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DNA methylation-based subtype prediction for pediatric acute lymphoblastic leukemia

BACKGROUND: We present a method that utilizes DNA methylation profiling for prediction of the cytogenetic subtypes of acute lymphoblastic leukemia (ALL) cells from pediatric ALL patients. The primary aim of our study was to improve risk stratification of ALL patients into treatment groups using DNA...

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Autores principales: Nordlund, Jessica, Bäcklin, Christofer L, Zachariadis, Vasilios, Cavelier, Lucia, Dahlberg, Johan, Öfverholm, Ingegerd, Barbany, Gisela, Nordgren, Ann, Övernäs, Elin, Abrahamsson, Jonas, Flaegstad, Trond, Heyman, Mats M, Jónsson, Ólafur G, Kanerva, Jukka, Larsson, Rolf, Palle, Josefine, Schmiegelow, Kjeld, Gustafsson, Mats G, Lönnerholm, Gudmar, Forestier, Erik, Syvänen, Ann-Christine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4343276/
https://www.ncbi.nlm.nih.gov/pubmed/25729447
http://dx.doi.org/10.1186/s13148-014-0039-z
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author Nordlund, Jessica
Bäcklin, Christofer L
Zachariadis, Vasilios
Cavelier, Lucia
Dahlberg, Johan
Öfverholm, Ingegerd
Barbany, Gisela
Nordgren, Ann
Övernäs, Elin
Abrahamsson, Jonas
Flaegstad, Trond
Heyman, Mats M
Jónsson, Ólafur G
Kanerva, Jukka
Larsson, Rolf
Palle, Josefine
Schmiegelow, Kjeld
Gustafsson, Mats G
Lönnerholm, Gudmar
Forestier, Erik
Syvänen, Ann-Christine
author_facet Nordlund, Jessica
Bäcklin, Christofer L
Zachariadis, Vasilios
Cavelier, Lucia
Dahlberg, Johan
Öfverholm, Ingegerd
Barbany, Gisela
Nordgren, Ann
Övernäs, Elin
Abrahamsson, Jonas
Flaegstad, Trond
Heyman, Mats M
Jónsson, Ólafur G
Kanerva, Jukka
Larsson, Rolf
Palle, Josefine
Schmiegelow, Kjeld
Gustafsson, Mats G
Lönnerholm, Gudmar
Forestier, Erik
Syvänen, Ann-Christine
author_sort Nordlund, Jessica
collection PubMed
description BACKGROUND: We present a method that utilizes DNA methylation profiling for prediction of the cytogenetic subtypes of acute lymphoblastic leukemia (ALL) cells from pediatric ALL patients. The primary aim of our study was to improve risk stratification of ALL patients into treatment groups using DNA methylation as a complement to current diagnostic methods. A secondary aim was to gain insight into the functional role of DNA methylation in ALL. RESULTS: We used the methylation status of ~450,000 CpG sites in 546 well-characterized patients with T-ALL or seven recurrent B-cell precursor ALL subtypes to design and validate sensitive and accurate DNA methylation classifiers. After repeated cross-validation, a final classifier was derived that consisted of only 246 CpG sites. The mean sensitivity and specificity of the classifier across the known subtypes was 0.90 and 0.99, respectively. We then used DNA methylation classification to screen for subtype membership of 210 patients with undefined karyotype (normal or no result) or non-recurrent cytogenetic aberrations (‘other’ subtype). Nearly half (n = 106) of the patients lacking cytogenetic subgrouping displayed highly similar methylation profiles as the patients in the known recurrent groups. We verified the subtype of 20% of the newly classified patients by examination of diagnostic karyotypes, array-based copy number analysis, and detection of fusion genes by quantitative polymerase chain reaction (PCR) and RNA-sequencing (RNA-seq). Using RNA-seq data from ALL patients where cytogenetic subtype and DNA methylation classification did not agree, we discovered several novel fusion genes involving ETV6, RUNX1, and PAX5. CONCLUSIONS: Our findings indicate that DNA methylation profiling contributes to the clarification of the heterogeneity in cytogenetically undefined ALL patient groups and could be implemented as a complementary method for diagnosis of ALL. The results of our study provide clues to the origin and development of leukemic transformation. The methylation status of the CpG sites constituting the classifiers also highlight relevant biological characteristics in otherwise unclassified ALL patients. