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Record W2737725258 · doi:10.1038/cdd.2017.115

Peroxisomes protect lymphoma cells from HDAC inhibitor-mediated apoptosis

2017· article· en· W2737725258 on OpenAlexafffund
Michael S. Dahabieh, Zongyi Ha, Erminia Di Pietro, Jessica N. Nichol, Alicia M. Bolt, Christophe Gonçalves, Daphné Dupéré-Richer, Filippa Pettersson, Koren K. Mann, Nancy Braverman, Sonia V. del Rincón, Wilson H. Miller

Bibliographic record

VenueCell Death and Differentiation · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHistone Deacetylase Inhibitors Research
Canadian institutionsMcGill University Health CentreMcGill University
FundersCanadian Institutes of Health ResearchMcGill UniversitySamuel Waxman Cancer Research Foundation
KeywordsPeroxisomeVorinostatBiologyCell biologyReactive oxygen speciesHistone deacetylase inhibitorGene knockdownApoptosisCancer researchHistone deacetylaseBiochemistryHistoneGene

Abstract

fetched live from OpenAlex

Peroxisomes are a critical rheostat of reactive oxygen species (ROS), yet their role in drug sensitivity and resistance remains unexplored. Gene expression analysis of clinical lymphoma samples suggests that peroxisomes are involved in mediating drug resistance to the histone deacetylase inhibitor (HDACi) Vorinostat (Vor), which promotes ROS-mediated apoptosis. Vor augments peroxisome numbers in cultured lymphoma cells, concomitant with increased levels of peroxisomal proteins PEX3, PEX11B, and PMP70. Genetic inhibition of peroxisomes, using PEX3 knockdown, reveals that peroxisomes protect lymphoma cells against Vor-mediated cell death. Conversely, Vor-resistant cells were tolerant to elevated ROS levels and possess upregulated levels of (1) catalase, a peroxisomal antioxidant, and (2) plasmalogens, ether glycerophospholipids that represent peroxisome function and serve as antioxidants. Catalase knockdown induces apoptosis in Vor-resistant cells and potentiates ROS-mediated apoptosis in Vor-sensitive cells. These findings highlight the role of peroxisomes in resistance to therapeutic intervention in cancer, and provide a novel modality to circumvent drug resistance.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.032
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.012
GPT teacher head0.241
Teacher spread0.229 · 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 teacher head, 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

Citations51
Published2017
Admission routes2
Has abstractyes

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