ERα-36 regulates progesterone receptor activity in breast cancer
Bibliographic record
Abstract
BACKGROUND: Alterations in estrogen and progesterone signaling, via their respective receptors, estrogen receptor alpha (ERα) and progesterone receptor (PR), respectively, are largely involved in the development of breast cancer (BC). The recent identification of ERα-36, a splice variant of ERα, has uncovered a new facet of this pathology. Although ERα-36 expression is associated with poor prognosis, metastasis development, and resistance to treatment, its predictive value has so far not been associated with a BC subtype and its mechanisms of action remain understudied. METHODS: To study ERα-36 expression in BC specimens, we performed immunochemical experiments. Next, the role of ERα-36 in progesterone signaling was investigated by generating KO clones using the CRISPR/CAS9 technology. PR signaling was also assessed by proximity ligation assay, Western blotting, RT-QPCR, and ChIP experiments. Finally, proliferation assays were performed with the IncuCyte technology and migration experiments using scratch assays. RESULTS: Here, we demonstrate that ERα-36 expression at the plasma membrane is correlated with a reduced disease-free survival in a cohort of 160 BC patients, particularly in PR-positive tumors, suggesting a crosstalk between ERα-36 and PR. Indeed, we show that ERα-36 interacts constitutively with PR in the nucleus of tumor cells. Moreover, it regulates PR expression and phosphorylation on key residues, impacting the biological effects of progesterone. CONCLUSIONS: ERα-36 is thus a regulator of PR signaling, interfering with its transcriptional activity and progesterone-induced anti-proliferative effects as well as migratory capacity. Hence, ERα-36 may constitute a new prognostic marker as well as a potential target in PR-positive BC.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".