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Record W3047755466 · doi:10.1158/1538-7445.pedca19-b26

Abstract B26: Prometastatic effect of ICG-001, a β-catenin/CBP dependent transcription inhibitor, in osteosarcoma

2020· article· en· W3047755466 on OpenAlexaboutno aff
Geoffroy Danieau, Sarah Morice, Sarah Renault, Kévin Biteau, Régis Brion, Jérôme Amiaud, Frédéric Lézot, Franck Verrecchia, Françoise Rédiní, Bénédicte Brounais-Le Royer

Bibliographic record

VenueCancer Research · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsnot available
Fundersnot available
KeywordsOsteosarcomaWnt signaling pathwayMedicineCancer researchBeta-cateninCateninPopulationInternal medicineOncologySignal transductionBiologyCell biology

Abstract

fetched live from OpenAlex

Abstract Osteosarcoma is the most common malignant bone tumor in the pediatric population, representing around 4 cases per million people per year in the world. Patient survival is closely related to the response of tumor cells to chemotherapy, reaching 70% at 5 years for patients with localized disease, but only 25% for high-risk patients with relapsed or metastatic disease. In 20% of cases, patients have detectable metastases at diagnosis, preferentially in the lungs, which is a sign of poor prognosis. However, it is estimated that around 80% of patients have pulmonary micrometastases, sometimes undetectable at diagnosis by imaging techniques. This makes metastatic dissemination a significant issue in the management of osteosarcoma. In addition, the survival rate has not evolved since the past decades and there is no current efficient therapy for these patients. Therefore, it is necessary to develop new therapeutic strategies. In this context, a dysregulation of the canonical Wnt signaling pathway (Wnt/β-catenin) has been reported in many osteosarcoma cases, but its implication in the development of primary and metastatic osteosarcoma is still controversial. An increase in β-catenin expression has been described in human osteosarcoma tissues compared to normal bones. Thus, we evaluated the antitumor potential of ICG-001, a small molecule that specifically binds to the transcriptional co-activator CREB-Binding Protein (CBP), disrupting its interaction with β-catenin and thus suppressing the Wnt/β-catenin target gene expression. First, we demonstrated that ICG-001 inhibits β-catenin/CBP-dependent transcription as evaluated by TCF-LEF reporter assay and RT-qPCR on β-catenin target genes in three human osteosarcoma cell lines, KHOS, MG63, and SJSA1. Moreover, ICG-001 decreases proliferation of osteosarcoma cells in a dose- and time-dependent manner, associated with a cell cycle blockade in G0/G1 phase after 24h of treatment, but without any effect on cell death. However, surprisingly, ICG-001 promotes KHOS, MG63, and SJSA1 cell migration in vitro and the development of pulmonary metastases in a murine xenograft model of osteosarcoma induced by injection of KHOS cells in a paratibial site. This study therefore raises new questions about the role of the Wnt/β-catenin pathway in the metastatic development of osteosarcoma. Thus, it is necessary to identify the different signatures of the signaling pathways potentially activated after disruption of the β-catenin and CBP interaction in osteosarcoma cells and responsible for the prometastatic effect of this drug. Citation Format: Geoffroy Danieau, Sarah Morice, Sarah Renault, Kevin Biteau, Régis Brion, Jérôme Amiaud, Frédéric Lezot, Franck Verrecchia, Françoise Rédini, Bénédicte Brounais-Le Royer. Prometastatic effect of ICG-001, a β-catenin/CBP dependent transcription inhibitor, in osteosarcoma [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr B26.

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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.057
GPT teacher head0.355
Teacher spread0.298 · 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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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