Frequently used antiemetic agent dexamethasone enhances the metastatic behaviour of select breast cancer cells
Bibliographic record
Abstract
Glucocorticoids, such as dexamethasone (Dex), are used to prevent common side effects induced by chemotherapy and are heavily prescribed for solid cancers such as breast cancer. There is substantial pre-clinical data to support that Dex activation of the glucocorticoid receptor overrides chemotherapy-induced apoptosis in breast cancer cell lines. These findings are compounded by a recent study demonstrating that increased glucocorticoid receptor activation by endogenous stress hormones increased breast cancer heterogeneity and metastasis. Our study is the first to use both in vitro and in vivo models to thoroughly compare the Dex response on the migration of multiple estrogen receptor negative (ER-) and ER+ cancer cell lines. ER+ and ER- breast cancer cell lines were studied to compare their endogenous glucocorticoid activity as well as their metastatic ability in response to Dex treatment. We show that in the ER- breast cancer lines, Dex increases cell numbers, invasiveness, and migration, while decreasing apoptotic ability. Furthermore, we show that following Dex treatment, ER- breast cancer lines migrate further in an in vivo zebrafish model in comparison to ER+ cell lines. The use of ROR1 antibody to block WNT signaling diminished the metastatic properties of ER- cells, however recombinant WNT5A alone was not sufficient to induce migration. Taken together, we demonstrate that Dex treatment exacerbates the metastatic potential of ER- but not ER+ cells. These findings add to the growing body of data stressing the potential adverse role of endogenous and synthetic glucocorticoids in breast cancer biology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".