Literature DB >> 25348669

Validation of DNA methylation to predict outcome in acute myeloid leukemia by use of xMELP.

Gerald B W Wertheim1, Catherine Smith2, Marlise Luskin3, Alison Rager3, Maria E Figueroa4, Martin Carroll5, Stephen R Master6.   

Abstract

BACKGROUND: Epigenetic dysregulation involving alterations in DNA methylation is a hallmark of various types of cancer, including acute myeloid leukemia (AML). Although specific cancer types and clinical aggressiveness of tumors can be determined by DNA methylation status, the assessment of DNA methylation at multiple loci is not routinely performed in the clinical laboratory.
METHODS: We recently described a novel microsphere-based assay for multiplex evaluation of DNA methylation. In the current study, we validated and used an improved assay [termed expedited microsphere HpaII small fragment Enrichment by Ligation-mediated PCR (xMELP)] that can be performed with appropriate clinical turnaround time.
RESULTS: Using the xMELP assay in conjunction with a new 17-locus random forest classifier that has been trained using 344 AML samples, we were able to segregate an independent cohort of 70 primary AML patients into methylation-determined subgroups with significantly distinct mortality risk (P = 0.009). We also evaluated precision, QC parameters, and preanalytic variables of the xMELP assay and determined the sensitivity of the random forest classifier score to failure at 1 or more loci.
CONCLUSIONS: Our results demonstrate that xMELP performance is suitable for implementation in the clinical laboratory and predicts AML outcome in an independent patient cohort.
© 2014 American Association for Clinical Chemistry.

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Year:  2014        PMID: 25348669      PMCID: PMC4384518          DOI: 10.1373/clinchem.2014.229781

Source DB:  PubMed          Journal:  Clin Chem        ISSN: 0009-9147            Impact factor:   8.327


  21 in total

Review 1.  A decade of exploring the cancer epigenome - biological and translational implications.

Authors:  Stephen B Baylin; Peter A Jones
Journal:  Nat Rev Cancer       Date:  2011-09-23       Impact factor: 60.716

2.  A comparative analysis of molecular genetic and conventional cytogenetic detection of diagnostically important translocations in more than 400 cases of acute leukemia, highlighting the frequency of false-negative conventional cytogenetics.

Authors:  Rebecca L King; Mojdeh Naghashpour; Christopher D Watt; Jennifer J D Morrissette; Adam Bagg
Journal:  Am J Clin Pathol       Date:  2011-06       Impact factor: 2.493

3.  Quantitative DNA methylation predicts survival in adult acute myeloid leukemia.

Authors:  Lars Bullinger; Mathias Ehrich; Konstanze Döhner; Richard F Schlenk; Hartmut Döhner; Matthew R Nelson; Dirk van den Boom
Journal:  Blood       Date:  2009-11-10       Impact factor: 22.113

4.  DNA methylation profiles and their relationship with cytogenetic status in adult acute myeloid leukemia.

Authors:  Sara Alvarez; Javier Suela; Ana Valencia; Agustín Fernández; Mark Wunderlich; Xabier Agirre; Felipe Prósper; José Ignacio Martín-Subero; Alba Maiques; Francesco Acquadro; Sandra Rodriguez Perales; María José Calasanz; Jose Roman-Gómez; Reiner Siebert; James C Mulloy; José Cervera; Miguel Angel Sanz; Manel Esteller; Juan C Cigudosa
Journal:  PLoS One       Date:  2010-08-16       Impact factor: 3.240

5.  DNA methylation signatures identify biologically distinct subtypes in acute myeloid leukemia.

Authors:  Maria E Figueroa; Sanne Lugthart; Yushan Li; Claudia Erpelinck-Verschueren; Xutao Deng; Paul J Christos; Elizabeth Schifano; James Booth; Wim van Putten; Lucy Skrabanek; Fabien Campagne; Madhu Mazumdar; John M Greally; Peter J M Valk; Bob Löwenberg; Ruud Delwel; Ari Melnick
Journal:  Cancer Cell       Date:  2010-01-07       Impact factor: 31.743

6.  Validation of DNA methylation biomarkers for diagnosis of acute lymphoblastic leukemia.

Authors:  Zac Chatterton; Daniel Burke; Kerry R Emslie; Jeffery M Craig; Jane Ng; David M Ashley; Francoise Mechinaud; Richard Saffery; Nicholas C Wong
Journal:  Clin Chem       Date:  2014-05-14       Impact factor: 8.327

7.  Automated screening for myelodysplastic syndromes through analysis of complete blood count and cell population data parameters.

