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MEDB-43. Development of a bioinformatics pipeline for identification of differential DNA methylation events associated with medulloblastoma relapse

Relapsed medulloblastoma (rMB) is treatment-resistant and fatal in ~95% of cases. The epigenetic features of rMB, and any role as drivers of disease relapse/treatment-resistance have yet to be investigated. We therefore developed a pipeline to identify differentially methylated CpGs (DM-CpGs) and re...

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Autores principales: Kui, Christopher, Richardson, Stacey, Schwalbe, Edward C, Thompson, Dean, Keeling, Claire, Strathdee, Gordon, Dufour, Christelle, Bailey, Simon, Ramaswamy, Vijay, Clifford, Steven C, Hill, Rebecca M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9164906/
http://dx.doi.org/10.1093/neuonc/noac079.417
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author Kui, Christopher
Richardson, Stacey
Schwalbe, Edward C
Thompson, Dean
Keeling, Claire
Strathdee, Gordon
Dufour, Christelle
Bailey, Simon
Ramaswamy, Vijay
Clifford, Steven C
Hill, Rebecca M
author_facet Kui, Christopher
Richardson, Stacey
Schwalbe, Edward C
Thompson, Dean
Keeling, Claire
Strathdee, Gordon
Dufour, Christelle
Bailey, Simon
Ramaswamy, Vijay
Clifford, Steven C
Hill, Rebecca M
author_sort Kui, Christopher
collection PubMed
description Relapsed medulloblastoma (rMB) is treatment-resistant and fatal in ~95% of cases. The epigenetic features of rMB, and any role as drivers of disease relapse/treatment-resistance have yet to be investigated. We therefore developed a pipeline to identify differentially methylated CpGs (DM-CpGs) and regions (DMRs) in a paired-rMB cohort. Our paired-rMB cohort (n=61, relapsed tumours matched with diagnosis counterparts) with available Illumina Methylation 450K/850K microarray data was processed in R-Studio. The packages Limma and DMRcate were used to perform a paired differential methylation analysis on a filtered selection of array probes (n=335,767), identifying DM-CpGs and DMRs with a 5% FDR. DMRs were further retained if they had a maximum-Δβ of >0.2 and correlated with locus-specific gene expression in a separate paired DNA-methylation array/RNA-seq cohort from medulloblastoma diagnosis samples (n=202). Finally, we created univariable Cox models to assess the prognostic potential of DM-CpGs/DMRs in an independent survival cohort of medulloblastoma diagnosis samples (n=498). Across the paired-rMB cohort, there were few significant differential methylation events initially identified at relapse (n=258 DM-CpGs, n=32 DMRs). Upon sub-analysis by molecular group, MB(Group4) (n=18 pairs) alone yielded significant findings (n=189 DM-CpGs, n=26 DMRs). Most changes involved hypermethylation events detected at relapse. Multiple DM-CpGs identified at relapse were prognostic for both overall and event-free survival when assessed in our independent cohort (n=22 whole cohort, n=13 Group 4, BH-adjusted p<0.05). When applying the DMR filters, only the MB(Group4) DMRs passed the Δβ filter (n=18/26), with few correlating with gene expression (n=2, p<0.001), and none demonstrating prognostic significance. This pipeline facilitates exploration of the clinical relevance of epigenome-wide changes in a paired-rMB cohort. We highlight the potential prognostic significance of DM-CpGs, and future work will explore the potential functional role of candidate-genes associated with our DMRs, as novel drivers of rMB.
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spelling pubmed-91649062022-06-05 MEDB-43. Development of a bioinformatics pipeline for identification of differential DNA methylation events associated with medulloblastoma relapse Kui, Christopher Richardson, Stacey Schwalbe, Edward C Thompson, Dean Keeling, Claire Strathdee, Gordon Dufour, Christelle Bailey, Simon Ramaswamy, Vijay Clifford, Steven C Hill, Rebecca M Neuro Oncol Medulloblastoma Relapsed medulloblastoma (rMB) is treatment-resistant and fatal in ~95% of cases. The epigenetic features of rMB, and any role as drivers of disease relapse/treatment-resistance have yet to be investigated. We therefore developed a pipeline to identify differentially methylated CpGs (DM-CpGs) and regions (DMRs) in a paired-rMB cohort. Our paired-rMB cohort (n=61, relapsed tumours matched with diagnosis counterparts) with available Illumina Methylation 450K/850K microarray data was processed in R-Studio. The packages Limma and DMRcate were used to perform a paired differential methylation analysis on a filtered selection of array probes (n=335,767), identifying DM-CpGs and DMRs with a 5% FDR. DMRs were further retained if they had a maximum-Δβ of >0.2 and correlated with locus-specific gene expression in a separate paired DNA-methylation array/RNA-seq cohort from medulloblastoma diagnosis samples (n=202). Finally, we created univariable Cox models to assess the prognostic potential of DM-CpGs/DMRs in an independent survival cohort of medulloblastoma diagnosis samples (n=498). Across the paired-rMB cohort, there were few significant differential methylation events initially identified at relapse (n=258 DM-CpGs, n=32 DMRs). Upon sub-analysis by molecular group, MB(Group4) (n=18 pairs) alone yielded significant findings (n=189 DM-CpGs, n=26 DMRs). Most changes involved hypermethylation events detected at relapse. Multiple DM-CpGs identified at relapse were prognostic for both overall and event-free survival when assessed in our independent cohort (n=22 whole cohort, n=13 Group 4, BH-adjusted p<0.05). When applying the DMR filters, only the MB(Group4) DMRs passed the Δβ filter (n=18/26), with few correlating with gene expression (n=2, p<0.001), and none demonstrating prognostic significance. This pipeline facilitates exploration of the clinical relevance of epigenome-wide changes in a paired-rMB cohort. We highlight the potential prognostic significance of DM-CpGs, and future work will explore the potential functional role of candidate-genes associated with our DMRs, as novel drivers of rMB. Oxford University Press 2022-06-03 /pmc/articles/PMC9164906/ http://dx.doi.org/10.1093/neuonc/noac079.417 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Medulloblastoma
Kui, Christopher
Richardson, Stacey
Schwalbe, Edward C
Thompson, Dean
Keeling, Claire
Strathdee, Gordon
Dufour, Christelle
Bailey, Simon
Ramaswamy, Vijay
Clifford, Steven C
Hill, Rebecca M
MEDB-43. Development of a bioinformatics pipeline for identification of differential DNA methylation events associated with medulloblastoma relapse
title MEDB-43. Development of a bioinformatics pipeline for identification of differential DNA methylation events associated with medulloblastoma relapse
title_full MEDB-43. Development of a bioinformatics pipeline for identification of differential DNA methylation events associated with medulloblastoma relapse
title_fullStr MEDB-43. Development of a bioinformatics pipeline for identification of differential DNA methylation events associated with medulloblastoma relapse
title_full_unstemmed MEDB-43. Development of a bioinformatics pipeline for identification of differential DNA methylation events associated with medulloblastoma relapse
title_short MEDB-43. Development of a bioinformatics pipeline for identification of differential DNA methylation events associated with medulloblastoma relapse
title_sort medb-43. development of a bioinformatics pipeline for identification of differential dna methylation events associated with medulloblastoma relapse
topic Medulloblastoma
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9164906/
http://dx.doi.org/10.1093/neuonc/noac079.417
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