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Record W2078893488 · doi:10.1158/1538-7445.am2012-825

Abstract 825: Wnt/beta-catenin signaling regulates the expression of O6-methylguanine DNA-methyltransferase in cancer cells: a new strategy to overcome resistance for DNA alkylators in cancer therapy

2012· article· en· W2078893488 on OpenAlexaff
Cecilia Dyberg, Ninib Baryawno, Jelena Milosevic, Malin Wickström, Baldur Sveinbjørnsson, Paul A. Northcott, Michael D. Taylor, Marcel Kool, Per Kogner, John Inge Johnsen

Bibliographic record

VenueCancer Research · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsWnt signaling pathwayCancer researchDNA methyltransferaseBiologyTemozolomideMethyltransferaseO-6-methylguanine-DNA methyltransferaseDNA repairGene knockdownMolecular biologyCancerCell cultureSignal transductionDNAGliomaCell biologyMethylationBiochemistryGenetics

Abstract

fetched live from OpenAlex

Abstract Background: A number of DNA-damaging agents attack the O6 position on guanine and thereby form the most potent cytotoxic DNA adducts known. The DNA-repair protein O6-alkylguanine (O6-AG) DNA alkyltransferase (AGT) encoded by the gene O6-Methylguanine (O6-MG)-DNA-methyltransferase (MGMT) repair DNA adducts caused by alkylating agents. MGMT has important implications in cancer treatment since its expression correlates inversely with sensitivity to agents that form O6-alkylguanine adducts, such as temozolamide. It is therefore of great interest to find agents that induce MGMT deficiency, increase the sensitivity and possible overcoming resistance to alkylating chemotherapeutic agents. Methods: Cell lines from medulloblastomas, gliomas, colon cancer and neuroblastomas were examined for Wnt/beta-catenin activity and MGMT expression. We used Western blot, Real-Time quantitative PCR (Q-PCR), siRNA knockdown and cDNA overexpression of beta-catenin, MGMT promotor reporter plasmids and cells with inducible siRNAs targeting beta-catenin to study beta-catenin mediated regulation of MGMT. The correlation between Wnt activity and MGMT expression was also investigated in primary medulloblastomas, gliomas and colon cancer using gene expression cohorts. Cell cytotoxicity and clonogenicity of chemotherapeutic drugs in combination with celecoxib were examined in cell lines using fluorometric microculture cytotoxicity assay and clonogenic assay, respectively. Compounds targeting Wnt signaling was investigated in combination with temolzolamide in vitro and in vivo. Results: MGMT expression level was shown be correlated to Wnt signaling activation both in primary tumors and cell lines of different origins. Proinflammatory prostaglandin E2 activates the Wnt/beta-catenin signaling and increase MGMT expression. Transfection experiments and cells with inducible siRNAs revealed that beta-catenin directly regulates MGMT expression via Tcf/LEF binding. Wnt inhibiting drugs and compounds potentiates the cytotoxic effect of the DNA alkylating drug, temozolomide in cells with elevated MGMT expression in vitro and in vivo. Conclusions: Our data demonstrate that MGMT is a direct Wnt/beta-catenin target, and agents that inhibit Wnt signalling reduces the transcription of MGMT through a prostaglandin E2-Wnt/beta-catenin route and thus increases the sensitivity to temozolomide. This provides a rational approach for improved efficacy of chemotherapeutic drugs inducing DNA alkylation in cancer treatment. The data also suggest that Wnt/beta-catenin is an important target for therapeutic interventions. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 825. doi:1538-7445.AM2012-825

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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.078
GPT teacher head0.395
Teacher spread0.317 · 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
Published2012
Admission routes1
Has abstractyes

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