":"10.3390\/ijms20184576","author":"X Yang","year":"2019","unstructured":"Yang X, Wong MPM, Ng RK. Aberrant DNA methylation in acute myeloid leukemia and its clinical implications. Int J Mol Sci. 2019. https:\/\/doi.org\/10.3390\/ijms20184576.","journal-title":"Int J Mol Sci"},{"issue":"7","key":"1625_CR6","doi-asserted-by":"publisher","first-page":"792","DOI":"10.1038\/nm.4125","volume":"22","author":"S Li","year":"2016","unstructured":"Li S, Garrett-Bakelman FE, Chung SS, Sanders MA, Hricik T, Rapaport F, et al. Distinct evolution and dynamics of epigenetic and genetic heterogeneity in acute myeloid leukemia. Nat Med. 2016;22(7):792\u20139.","journal-title":"Nat Med"},{"issue":"1","key":"1625_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13148-022-01242-6","volume":"14","author":"S Sestakova","year":"2022","unstructured":"Sestakova S, Cerovska E, Salek C, Kundrat D, Jeziskova I, Folta A, et al. A validation study of potential prognostic DNA methylation biomarkers in patients with acute myeloid leukemia using a custom DNA methylation sequencing panel. Clin Epigen. 2022;14(1):1.","journal-title":"Clin Epigen"},{"key":"1625_CR8","doi-asserted-by":"publisher","first-page":"2059","DOI":"10.1056\/NEJMoa1301689","volume":"368","author":"TJ Ley","year":"2013","unstructured":"Cancer Genome Atlas Research Network, Ley TJ, Miller C, Ding L, Raphael BJ, Mungall AJ, et al. Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. N Engl J Med. 2013;368:2059\u201374.","journal-title":"N Engl J Med"},{"issue":"6","key":"1625_CR9","doi-asserted-by":"publisher","first-page":"1227","DOI":"10.1038\/leu.2013.362","volume":"28","author":"E Jost","year":"2014","unstructured":"Jost E, Lin Q, Weidner CI, Wilop S, Hoffmann M, Walenda T, et al. Epimutations mimic genomic mutations of DNMT3A in acute myeloid leukemia. Leukemia. 2014;28(6):1227\u201334.","journal-title":"Leukemia"},{"issue":"9","key":"1625_CR10","doi-asserted-by":"publisher","first-page":"1128","DOI":"10.1016\/j.leukres.2012.05.012","volume":"36","author":"H Hajkova","year":"2012","unstructured":"Hajkova H, Markova J, Haskovec C, Sarova I, Fuchs O, Kostecka A, et al. Decreased DNA methylation in acute myeloid leukemia patients with DNMT3A mutations and prognostic implications of DNA methylation. Leuk Res. 2012;36(9):1128\u201333.","journal-title":"Leuk Res"},{"issue":"20","key":"1625_CR11","doi-asserted-by":"publisher","first-page":"5573","DOI":"10.1182\/blood-2011-01-332353","volume":"118","author":"S Deneberg","year":"2011","unstructured":"Deneberg S, Guardiola P, Lennartsson A, Qu Y, Gaidzik V, Blanchet O, et al. Prognostic DNA methylation patterns in cytogenetically normal acute myeloid leukemia are predefined by stem cell chromatin marks. Blood. 2011;118(20):5573\u201382.","journal-title":"Blood"},{"key":"1625_CR12","doi-asserted-by":"publisher","first-page":"8489","DOI":"10.1038\/ncomms9489","volume":"6","author":"N Jung","year":"2015","unstructured":"Jung N, Dai B, Gentles AJ, Majeti R, Feinberg AP. An LSC epigenetic signature is largely mutation independent and implicates the HOXA cluster in AML pathogenesis. Nat Commun. 2015;6:8489.","journal-title":"Nat Commun"},{"issue":"6","key":"1625_CR13","doi-asserted-by":"publisher","first-page":"1279","DOI":"10.1038\/leu.2015.6","volume":"29","author":"DH Spencer","year":"2015","unstructured":"Spencer DH, Young MA, Lamprecht TL, Helton NM, Fulton R, O\u2019Laughlin M, et al. Epigenomic analysis of the HOX gene loci reveals mechanisms that may control canonical expression patterns in AML and normal hematopoietic cells. Leukemia. 2015;29(6):1279\u201389.","journal-title":"Leukemia"},{"issue":"2","key":"1625_CR14","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1038\/sj.leu.2402354","volume":"16","author":"HA Drabkin","year":"2002","unstructured":"Drabkin HA, Parsy C, Ferguson K, Guilhot F, Lacotte L, Roy L, et al. Quantitative HOX expression in chromosomally defined subsets of acute myelogenous leukemia. Leukemia. 2002;16(2):186\u201395.","journal-title":"Leukemia"},{"key":"1625_CR15","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1016\/j.jare.2019.05.006","volume":"20","author":"A Nagy","year":"2019","unstructured":"Nagy A, Osz A, Budczies J, Krizsan S, Szombath G, Demeter J, et al. Elevated HOX gene expression in acute myeloid leukemia is associated with NPM1 mutations and poor survival. J Adv Res. 2019;20:105\u201316.","journal-title":"J Adv Res"},{"issue":"2","key":"1625_CR16","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1053\/j.seminhematol.2018.08.001","volume":"56","author":"SF Cai","year":"2019","unstructured":"Cai SF, Levine RL. Genetic and epigenetic determinants of AML pathogenesis. Semin Hematol. 