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Record W3113000665 · doi:10.1093/neuonc/noaa215.846

STEM-29. THE HISTONE VARIANT macroH2A2 ORCHESTRATES AN ACTIONABLE CHROMATIN PROGRAM OF STEMNESS IN GLIOBLASTOMA

2020· article· en· W3113000665 on OpenAlexaff
Ana Nikolić, Anna Bobyn, Katrina Ellestad, Xueqing Lun, Michael J. Johnston, Christopher J. Gafuik, Franz J. Zemp, Nicoletta Ninkovic, Daniel R. Berger, Duncan K. Brownsey, Peter B. Dirks, Darren J. Derksen, Donna L. Senger, Jennifer A. Chan, Douglas J. Mahoney, Marco Gallo

Bibliographic record

VenueNeuro-Oncology · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsHospital for Sick ChildrenUniversity of Calgary
Fundersnot available
KeywordsChromatinEpigeneticsBiologyHistoneEpigenomicsReprogrammingCancer researchTranscription factorGlioblastomaTranscriptomeStem cellComputational biologyCell biologyCellGeneticsDNA methylationGene expressionGene

Abstract

fetched live from OpenAlex

Abstract Glioblastoma cells with the crucial stemness property of self-renewal constitute therapy-resistant reservoirs that seed tumor relapse. Effective targeting of these cells in clinical settings has been hampered by their relative quiescence, which invalidates the cell replication bias of most current treatments. Furthermore, although their dependence on specific chromatin and transcriptional states for the maintenance of stemness programs has been proposed as a vulnerability, these nuclear programs have been challenging to target pharmaceutically. Therefore the identification of targetable chromatin paradigms regulating self-renewal would represent a significant advancement for this incurable malignancy. Here we report a new role for the histone variant macroH2A2 in modulating a targetable epigenetic network of stemness in glioblastoma. By integrating transcriptomic, bulk and single-cell epigenomic datasets we generated from patient-derived models and surgical specimens, we show that macroH2A2 represses a transcriptional network of stemness through direct regulation of chromatin accessibility at enhancer elements. Functional assays in vitro and in vivo further showcase that macroH2A2 antagonizes self-renewal and stemness in glioblastoma preclinical models. In agreement with our experimental findings, high expression of macroH2A2 is a positive prognostic factor in clinical glioblastoma cohorts. Reasoning that increasing macroH2A2 levels could be an effective strategy to repress stemness programs and ameliorate patient outcome, we embarked on a screen to identify compounds that could elevate macroH2A2 levels. We report that an inhibitor of the chromatin remodeler Menin increases macroH2A2 levels, which in turn repress self-renewal. Additionally, we provide evidence that Menin inhibition induces viral mimicry programs and the demise of glioblastoma cells. Menin inhibition is being tested in clinical trials for blood malignancies (NCT04067336). Our preclinical work therefore reveals a novel and central role for macroH2A2 in an epigenetic network of stemness and suggests new clinical approaches for glioblastoma.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.295
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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