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NPJ Breast Cancer logoLink to NPJ Breast Cancer
. 2026 Jun 25;12:134. doi: 10.1038/s41523-026-00998-x

Individualised progesterone receptor modulator prevention strategies for triple-negative breast cancer in BRCA1 pathogenic variant carriers

Martin Widschwendter 1,2,3,4,5,6,✉, Rita Schmutzler 7, Nora Pashayan 8, Jelle Wesseling 9, Marc Tischkowitz 10, Michal Zikan 11, Miranda Steenbeek 12, Marike Gabrielson 13, Christian F Singer 14, Cathrin Brisken 15,16, Rebecca Gomperts 17, Sharon Cameron 18,19, Dafydd Gareth Evans 20, Andri Papakonstantinou 21,22, Marc Buyse 23, Kerstin Rhiem 7, Mateja Krajc 24, Charlotte Vavourakis 2,3, Elisa Redl 2,3, Chiara Herzog 2,3, James Barrett 2,3, Mohammed Fatih Rasul 6,25, Deborah Utjés 6, Kiriaki Papaikonomou 6, Angelique Flöter Rådestad 6,26, Athanasios Zouzos 27, Twana Alkasalias 6,28, Kristina Gemzell-Danielsson 6,29
PMCID: PMC13661513  PMID: 42350451

Abstract

Women with germline BRCA1 pathogenic variants face a very high risk of early-onset triple-negative breast cancer (TNBC), with risk-reducing mastectomy currently the only established preventive option. Emerging evidence suggests aberrant progesterone signalling contributes to TNBC risk, while preclinical studies indicate progesterone receptor modulators such as mifepristone may substantially reduce cancer development. DNA methylation-based markers reflecting field cancerization and replicative age could enable real-time monitoring of preventive efficacy and support an individualised primary prevention approach.

Subject terms: Cancer, Genetics, Oncology

Introduction

Breast cancer (BC) is the leading cause of cancer-related death among young women worldwide, and its prevalence is increasing1. Pathogenic variants (PVs) in the BRCA1 gene are responsible for approximately 1 to 3% of BCs globally, with 60 to 70% of these cancers being of basal cell origin and lacking expression of estrogen, progesterone, and HER2 receptors, making them triple negative breast cancers (TNBC)2. Among all BC subtypes, TNBC has the worst prognosis3 and treatment options remain limited due to the absence of therapeutic targets. BRCA1 PV carriers have a 40% lifetime risk for TNBC, compared to a 1% lifetime risk in women without PVs; notably, this risk rises sharply from 25–30 years onwards2. Additionally, BRCA1 PV carriers have a 45% lifetime risk of ovarian cancer (OC), compared to 1.8% risk for women without PVs and the risk starts to rise from the age of 35 onwards4.

Options for management of TNBC risk for BRCA1 PV carriers are rather scarce. Primary prevention strategies (aimed at preventing cancer development) are mostly limited to risk reducing bilateral mastectomy, which can lower BC risk by 90-95%5 and remains the gold standard for breast cancer prevention. However, the procedure shows only a tendency towards improved survival6, has a higher risk of failure in women who smoke or have a high body mass index (BMI), carries a risk of post-surgical complications, and has negative consequences on self-perception and physical and mental well-being. Risk reduction through selective estrogen receptor modulators (SERMs; e.g. tamoxifen and raloxifene) and aromatase inhibitors7,8 has shown efficacy in reducing estrogen receptor positive BC risk, but not mortality, and these drugs do not prevent TNBC.

Secondary prevention strategies (aimed at early cancer detection) are currently limited to enhanced imaging-based surveillance (i.e. mammograms and breast MRI) and these remain a core aspect of the follow-up management of BRCA1 PV carriers. Blood-based early detection strategies (e.g. detection of circulating tumor DNA) have not shown great promise so far due to limited sensitivity9,10.

Individual BC risk for BRCA1 PV carriers varies considerably, making risk stratification an important component of both primary and secondary prevention. These risks have been substantiated in recent years by comprehensive cohort studies. In particular, age-dependent prospective incidence rates have been empirically determined and allow age-dependent risk prediction11,12. This has significantly improved risk communication and informed decision-making on the uptake of preventive measures. CanRisk, an online tool based on personal, family and genetic risk factors, is now fully embedded in many cancer genetics services and implementation studies using CanRisk with other risk factors [i.e. polygenic risk score (PRS) and non-genetic risk factors] are underway in tertiary care (e.g. Precision HBOC, CanRisk-Clingen) and primary care (e.g. CanRisk-GP). Such comprehensive risk prediction has been shown to also modify individual breast cancer risk in BRCA1 PV carriers that might provide additional information for decision-making regarding prophylactic bilateral mastectomy13. Although mammographic density is a risk factor for BC, it is currently not well integrated into risk stratification, and – in particular for BRCA1 PV carriers – might be unsuitable due to lower mammographic density observed in TNBC14.

