Evidence map›Paper›PMID 26237075›Full record

ArticleEpigenetics2015

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

Alem S Gabriel, Fadhel M Lafta, Edward C Schwalbe, Sirintra Nakjang, Simon J Cockell, Alice Iliasova, Amir Enshaei, Claire Schwab, Vikki Rand, Steven C Clifford and 6 more

Open access · bronzeAbstract read
In one paragraph

Article in Epigenetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
1.8field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 39 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Age-Driven Genetic and Epigenetic Heterogeneity in B-ALL.International journal of molecular sciences · 2025
    Review
  5. Article
  6. Article
  7. Review
  8. Identification ofInternational journal of molecular sciences · 2023
    Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Epigenetic Control of Infant B Cell Precursor Acute Lymphoblastic Leukemia.International journal of molecular sciences · 2021
    Review
  14. Article
  15. Article
  16. Article
  17. Epigenetic Priming in Childhood Acute Lymphoblastic Leukemia.Frontiers in cell and developmental biology · 2019
    Review
  18. Review
  19. Article
  20. Molecular processes involved in B cell acute lymphoblastic leukaemia.Cellular and molecular life sciences : CMLS · 2018
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 6 institutions in 2 countries.

Alem S Gabriela Northern Institute for Cancer Research; Faculty of Medical Sciences; Newcastle University ; Newcastle upon Tyne , UK.
Fadhel M Lafta
Edward C Schwalbe
Sirintra Nakjang
Simon J Cockell
Alice Iliasova
Amir Enshaei
Claire Schwab
Vikki Rand
Steven C Clifford
Sally E Kinsey
Chris D Mitchell
Ajay Vora
Christine J Harrison
Anthony V Moorman
Gordon Strathdee
Newcastle upon Tyne Hospital · GBNewcastle University · GBJohn Radcliffe Hospital · GBNorthumbria University · GBBioinformatics Institute · SGLeeds General Infirmary · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

EpigenomicsBasic Helix-Loop-Helix ProteinsChildChild, PreschoolCore Binding Factor Alpha 2 SubunitCpG IslandsDNA-Binding ProteinsDNA MethylationETS Translocation Variant 6 ProteinGenome, HumanHumansInfantOncogene Proteins, FusionPre-B-Cell Leukemia Transcription Factor 1Precursor Cell Lymphoblastic Leukemia-LymphomaPrognosisBasic Helix-Loop-Helix ProteinsCore Binding Factor Alpha 2 SubunitDNA-Binding ProteinsETS Translocation Variant 6 ProteinOncogene Proteins, FusionPBX1 protein, humanPre-B-Cell Leukemia Transcription Factor 1Proto-Oncogene ProteinsProto-Oncogene Proteins c-etsRepressor ProteinsRUNX1 protein, humanTCF3 protein, human450KALLbiomarkerchildhoodmethylationrelapse

Identifiers

PMID26237075
PMCPMC4622588
OpenAlexW2170959495

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.