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13148-014-0039-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-43432762015-02-28 DNA methylation-based subtype prediction for pediatric acute lymphoblastic leukemia Nordlund, Jessica Bäcklin, Christofer L Zachariadis, Vasilios Cavelier, Lucia Dahlberg, Johan Öfverholm, Ingegerd Barbany, Gisela Nordgren, Ann Övernäs, Elin Abrahamsson, Jonas Flaegstad, Trond Heyman, Mats M Jónsson, Ólafur G Kanerva, Jukka Larsson, Rolf Palle, Josefine Schmiegelow, Kjeld Gustafsson, Mats G Lönnerholm, Gudmar Forestier, Erik Syvänen, Ann-Christine Clin Epigenetics Research BACKGROUND: We present a method that utilizes DNA methylation profiling for prediction of the cytogenetic subtypes of acute lymphoblastic leukemia (ALL) cells from pediatric ALL patients. The primary aim of our study was to improve risk stratification of ALL patients into treatment groups using DNA methylation as a complement to current diagnostic methods. A secondary aim was to gain insight into the functional role of DNA methylation in ALL. RESULTS: We used the methylation status of ~450,000 CpG sites in 546 well-characterized patients with T-ALL or seven recurrent B-cell precursor ALL subtypes to design and validate sensitive and accurate DNA methylation classifiers. After repeated cross-validation, a final classifier was derived that consisted of only 246 CpG sites. The mean sensitivity and specificity of the classifier across the known subtypes was 0.90 and 0.99, respectively. We then used DNA methylation classification to screen for subtype membership of 210 patients with undefined karyotype (normal or no result) or non-recurrent cytogenetic aberrations (‘other’ subtype). Nearly half (n = 106) of the patients lacking cytogenetic subgrouping displayed highly similar methylation profiles as the patients in the known recurrent groups. We verified the subtype of 20% of the newly classified patients by examination of diagnostic karyotypes, array-based copy number analysis, and detection of fusion genes by quantitative polymerase chain reaction (PCR) and RNA-sequencing (RNA-seq). Using RNA-seq data from ALL patients where cytogenetic subtype and DNA methylation classification did not agree, we discovered several novel fusion genes involving ETV6, RUNX1, and PAX5. CONCLUSIONS: Our findings indicate that DNA methylation profiling contributes to the clarification of the heterogeneity in cytogenetically undefined ALL patient groups and could be implemented as a complementary method for diagnosis of ALL. The results of our study provide clues to the origin and development of leukemic transformation. The methylation status of the CpG sites constituting the classifiers also highlight relevant biological characteristics in otherwise unclassified ALL patients. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13148-014-0039-z) contains supplementary material, which is available to authorized users. BioMed Central 2015-02-17 /pmc/articles/PMC4343276/ /pubmed/25729447 http://dx.doi.org/10.1186/s13148-014-0039-z Text en © Nordlund et al.; licensee Biomed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Nordlund, Jessica
Bäcklin, Christofer L
Zachariadis, Vasilios
Cavelier, Lucia
Dahlberg, Johan
Öfverholm, Ingegerd
Barbany, Gisela
Nordgren, Ann
Övernäs, Elin
Abrahamsson, Jonas
Flaegstad, Trond
Heyman, Mats M
Jónsson, Ólafur G
Kanerva, Jukka
Larsson, Rolf
Palle, Josefine
Schmiegelow, Kjeld
Gustafsson, Mats G
Lönnerholm, Gudmar
Forestier, Erik
Syvänen, Ann-Christine
DNA methylation-based subtype prediction for pediatric acute lymphoblastic leukemia
title DNA methylation-based subtype prediction for pediatric acute lymphoblastic leukemia
title_full DNA methylation-based subtype prediction for pediatric acute lymphoblastic leukemia
title_fullStr DNA methylation-based subtype prediction for pediatric acute lymphoblastic leukemia
title_full_unstemmed DNA methylation-based subtype prediction for pediatric acute lymphoblastic leukemia
title_short DNA methylation-based subtype prediction for pediatric acute lymphoblastic leukemia
title_sort dna methylation-based subtype prediction for pediatric acute lymphoblastic leukemia
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4343276/
https://www.ncbi.nlm.nih.gov/pubmed/25729447
http://dx.doi.org/10.1186/s13148-014-0039-z
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