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Abstract A051 Genome-wide CRISPR/Cas9 library screening identified TP53 as a critical driver for resistance to EZH2 inhibitor in rhabdoid tumors

2024· article· en· W4402267061 on OpenAlexaboutno aff
Céline Chauvin, Tiphaine Héry, Rachida Bouarich, Fariba Némati, Diego Teyssonneau, Camille Fouassier, Chiara Giudiceandrea, Zhi‐Yan Han, Sakina Zaïdi, Didier Surdez, Sergio Roman‐Roman, Didier Decaudin, Raphaël Margueron, Franck Bourdeaut

Bibliographic record

VenueCancer Research · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChromatin Remodeling and Cancer
Canadian institutionsnot available
Fundersnot available
KeywordsCRISPRGenomeEZH2BiologyGeneticsMedicineCancer researchComputational biologyGeneEpigenetics

Abstract

fetched live from OpenAlex

Abstract Rhabdoid tumors (RTs) are rare, highly aggressive pediatric malignancies which occur in kidney, soft-parts and brain. They are characterized by a complete inactivation of the SMARCB1 tumor suppressor gene encoding a core subunit of the chromatin remodeling SWI/SNF complex. Prognosis for children with RTs is poor as, in many instances, these tumors are resistant to conventional type chemotherapy. Pharmacological inhibition of EZH2 is a promising strategy to treat some tumors with loss of function in SMARCB1. However, the clinical response rate remains low, and both primary and secondary resistance have been reported. Understanding the mechanisms of resistance to EZH2 inhibition may allow new therapeutic hypothesis. For this purpose, we realized a genome-wide CRISPR-Cas9 knockout screening on two rhabdoid cell lines treated with EZH2 inhibitor. We identified TP53 loss as the sole consistent gene knock-out able to confer some resistance to EZH2 inhibition in both cell lines. Conversely, we demonstrated that MDM2/MDM4 inhibition, in a TP53-dependant manner, strongly synergized with EZH2 inhibition to control cell lines viability in vitro. We further treated 4 rhabdoid patient-derived xenografts with UNC1999, Idasanutlin and the combination of both and observed a potent tumor growth control upon combined EZH2 and MDM2/MDM4 inhibitions. To conclude, our results strongly encourage to assess the actual efficacy of combined MDM2/MDM4 and EZH2 inhibitors in the treatment of patients with SMARCB1-deficient rhabdoid tumors. Citation Format: Céline Chauvin, Tiphaine Hery, Rachida Bouarich, Fariba Nemati, Diego Teyssonneau, Camille Fouassier, Chiara Giudiceandrea, Zhi-Yan Han, Sakina Zaidi, Didier Surdez, Sergio Roman-Roman, Didier Decaudin, Raphaël Margueron, Franck Bourdeaut. Genome-wide CRISPR/Cas9 library screening identified TP53 as a critical driver for resistance to EZH2 inhibitor in rhabdoid tumors [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr A051.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.279
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.046
GPT teacher head0.404
Teacher spread0.358 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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