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Resistance To Vorinostat In Hematological Malignancies May Involve Cytoprotective UPR and Correlates With Increased Sensitivity To Bortezomib-Induced Cell Death

2013· article· en· W2279265373 on OpenAlexaff
Daphné Dupéré-Richer, Mena Kinal, Filippa Pettersson, Wilson H. Miller

Bibliographic record

VenueBlood · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHistone Deacetylase Inhibitors Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsVorinostatBortezomibHistone deacetylase inhibitorProteasome inhibitorCancer researchAutophagyHistone deacetylaseBiologyProteasomePharmacologyMedicineImmunologyHistoneApoptosisMultiple myelomaCell biology

Abstract

fetched live from OpenAlex

Abstract Histone deacetylase inhibitors (HDACi) have shown promising activity against hematological malignancies in clinical trials and have led to the approval of vorinostat for the treatment of cutaneous T-cell lymphoma. However, as with many cancer therapies, de novoresistance is common and acquired resistance inevitably follows sensitivity. This issue is particularly difficult to resolve in HDACi therapy, as the mechanism of action is still unclear and may involve several components. Our objective was to understand the molecular mechanisms underlying resistance to HDACi in order to design better combination strategies and to identify predictive biomarkers for response to HDACi therapy. To gain insight into HDACi resistance, we developed vorinostat-resistant clones using a dose escalation protocol in the monocytic-like, histiocytic lymphoma cell line U937 and the diffuse large B-cell lymphoma SUDHL6. Indeed, resistant cells grow in 4 µM vorinostat without induction of cell death. Using a variety of targeted drugs, we evaluated the lethal dose (LD)50in the resistant cells versus their parental counterpart in order to screen for potential pathways involved in resistance to vorinostat. We found that the vorinostat-resistant cells are cross-resistant to other HDACi but not all. Interestingly, the resistant cells exhibit increased sensitivity toward bortezomib, an inhibitor of the proteasome and to chloroquine, an inhibitor of autophagy. Both these drugs target protein processing, suggesting its importance in driving resistance to HDACi. We found that, in addition to elevated autophagy, vorinostat-resistant cells exhibit marks of ER stress, such as dilated ER when visualized by electron microscopy. Moreover, resistant cells have an increased protein synthesis rate and an accumulation of ubiquitinated proteins compared to their parental counterparts. Consistent with this, we observe activation of the UPR in the resistant cells. We hypothesized that activation of UPR could be a mechanism of vorinostat resistance, because the UPR induces the upregulation of pro-survival genes and may induce autophagy. Understanding vorinostat resistance holds clinical relevance in terms of improving HDACi therapy and being able to identify subsets of patients who would benefit most from combination therapy, such as vorinostat with bortezomib. Disclosures: No relevant conflicts of interest to declare.

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 head0.010
GPT teacher head0.230
Teacher spread0.221 · 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".

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Citations5
Published2013
Admission routes1
Has abstractyes

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