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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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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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. |
format | Online Article Text |
id | pubmed-4343276 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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