Antiprogestins reduce epigenetic field cancerization in breast tissue of young healthy women
Bibliographic record
Abstract
BACKGROUND: Breast cancer is a leading cause of death in premenopausal women. Progesterone drives expansion of luminal progenitor cells, leading to the development of poor-prognostic breast cancers. However, it is not known if antagonising progesterone can prevent breast cancers in humans. We suggest that targeting progesterone signalling could be a means of reducing features which are known to promote breast cancer formation. METHODS: In healthy premenopausal women with and without a BRCA mutation we studied (i) estrogen and progesterone levels in saliva over an entire menstrual cycle (n = 20); (ii) cancer-free normal breast-tissue from a control population who had no family or personal history of breast cancer and equivalently from BRCA1/2 mutation carriers (n = 28); triple negative breast cancer (TNBC) biopsies and healthy breast tissue taken from sites surrounding the TNBC in the same individuals (n = 14); and biopsies of ER+ve/PR+ve stage T1-T2 cancers and healthy breast tissue taken from sites surrounding the cancer in the same individuals (n = 31); and (iii) DNA methylation and DNA mutations in normal breast tissue (before and after treatment) from clinical trials that assessed the potential preventative effects of vitamins and antiprogestins (mifepristone and ulipristal acetate; n = 44). RESULTS: Daily levels of progesterone were higher throughout the menstrual cycle of BRCA1/2 mutation carriers, raising the prospect of targeting progesterone signalling as a means of cancer risk reduction in this population. Furthermore, breast field cancerization DNA methylation signatures reflective of (i) the mitotic age of normal breast epithelium and (ii) the proportion of luminal progenitor cells were increased in breast cancers, indicating that luminal progenitor cells with elevated replicative age are more prone to malignant transformation. The progesterone receptor antagonist mifepristone reduced both the mitotic age and the proportion of luminal progenitor cells in normal breast tissue of all control women and in 64% of BRCA1/2 mutation carriers. These findings were validated by an alternate progesterone receptor antagonist, ulipristal acetate, which yielded similar results. Importantly, mifepristone reduced both the TP53 mutation frequency as well as the number of TP53 mutations in mitotic-age-responders. CONCLUSIONS: These data support the potential usage of antiprogestins for primary prevention of poor-prognostic breast cancers. TRIAL REGISTRATION: Clinical trial 1 Mifepristone treatment prior to insertion of a levonorgestrel releasing intrauterine system for improved bleeding control - a randomized controlled trial, clinicaltrialsregister.eu, 2009-009014-40 ; registered on 20 July 2009. Clinical trial 2 The effect of a progesterone receptor modulator on breast tissue in women with BRCA1 and 2 mutations, clinicaltrials.gov, NCT01898312 ; registered on 07 May 2013. Clinical trial 3 A pilot prevention study of the effects of the anti- progestin Ulipristal Acetate (UA) on surrogate markers of breast cancer risk, clinicaltrialsregister.eu, 2015-001587-19 ; registered on 15 July 2015.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".