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Record W2043825335 · doi:10.1002/ijc.21797

4‐HPR modulates gene expression in ovarian cells

2006· article· en· W2043825335 on OpenAlexaff
Molly Brewer, Nathaniel D. Kirkpatrick, J. Taylor Wharton, Jian Wang, Kenneth D. Hatch, Nelly Auersperg, Urs Utzinger, David M. Gershenson, Robert C. Bast, Changping Zou

Bibliographic record

VenueInternational Journal of Cancer · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinoids in leukemia and cellular processes
Canadian institutionsUniversity of British Columbia
FundersOvarian Cancer Research FoundationU.S. Department of Defense
KeywordsOvarian cancerCancer researchMicroarray analysis techniquesBiologyCancer cellCancerMicroarrayBlotApoptosisGene expressionGeneGenetics

Abstract

fetched live from OpenAlex

Ovarian cancer has a high rate of recurrence and subsequent mortality following chemotherapy despite intense efforts to improve treatment outcomes. Recent trials have suggested that retinoids, especially 4-(N-hydroxyphenyl) retinamide (4-HPR), play an important role as a chemopreventive agent and are currently being used in clinical trials for ovarian cancer chemoprevention as well as treatment. This study examines the mechanism of its activity in premalignant and cancer cells. We investigated the modulation of gene expression by 4-HPR in immortalized ovarian surface epithelial (IOSE) cells and ovarian cancer (OVCA433) cells with DNA microarray. Real time RT-PCR and western blotting were used to confirm the microarray results and metabolic changes were examined with optical fluorescence spectroscopy. 4-HPR resulted in an up-regulation of expression of proapoptotic genes and mitochondrial uncoupling protein in OVCA433 cells and modulation of the RXR receptors in IOSE cells, and down-regulation of mutant BRCA genes in both IOSE and OVCA433 cells. 4-HPR had a larger effect on the redox in the 433 cells compared to IOSE. These findings suggest that 4-HPR acts through different mechanisms in premalignant ovarian surface cells and cancer cells, with a preventive effect in premalignant cells and a treatment effect in cancer cells.

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 score0.015
Threshold uncertainty score0.238

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 head0.004
GPT teacher head0.259
Teacher spread0.255 · 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

Citations8
Published2006
Admission routes1
Has abstractyes

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