Authors:  Philipp W Raess; Gert-Jan M van de Geijn; Tjin L Njo; Boudewijn Klop; Dmitry Sukhachev; Gerald Wertheim; Tom McAleer; Stephen R Master; Adam Bagg
Journal:  Am J Hematol       Date:  2014-03-13       Impact factor: 10.047

Review 8.  Hallmarks of cancer: the next generation.

Authors:  Douglas Hanahan; Robert A Weinberg
Journal:  Cell       Date:  2011-03-04       Impact factor: 41.582

Review 9.  The diagnostic value of DNA methylation in leukemia: a systematic review and meta-analysis.

Authors:  Danjie Jiang; Qingxiao Hong; Yusheng Shen; Yan Xu; Huangkai Zhu; Yirun Li; Chunjing Xu; Guifang Ouyang; Shiwei Duan
Journal:  PLoS One       Date:  2014-05-08       Impact factor: 3.240

10.  Genome-wide signatures of differential DNA methylation in pediatric acute lymphoblastic leukemia.

Authors:  Jessica Nordlund; Christofer L Bäcklin; Per Wahlberg; Stephan Busche; Eva C Berglund; Maija-Leena Eloranta; Trond Flaegstad; Erik Forestier; Britt-Marie Frost; Arja Harila-Saari; Mats Heyman; Olafur G Jónsson; Rolf Larsson; Josefine Palle; Lars Rönnblom; Kjeld Schmiegelow; Daniel Sinnett; Stefan Söderhäll; Tomi Pastinen; Mats G Gustafsson; Gudmar Lönnerholm; Ann-Christine Syvänen
Journal:  Genome Biol       Date:  2013-09-24       Impact factor: 13.583

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  5 in total

1.  Validation of a clinical assay of multi-locus DNA methylation for prognosis of newly diagnosed AML.

Authors:  Courtney D Dinardo; Marlise R Luskin; Martin Carroll; Catherine Smith; Jenna Harrison; Sherry Pierce; Steve Kornblau; Marina Konopleva; Tapan Kadia; Hagop Kantarjian; Gerald B Wertheim; Stephen R Master
Journal:  Am J Hematol       Date:  2017-02       Impact factor: 10.047

2.  A clinical measure of DNA methylation predicts outcome in de novo acute myeloid leukemia.

Authors:  Marlise R Luskin; Phyllis A Gimotty; Catherine Smith; Alison W Loren; Maria E Figueroa; Jenna Harrison; Zhuoxin Sun; Martin S Tallman; Elisabeth M Paietta; Mark R Litzow; Ari M Melnick; Ross L Levine; Hugo F Fernandez; Selina M Luger; Martin Carroll; Stephen R Master; Gerald B W Wertheim
Journal:  JCI Insight       Date:  2016-06-16

3.  Detection of prognostic methylation markers by methylC-capture sequencing in acute myeloid leukemia.

Authors:  Yan Li; Hongmei Zhao; Qingyu Xu; Na Lv; Yu Jing; Lili Wang; Xiaowen Wang; Jing Guo; Lei Zhou; Jing Liu; Guofeng Chen; Chongjian Chen; Yonghui Li; Li Yu
Journal:  Oncotarget       Date:  2017-11-30

4.  Development and validation of a multivariate predictive model for rheumatoid arthritis mortality using a machine learning approach.

Authors:  José M Lezcano-Valverde; Fernando Salazar; Leticia León; Esther Toledano; Juan A Jover; Benjamín Fernandez-Gutierrez; Eduardo Soudah; Isidoro González-Álvaro; Lydia Abasolo; Luis Rodriguez-Rodriguez
Journal:  Sci Rep       Date:  2017-08-31       Impact factor: 4.379

Review 5.  Clinical implications of genome-wide DNA methylation studies in acute myeloid leukemia.

Authors:  Yan Li; Qingyu Xu; Na Lv; Lili Wang; Hongmei Zhao; Xiuli Wang; Jing Guo; Chongjian Chen; Yonghui Li; Li Yu
Journal:  J Hematol Oncol       Date:  2017-02-02       Impact factor: 17.388

  5 in total

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