Blockade of AP-1 Potentiates Endocrine Therapy and Overcomes Resistance
Bibliographic record
Abstract
UNLABELLED: The transcription factor AP-1 is downstream of growth factor (GF) receptors (GFRs) and stress-related kinases, both of which are implicated in breast cancer endocrine resistance. Previously, we have suggested that acquired endocrine resistance is associated with increased activity of AP-1 in an in vivo model. In this report, we provide direct evidence for the role of AP-1 in endocrine resistance. First, significant overlap was found between genes modulated in tamoxifen resistance and a gene signature associated with GF-induced estrogen receptor (ER) cistrome. Interestingly, these overlapping genes were enriched for key signaling components of GFRs and stress-related kinases and had AP-1 motifs in their promoters/enhancers. Second, to determine a more definitive role of AP-1 in endocrine resistance, AP-1 was inhibited using an inducible dominant-negative (DN) cJun expressed in MCF7 breast cancer cells in vitro and in vivo AP-1 blockade enhanced the antiproliferative effect of endocrine treatments in vitro, accelerated xenograft tumor response to tamoxifen and estrogen deprivation in vivo, promoted complete regression of tumors, and delayed the onset of tamoxifen resistance. Induction of DN-cJun after the development of tamoxifen resistance resulted in dramatic tumor shrinkage, accompanied by reduced proliferation and increased apoptosis. These data suggest that AP-1 is a key determinant of endocrine resistance by mediating a global shift in the ER transcriptional program. IMPLICATIONS: AP-1 represents a viable therapeutic target to overcome endocrine resistance. Mol Cancer Res; 14(5); 470-81. ©2016 AACR.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".