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Epigenetic landscape correlates with genetic subtype but does not predict outcome in childhood acute lymphoblastic leukemia

Although children with acute lymphoblastic leukemia (ALL) generally have a good outcome, some patients do relapse and survival following relapse is poor. Altered DNA methylation is highly prevalent in ALL and raises the possibility that DNA methylation-based biomarkers could predict patient outcome....

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Autores principales: Gabriel, Alem S, Lafta, Fadhel M, Schwalbe, Edward C, Nakjang, Sirintra, Cockell, Simon J, Iliasova, Alice, Enshaei, Amir, Schwab, Claire, Rand, Vikki, Clifford, Steven C, Kinsey, Sally E, Mitchell, Chris D, Vora, Ajay, Harrison, Christine J, Moorman, Anthony V, Strathdee, Gordon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4622588/
https://www.ncbi.nlm.nih.gov/pubmed/26237075
http://dx.doi.org/10.1080/15592294.2015.1061174
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author Gabriel, Alem S
Lafta, Fadhel M
Schwalbe, Edward C
Nakjang, Sirintra
Cockell, Simon J
Iliasova, Alice
Enshaei, Amir
Schwab, Claire
Rand, Vikki
Clifford, Steven C
Kinsey, Sally E
Mitchell, Chris D
Vora, Ajay
Harrison, Christine J
Moorman, Anthony V
Strathdee, Gordon
author_facet Gabriel, Alem S
Lafta, Fadhel M
Schwalbe, Edward C
Nakjang, Sirintra
Cockell, Simon J
Iliasova, Alice
Enshaei, Amir
Schwab, Claire
Rand, Vikki
Clifford, Steven C
Kinsey, Sally E
Mitchell, Chris D
Vora, Ajay
Harrison, Christine J
Moorman, Anthony V
Strathdee, Gordon
author_sort Gabriel, Alem S
collection PubMed
description Although children with acute lymphoblastic leukemia (ALL) generally have a good outcome, some patients do relapse and survival following relapse is poor. Altered DNA methylation is highly prevalent in ALL and raises the possibility that DNA methylation-based biomarkers could predict patient outcome. In this study, genome-wide methylation analysis, using the Illumina Infinium HumanMethylation450 BeadChip platform, was carried out on 52 diagnostic patient samples from 4 genetic subtypes [ETV6-RUNX1, high hyperdiploidy (HeH), TCF3-PBX1 and dic(9;20)(p11–13;q11)] in a 1:1 case-control design with patients who went on to relapse (as cases) and patients achieving long-term remission (as controls). Pyrosequencing assays for selected loci were used to confirm the array-generated data. Non-negative matrix factorization consensus clustering readily clustered samples according to genetic subgroups and gene enrichment pathway analysis suggested that this is in part driven by epigenetic disruption of subtype specific signaling pathways. Multiple bioinformatics approaches (including bump hunting and individual locus analysis) were used to identify CpG sites or regions associated with outcome. However, no associations with relapse were identified. Our data revealed that ETV6-RUNX1 and dic(9;20) subtypes were mostly associated with hypermethylation; conversely, TCF3-PBX1 and HeH were associated with hypomethylation. We observed significant enrichment of the neuroactive ligand-receptor interaction pathway in TCF3-PBX1 as well as an enrichment of genes involved in immunity and infection pathways in ETV6-RUNX1 subtype. Taken together, our results suggest that altered DNA methylation may have differential impacts in distinct ALL genetic subtypes.
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spelling pubmed-46225882016-02-03 Epigenetic landscape correlates with genetic subtype but does not predict outcome in childhood acute lymphoblastic leukemia Gabriel, Alem S Lafta, Fadhel M Schwalbe, Edward C Nakjang, Sirintra Cockell, Simon J Iliasova, Alice Enshaei, Amir Schwab, Claire Rand, Vikki Clifford, Steven C Kinsey, Sally E Mitchell, Chris D Vora, Ajay Harrison, Christine J Moorman, Anthony V Strathdee, Gordon Epigenetics Research Paper Although children with acute lymphoblastic leukemia (ALL) generally have a good outcome, some patients do relapse and survival following relapse is poor. Altered DNA methylation is highly prevalent in ALL and raises the possibility that DNA methylation-based biomarkers could predict patient outcome. In this study, genome-wide methylation analysis, using the Illumina Infinium HumanMethylation450 BeadChip platform, was carried out on 52 diagnostic patient samples from 4 genetic subtypes [ETV6-RUNX1, high hyperdiploidy (HeH), TCF3-PBX1 and dic(9;20)(p11–13;q11)] in a 1:1 case-control design with patients who went on to relapse (as cases) and patients achieving long-term remission (as controls). Pyrosequencing assays for selected loci were used to confirm the array-generated data. Non-negative matrix factorization consensus clustering readily clustered samples according to genetic subgroups and gene enrichment pathway analysis suggested that this is in part driven by epigenetic disruption of subtype specific signaling pathways. Multiple bioinformatics approaches (including bump hunting and individual locus analysis) were used to identify CpG sites or regions associated with outcome. However, no associations with relapse were identified. Our data revealed that ETV6-RUNX1 and dic(9;20) subtypes were mostly associated with hypermethylation; conversely, TCF3-PBX1 and HeH were associated with hypomethylation. We observed significant enrichment of the neuroactive ligand-receptor interaction pathway in TCF3-PBX1 as well as an enrichment of genes involved in immunity and infection pathways in ETV6-RUNX1 subtype. Taken together, our results suggest that altered DNA methylation may have differential impacts in distinct ALL genetic subtypes. Taylor & Francis 2015-08-03 /pmc/articles/PMC4622588/ /pubmed/26237075 http://dx.doi.org/10.1080/15592294.2015.1061174 Text en © 2015 The Author(s). Published with license by Taylor & Francis http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The moral rights of the named author(s) have been asserted.
spellingShingle Research Paper
Gabriel, Alem S
Lafta, Fadhel M
Schwalbe, Edward C
Nakjang, Sirintra
Cockell, Simon J
Iliasova, Alice
Enshaei, Amir
Schwab, Claire
Rand, Vikki
Clifford, Steven C
Kinsey, Sally E
Mitchell, Chris D
Vora, Ajay
Harrison, Christine J
Moorman, Anthony V
Strathdee, Gordon
Epigenetic landscape correlates with genetic subtype but does not predict outcome in childhood acute lymphoblastic leukemia
title Epigenetic landscape correlates with genetic subtype but does not predict outcome in childhood acute lymphoblastic leukemia
title_full Epigenetic landscape correlates with genetic subtype but does not predict outcome in childhood acute lymphoblastic leukemia
title_fullStr Epigenetic landscape correlates with genetic subtype but does not predict outcome in childhood acute lymphoblastic leukemia
title_full_unstemmed Epigenetic landscape correlates with genetic subtype but does not predict outcome in childhood acute lymphoblastic leukemia
title_short Epigenetic landscape correlates with genetic subtype but does not predict outcome in childhood acute lymphoblastic leukemia
title_sort epigenetic landscape correlates with genetic subtype but does not predict outcome in childhood acute lymphoblastic leukemia
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4622588/
https://www.ncbi.nlm.nih.gov/pubmed/26237075
http://dx.doi.org/10.1080/15592294.2015.1061174
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