Abstract 1587: Breast cancer treatment: Exploring bazedoxifene, a known SERM, SERD and indirect STAT3 inhibitor
Bibliographic record
Abstract
Abstract In 2020, breast cancer was the most widespread cancer. This heterogenous disease can be divided into molecular subtypes according to three biomarkers: Estrogen Receptor (ER), Progesterone Receptor (PR) and Epidermal Growth Factor Receptor 2 (HER2). Currently, triple-negative breast cancers (TNBC), negative for all three biomarkers, have no personalized treatment. Also, about 40% of women with breast cancer receiving tamoxifen, a selective estrogen receptor modulator (SERM), have or will develop a resistance. Bazedoxifene (BZA), a SERM, a selective estrogen receptor modulator (SERD) and an indirect Signal transducer and activator of transcription 3 (STAT3) inhibitor, used for treatment of osteoporosis, has exhibited in vitro antitumoral effects. Therefore, BZA efficacy must be further evaluated. We hypothesize that BZA is a therapeutic option for hormone receptor (HR)-positive breast cancers and a novel anticancer agent for TNBC patients. To verify our hypothesis, we performed 2D viability assays on breast cancer cell lines treated with different BZA and hydroxytamoxifen (4OHT) concentrations to calculate the absolute half maximal inhibitory concentration (IC50). We then performed 3D viability assays, which is a first with BZA treatment. We further investigated gene expression of known STAT3 targets in breast cancer subtypes in UALCAN and on survival outcomes in PRECOG and ROCplot. The 72 hours BZA IC50 is respectively 8.038 ± 0.132 µM for TNBC basal-like 2 cell line (SUM149PT) and the 4OHT IC50 for this cell line is 6.095 ± 0.133 µM (p-value= 0.1). Despite IC50 seeming lower for 4OHT, the results are not significant when performing two sided Mann-Whitney. Similarly, for MDA-MB-231, another TNBC cell line, characterized as mesenchymal-like, BZA IC50 (7.988± 0.482 µM) seems higher but is not significantly different to the 4OHT IC50 (7.080± 0.167 µM) (p-value= 0.1). We also found that BZA IC50 and 4OHT IC50 for MCF7 (HR+) are not significantly different (p-value= 0.4). 3D viability assays performed on SUM149PT spheroids treated for 3 days with 2X and 5X BZA IC50 decreased cell viability whilst 2X 4OHT IC50 did not reduce cell viability. Lastly, we determined that BIRC5, a known inhibitor of apoptosis, is more expressed in TNBC patients from TCGA breast cancer cohort than other molecular subtypes, but patients diagnosed with luminal A breast cancer (HR+/HER2-) receiving chemotherapy and experiencing a recurrence have a higher median gene expression of BIRC5. In summary, we have shown that BZA seems less effective to reduce cell viability in 2D assays than 4OHT in TNBC cell line but may be more effective in 3D models. A decrease in phosphorylated STAT3 following BZA treatment could be beneficial to patients with luminal A breast cancer who are not responding to chemotherapy. Citation Format: Juliette Bherer, Alisson Clemenceau, Caroline Diorio, Francine Durocher. Breast cancer treatment: Exploring bazedoxifene, a known SERM, SERD and indirect STAT3 inhibitor [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1587.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".