Evidence map›Paper›PMID 37872885›Full record

ReviewMolecular oncology2023

A guide to epigenetics in leukaemia stem cells.

Shuchi Agrawal-Singh, Jaana Bagri, Nathalie Sakakini, Brian J P Huntly

Abstract readReview
In one paragraph

Review in Molecular oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

4 authors.

Shuchi Agrawal-SinghDepartment of Haematology, Jeffrey Cheah Biomedical Centre, University of Cambridge, UK.ORCID 0000-0001-8632-4556
Jaana BagriDepartment of Haematology, Jeffrey Cheah Biomedical Centre, University of Cambridge, UK.
Nathalie SakakiniDepartment of Haematology, Jeffrey Cheah Biomedical Centre, University of Cambridge, UK.
Brian J P HuntlyDepartment of Haematology, Jeffrey Cheah Biomedical Centre, University of Cambridge, UK.ORCID 0000-0003-0312-161X

Funding

Cancer Research UK 25508Cancer Research UK C49940/A25117Cancer Research UK DRCRPG-Nov22/100014Medical Research Council MC_PC_17230Medical Research Council MR/X008371/1Wellcome TrustWellcome Trust 203151/Z/16/ZWellcome Trust 218481/Z/19/Z
6 · The paper itself

Abstract

Leukaemia stem cells (LSCs) are the critical seed for the growth of haematological malignancies, driving the clonal expansion that enables disease initiation, relapse and often resistance. Specifically, they display inherent phenotypic and epigenetic plasticity resulting in complex heterogenic diseases. In this review, we discuss the key principles of deregulation of epigenetic processes that shape this disease evolution. We consider measures to define and quantify clonal heterogeneity, combining information from recent studies assessing mutational, transcriptional and epigenetic landscapes at single cell resolution in myeloid neoplasms (MN). We highlight the importance of integrating epigenetic and genetic information to better understand inter- and intra-patient heterogeneity and discuss how this understanding further informs evolution and progression trajectories and subsequent clinical response in MN. Under this topic, we also discuss efforts to identify mechanisms of resistance, by longitudinal analyses of patient samples. Finally, we highlight how we might target these aberrant epigenetic processes for better therapeutic outcomes and to potentially eradicate LSCs.

Indexed as

Leukemia, Myeloid, AcuteEpigenesis, GeneticHumansMutationNeoplastic Stem CellsStem Cellsepigenetic plasticityheterogeneityleukaemia stem cellsmyeloid neoplasmssingle cell studies and multiomicstargeting LSC

Identifiers

PMID37872885
PMCPMC10701772

What Socratic holds

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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 Socratic graph.