Nuclear PRMT5 is a biomarker of sensitivity to tamoxifen in ERα+ breast cancer
Bibliographic record
Abstract
Endocrine therapies targeting estrogen signaling, such as tamoxifen, have significantly improved management of estrogen receptor alpha (ERα)-positive breast cancers. However, their efficacy is limited by intrinsic and acquired resistance to treatment, and there is currently no predictive marker of response to these anti-estrogens to guide treatment decision. Here, using two independent cohorts of breast cancer patients, we identified nuclear PRMT5 expression as an independent predictive marker of sensitivity to tamoxifen. Mechanistically, we discovered that tamoxifen stimulates ERα methylation by PRMT5, a key event for its binding to corepressors such as SMRT and HDAC1, participating in the inhibition of the transcriptional activity of ERα. Although PRMT5 is mainly localized in the cytoplasm of tumor cells, our analyses show that tamoxifen triggers its nuclear translocation in tamoxifen-sensitive tumors but not in resistant ones. Hence, we unveil a biomarker of sensitivity to tamoxifen in ERα-positive breast tumors that could be used to enhance the response of breast cancer patients to endocrine therapy, by fostering its nuclear expression.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".