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Record W2134123270 · doi:10.1371/journal.pone.0013831

Breast Cancer Stem-Like Cells Are Inhibited by a Non-Toxic Aryl Hydrocarbon Receptor Agonist

2010· article· en· W2134123270 on OpenAlexafffund
Gérald J. Prud’homme, Yelena Glinka, Anna Toulina, Olga Ace, Venkateswaran Subramaniam, Serge Jothy

Bibliographic record

VenuePLoS ONE · 2010
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
FundersCanadian Institutes of Health ResearchCanadian Breast Cancer Research AllianceOntario Institute for Cancer Research
KeywordsCancer stem cellTranilastCancer researchAryl hydrocarbon receptorStem cellChemistryCD44BiologyPharmacologyCellCell biologyTranscription factorBiochemistry

Abstract

fetched live from OpenAlex

BACKGROUND: Cancer stem cells (CSCs) have increased resistance to cancer chemotherapy. They can be enriched as drug-surviving CSCs (D-CSCs) by growth with chemotherapeutic drugs, and/or by sorting of cells expressing CSC markers such as aldehyde dehydrogenase-1 (ALDH). CSCs form colonies in agar, mammospheres in low-adherence cultures, and tumors following xenotransplantation in Scid mice. We hypothesized that tranilast, a non-toxic orally active drug with anti-cancer activities, would inhibit breast CSCs. METHODOLOGY/FINDINGS: We examined breast cancer cell lines or D-CSCs generated by growth of these cells with mitoxantrone. Tranilast inhibited colony formation, mammosphere formation and stem cell marker expression. Mitoxantrone-selected cells were enriched for CSCs expressing stem cell markers ALDH, c-kit, Oct-4, and ABCG2, and efficient at forming mammospheres. Tranilast markedly inhibited mammosphere formation by D-CSCs and dissociated formed mammospheres, at pharmacologically relevant concentrations. It was effective against D-CSCs of both HER-2+ and triple-negative cell lines. Tranilast was also effective in vivo, since it prevented lung metastasis in mice injected i.v. with triple-negative (MDA-MB-231) mitoxantrone-selected cells. The molecular targets of tranilast in cancer have been unknown, but here we demonstrate it is an aryl hydrocarbon receptor (AHR) agonist and this plays a key role. AHR is a transcription factor activated by 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), polycyclic aromatic hydrocarbons and other ligands. Tranilast induced translocation of the AHR to the nucleus and stimulated CYP1A1 expression (a marker of AHR activation). It inhibited binding of the AHR to CDK4, which has been linked to cell-cycle arrest. D-CSCs expressed higher levels of the AHR than other cells. Knockdown of the AHR with siRNA, or blockade with an AHR antagonist, entirely abrogated the anti-proliferative and anti-mammosphere activity of tranilast. Thus, the anti-cancer effects of tranilast are AHR dependent. CONCLUSION/SIGNIFICANCE: We show that tranilast is an AHR agonist with inhibitory effects on breast CSCs. It is effective against CSCs of triple-negative breast cancer cells selected for anti-cancer drug resistance. These results suggest it might find applications in the treatment of breast cancer.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.016
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0020.000

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 head0.019
GPT teacher head0.227
Teacher spread0.208 · 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.

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

Citations141
Published2010
Admission routes2
Has abstractyes

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