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Record W4417006557 · doi:10.1182/blood-2025-7490

Priming of bone marrow stromal cells with the epigenetic modifier decitabine overcomes stroma-mediated resistance to bortezomib in multiple myeloma cells.

2025· article· en· W4417006557 on OpenAlexaff
Jahangir Abdi, Janna Emery, Horace T. Crogman, Armand Keating

Bibliographic record

VenueBlood · 2025
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsDecitabineBortezomibBone marrowMultiple myelomaStromal cellPriming (agriculture)Cancer cell

Abstract

fetched live from OpenAlex

Abstract Title of the project Priming of bone marrow stromal cells with the epigenetic modifier decitabine overcomes stroma-mediated resistance to bortezomib in multiple myeloma cells. Introduction. In multiple myeloma (MM), the malignant plasma cells reside in the bone marrow microenvironment. Within this environment, MM cells are protected against anti-myeloma drugs through interaction with bone marrow mesenchymal stromal cells (MSCs). This form of stroma-mediated protection may partly explain poor treatment response in some MM patients. One approach to overcome this resistance is using a combination of drugs which target both the cancer cells and disrupt the above interaction at the same time. In this project we investigated whether pre-treatment (priming) of MSCs with an epigenetic modifier decitabine could overcome the above resistance when MM cells are exposed to the anti-myeloma drug bortezomib (BTZ). Methods. The luciferase-tagged MM cell line (U266) and the bone marrow MSC line (HS.5) were cultivated and maintained in their specific culture media. First, HS.5 cells were seeded on 96-well plates and treated with different doses of decitabine for 24h. Then, the decitabine was removed and wells washed, U266 cells were added on top of the HS.5 cells (co-culture), BTZ was added to the wells and plate incubation continued for another 24h. Finally, luminescence of the 96-well plate was measured using a luminescence plate reader to calculate % cytotoxicity. Results. MM cells’ death by BTZ was the highest in the absence of HS.5 cells (n=3, mean=67%), however, it was significantly reduced when MM cells were co-cultured with HS.5 cells (n=3, mean=44.5%, p<0.001) implying stroma-induced drug resistance. On the other hand, when HS.5 cells were primed with decitabine, cell death in MM cells was increased to the level close to MM cells’ death in monoculture (n=3, mean= 63.5%, p=0.171) indicating rescue effect of decitabine treatment of HS.5 cells.Conclusions. Our findings indicate that MSCs may at least partly employ an epigenetic mechanism to induce resistance to drugs in MM cells via direct interaction with latter cells. However, further investigation is ongoing to establish whether this could be a potential underlying mechanism.

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 integrity0.0000.001
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 head0.013
GPT teacher head0.252
Teacher spread0.239 · 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
Published2025
Admission routes1
Has abstractyes

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