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Abstract P1-12-14: Retinoic acid sensitizes triple-negative breast cancer cells to tamoxifen treatment

2015· article· en· W2251738513 on OpenAlexaff
Krysta M. Coyle, Cheryl A. Dean, Diana B. Jo, Margaret L. Thomas, Mohammad Sultan, Paola Marcato

Bibliographic record

VenueCancer Research · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinoids in leukemia and cellular processes
Canadian institutionsDalhousie University
Fundersnot available
KeywordsTamoxifenEstrogen receptorTriple-negative breast cancerBreast cancerInternal medicineEstrogenCancer researchEndocrinologyMedicineRetinoic acidCell growthCancerBiologyCell culture

Abstract

fetched live from OpenAlex

Abstract Tamoxifen, an estrogen receptor (ER) antagonist, is often used as an adjuvant endocrine therapy in the successful treatment of ER+ breast tumors. Tumors that lack ER, progesterone receptor (PR) and HER2 expression (i.e. triple-negative breast cancers) cannot be treated with adjuvant endocrine therapies, like tamoxifen, and are often more aggressive. Inducing ER expression is a potential strategy for sensitization of triple-negative breast cancers to adjuvant endocrine therapies. Given recent evidence suggesting cross-talk between the retinoic acid (RA) and estrogen signaling pathways, we investigated if RA induces expression of ER in triple-negative breast cancer cells. We hypothesize that this would lead to sensitization of the cells to tamoxifen treatment. Quantitative PCR of mRNA isolated from triple-negative MDA-MB-231 cells treated with RA and estradiol had increased ER transcript levels. Furthermore, treatment with estradiol and RA synergistically induced increased expression of RA-inducible genes. In cell proliferation studies, neither RA nor estradiol treatment alone significantly altered the growth of MDA-MB-231 cells; however, when treated with both estradiol and RA together, the growth of the cells increased significantly. This suggests that the RA-mediated increase in ER expression sensitizes MDA-MB-231 cells to estradiol-induced cell growth. Next, we investigated whether the increased ER expression sensitized MDA-MB-231 cells to tamoxifen treatment. Tamoxifen did not decrease the growth of MDA-MB-231 cells; however, when applied in combination with both estradiol and RA, tamoxifen significantly reduced MDA-MB-231 proliferation. Furthermore, tamoxifen treatment reduced the synergistic effects of estradiol/RA on RA-inducible gene expression. Together, these results suggest that the use of RA in combination with tamoxifen warrants further investigation as a potential treatment for triple-negative breast cancers. The success of the combination treatment of tamoxifen and RA in the reduction of triple-negative breast cancer cell tumor xenografts will provide further justification for this strategy in the treatment of triple-negative breast cancers. Citation Format: Krysta M Coyle, Cheryl A Dean, Diana B Jo, Margaret Thomas, Mohammad Sultan, Paola Marcato. Retinoic acid sensitizes triple-negative breast cancer cells to tamoxifen treatment [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P1-12-14.

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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)0.0000.000
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)0.0040.001

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 head0.062
GPT teacher head0.375
Teacher spread0.313 · 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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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