2019;56(2):84\u20139.","journal-title":"Semin Hematol"},{"issue":"11","key":"1625_CR17","doi-asserted-by":"publisher","first-page":"595","DOI":"10.1182\/blood.V110.11.595.595","volume":"110","author":"H Kroeger","year":"2007","unstructured":"Kroeger H, Jelinek J, Kornblau SM, Bueso-Ramos CE, Issa J. Increased DNA methylation is associated with good prognosis in AML. Blood. 2007;110(11):595.","journal-title":"Blood"},{"key":"1625_CR18","unstructured":"Andrews S. FastQC: a quality control tool for high throughput sequence data [Online]. 2015; Available at: http:\/\/www.bioinformatics.babraham.ac.uk\/projects\/fastqc\/. Accessed 20 June 2020."},{"issue":"19","key":"1625_CR19","doi-asserted-by":"publisher","first-page":"3047","DOI":"10.1093\/bioinformatics\/btw354","volume":"32","author":"P Ewels","year":"2016","unstructured":"Ewels P, Magnusson M, Lundin S, Kaller M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics. 2016;32(19):3047\u20138.","journal-title":"Bioinformatics"},{"issue":"1","key":"1625_CR20","doi-asserted-by":"publisher","first-page":"10","DOI":"10.14806\/ej.17.1.200","volume":"17","author":"M Martin","year":"2011","unstructured":"Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 2011;17(1):10.","journal-title":"EMBnet J"},{"issue":"13","key":"1625_CR21","doi-asserted-by":"publisher","first-page":"1698","DOI":"10.1093\/bioinformatics\/bts254","volume":"28","author":"C Otto","year":"2012","unstructured":"Otto C, Stadler PF, Hoffmann S. Fast and sensitive mapping of bisulfite-treated sequencing data. Bioinformatics. 2012;28(13):1698\u2013704.","journal-title":"Bioinformatics"},{"issue":"6","key":"1625_CR22","doi-asserted-by":"publisher","first-page":"548","DOI":"10.1200\/JCO.2013.50.6337","volume":"32","author":"G Marcucci","year":"2014","unstructured":"Marcucci G, Yan P, Maharry K, Frankhouser D, Nicolet D, Metzeler KH, et al. Epigenetics meets genetics in acute myeloid leukemia: clinical impact of a novel seven-gene score. J Clin Oncol. 2014;32(6):548\u201356.","journal-title":"J Clin Oncol"},{"issue":"5","key":"1625_CR23","doi-asserted-by":"publisher","first-page":"495","DOI":"10.1038\/nbt.1630","volume":"28","author":"CY McLean","year":"2010","unstructured":"McLean CY, Bristor D, Hiller M, Clarke SL, Schaar BT, Lowe CB, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat Biotechnol. 2010;28(5):495\u2013501.","journal-title":"Nat Biotechnol"},{"issue":"W1","key":"1625_CR24","doi-asserted-by":"publisher","first-page":"W90","DOI":"10.1093\/nar\/gkw377","volume":"44","author":"MV Kuleshov","year":"2016","unstructured":"Kuleshov MV, Jones MR, Rouillard AD, Fernandez NF, Duan Q, Wang Z, et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res. 2016;44(W1):W90\u20137.","journal-title":"Nucleic Acids Res"},{"key":"1625_CR25","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-10-48","author":"E Eden","year":"2009","unstructured":"Eden E, Navon R, Steinfeld I, Lipson D, Yakhini Z. GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists. BMC Bioinform. 2009. https:\/\/doi.org\/10.1186\/1471-2105-10-48.","journal-title":"BMC Bioinform"}],"container-title":["Clinical Epigenetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13148-024-01625-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13148-024-01625-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13148-024-01625-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T09:02:26Z","timestamp":1705914146000},"score":1,"resource":{"primary":{"URL":"https:\/\/clinicalepigeneticsjournal.biomedcentral.com\/articles\/10.1186\/s13148-024-01625-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,22]]},"references-count":25,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["1625"],"URL":"https:\/\/doi.org\/10.1186\/s13148-024-01625-x","relation":{},"ISSN":["1868-7083"],"issn-type":[{"value":"1868-7083","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,22]]},"assertion":[{"value":"18 September 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 January 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 January 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Informed consent was obtained from all patients and healthy donors. The research was approved by the Ethics Committees of the Institute of Hematology and Blood Transfusion (Prague, Czech Republic) and the University Hospital Brno (Brno, Czech Republic).","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"17"}}