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Record W4200016728 · doi:10.3390/cancers14010014

Tipping Growth Inhibition into Apoptosis by Combining Treatment with MDM2 and WIP1 Inhibitors in p53WT Uterine Leiomyosarcoma

2021· article· en· W4200016728 on OpenAlexaff
Victoria Chamberlain, Yvette Drew, John Lunec

Bibliographic record

VenueCancers · 2021
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsUniversity of British Columbia
FundersSarcoma UK
KeywordsApoptosisGrowth inhibitionMdm2Cancer researchChemistryPharmacologyBiologyBiochemistry

Abstract

fetched live from OpenAlex

As there is no optimal therapeutic strategy defined for women with advanced or recurrent uLMS, there is an urgent need for the discovery of novel, targeted approaches. One such area of interest is the pharmacological inhibition of the MDM2-p53 interaction with small-molecular-weight MDM2 inhibitors. Growth inhibition and cytotoxic assays were used to evaluate uLMS cell line responses to MDM2 inhibitors as single agents and in combination, qRT-PCR to assess transcriptional changes and Caspase-Glo 3/7 assay to detect apoptosis. RG7388 and HDM201 are potent, selective antagonists of the MDM2-p53 interaction that can effectively stabilise and activate p53 in a dose-dependent manner. GSK2830371, a potent and selective WIP1 phosphatase inhibitor, was shown to significantly potentiate the growth inhibitory effects of RG7388 and HDM201, and significantly increase the mRNA expression of p53 transcriptional target genes in a p53WT cell line at a concentration that has no growth inhibitory effects as a single agent. RG7388, HDM201 and GSK2830371 failed to induce apoptosis as single agents; however, a combination treatment tipped cells into apoptosis from senescence. These data present the possibility of MDM2 and WIP1 inhibitor combinations as a potential treatment option for p53WT uLMS patients that warrants further investigation.

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 score0.027
Threshold uncertainty score0.851

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 head0.009
GPT teacher head0.242
Teacher spread0.233 · 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
Published2021
Admission routes1
Has abstractyes

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