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Record W4404230706 · doi:10.1093/neuonc/noae165.0967

EXTH-36. SHIFTING FROM EPIGENETICS TO THE EPICHAPEROME: HSP90 AS A THERAPEUTIC TARGET FOR H3K27M DIFFUSE MIDLINE GLIOMA (DMG)

2024· article· en· W4404230706 on OpenAlexaff
Stefanie-Grace Sbergio, Sanja Pajovic, Arun Anguraj Vadivel, Jun Watanabe, Javal Sheth, Laura Canty, Gabriela Chiosis, Mark Nitz, Rintaro Hashizume, Cynthia Hawkins

Bibliographic record

VenueNeuro-Oncology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHeat shock proteins research
Canadian institutionsUniversity of TorontoSickKids Foundation
Fundersnot available
KeywordsEpigeneticsHsp90GliomaMedicineCancer researchBiologyHeat shock proteinGenetics

Abstract

fetched live from OpenAlex

Abstract Diffuse midline gliomas (DMG) are lethal pediatric brain tumours, the majority of which have truncal histone (H3K27M) mutations. To investigate cellular vulnerabilities of histone mutant cells we generated oligodendrocyte precursor cells (OPC) isogenic cell lines and performed a high-throughput synthetic lethality drug screen (2400 small molecules). This identified HSP90 inhibitors as a potential therapeutic option for H3K27M DMG. We hypothesize that epichaperome HSP90 inhibitors present a new therapeutic approach targeting multiple aspects of DMG oncogenicity. HSP90 inhibitors, PU-H71 and PU-HZ151, effectively reduced viability of DMG lines in vitro in the low nanomolar range and result in caspase mediated cell death (p<0.0001 1 uM, p<0.05 500 nM, n=6). PU-HZ151 treated mice had a survival benefit vs control mice injected with orthotopic DMG xenografts (p=0.0012). In diseased cells, activated HSP90 forms a scaffold defined as the epichaperome. To unravel the molecular mechanisms of epichaperome inhibition in DMG cells, we performed epichaperomics – a pull down of epichaperome HSP90 with co-chaperones and clients followed by LC-MS/MS analysis. We identified an interactome enriched with proteins involved in cell cycling, RAS/MAPK signaling, immune response, and metabolic reprogramming. Proteomic and phosphoproteomic profiling of DMG cells post-PU-HZ151 treatment provided insights into the direct downstream effects critical for maintaining DMG viability, identified functional vulnerabilities primed by epichaperome inhibition including downregulation of cell cycling, and upregulation of HSF1 mediated cellular response to stress. In silico screening and kinase enrichment analysis highlighted CSNK2A1 as a top active kinase in DMG cells following PU-HZ151 treatment. To enhance the therapeutic efficacy of epichaperome inhibition, we employed the CSNK2A1 kinase inhibitor, CX-4945, in combination with PU-HZ151, resulting in the effective ablation of DMG patient cells in vitro. These data highlight the potential of epichaperome inhibitors for DMG treatment, as they target multiple DMG oncogenic pathways.

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 score0.001
Threshold uncertainty score0.005

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)0.0010.000

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 head0.028
GPT teacher head0.342
Teacher spread0.314 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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