The unmet needs

The principles of P4 Medicine (Fig. 1) provide a structured approach to highlight the several unmet needs required to advance primary BC prevention in BRCA1 PV carriers.

  1. Prediction: Although the above-mentioned tools are available to refine BC risk, none of them indicate how this risk changes over time or can be influenced by interventions. BRCA1 is ubiquitously expressed and centrally involved in DNA repair, however, until recently, only cell-autonomous mechanisms (i.e. direct effects of the BRCA1 PV status in the cancer’s cell of origin such as reduced DNA repair in breast epithelial cells) were considered as pathogenic factors in BRCA1 PV carriers15. This is at odds with the observation that carcinogenesis is limited to tissues without particularly high cell turnover (i.e. breast and Fallopian Tube fimbriae epithelial cells); organs with a high cell turnover (e.g. intestine) and thereby a high demand for accurate DNA repair are not at risk. Evidence has now shown that cell non-autonomous factors play a central role and that their local effects might serve as ideal risk predictors.

  2. Prevention: Apart from surgical removal of the organs at risk, no primary preventive measures have been proven to reduce TNBC risk in BRCA1 PV carriers. Targeting cell non-autonomous factors could offer a promising alternative.

  3. Personalised: The lack of means by which to measure the effectiveness of a primary preventive intervention has resulted in therapeutic options being offered without personalisation regarding the modality, the dosage or duration. To gain sufficient coverage and willingness for primary prevention, personalised efficacy measurements are needed.

  4. Participatory: Clear communication, decision aids16, decision coaching and simplicity of risk assessment, preventive measures and monitoring are essential to ensure high uptake, long term engagement, adherence and commitment from the BRCA1 PV carrier.

Fig. 1. Principles of P4 Medicine applied to primary breast cancer prevention in BRCA1 pathogenic variant carriers.

Fig. 1

The image in the centre of the Figure has been obtained from Adobe Stock.

Progesterone – a key risk factor for TNBC

Elevated steroid hormone levels are one of the most striking recently discovered cell non-autonomous factors mediated by a pathogenic BRCA1 PV. These findings point to elevated progesterone levels during the luteal phase of the menstrual cycle17–20. Beside several other effects, progesterone stimulates Receptor Activator of Nuclear factor Kappa-B Ligand (RANKL) secretion21 in hormone-sensitive mature luminal cells, which triggers the proliferation of luminal progenitor (and basal) cells via a paracrine mechanism22–25. These estrogen- and progesterone-receptor-negative cells are the cells of origin for TNBC.

Additional evidence supporting progesterone as the most important steroid driving the formation of BCs with poor prognosis includes findings from the Women’s Health Initiative study26 where the combination of estrogen with medroxyprogesterone acetate for hormone replacement was associated with an increased BC risk, while estrogen alone was linked to a reduced risk. In addition, long-term use of oral contraceptive pills, mainly due to the progestin component27, increased the TNBC risk28. Higher parity, which corresponds to prolonged exposure to progesterone, was associated with higher TNBC risk among black women28. Most recent evidence further supports progesterone’s key role in the formation of TNBC also in young women: Estrogen plus progestin hormone therapy was associated with an increased incidence of young-onset breast cancer, with a particularly strong association observed for TNBC (HR 1.50; 95% CI, 1.02–2.20) whereas estrogen alone decreased the breast cancer risk significantly (HR 0.86; 95% CI 0.75–0.98)29.

The observation that risk-reducing bilateral salpingo-oophorectomy consistently reduces BC risk in BRCA1 PV carriers but has a less marked effect in BRCA2 PV carriers30,31, strongly supports the view that aberrant high progesterone levels in BRCA1 PV carriers play a central role in the development of TNBC.

In addition to the proliferative effects of progesterone on the cells of origin for TNBC (i.e. basal and luminal progenitor cells)24,25, progesterone may exert its pro-carcinogenic potential via the modulation of immune surveillance given that immune tolerance mechanisms are shared by both cancer and pregnancy. The progesterone induced expression of B7-H4 (VTCN1), an onco-fetal immune tolerance checkpoint, contributes to progesterone-induced BC progression via CD8 + T cell exhaustion32. Progesterone may also be involved in the development and progression of metastatic high-grade serous ovarian cancer33–35, at least in part via progesterone-mediated suppression of natural killer (NK) cell cytotoxicity at the Fallopian Tube fimbriae, which are exposed to ultra-high concentrations of progesterone due to their close proximity of the ovaries19.

Current modalities for assessing and monitoring TNBC risk

Primary cancer prevention implies that in the organ at risk (i.e. breast) there are neither macroscopic nor microscopic signs of cancer or pre-cancer. Significant amounts of research focus on the detection of the earliest signs of cancer, utilising circulating cells36,37 or circulating cell-products (e.g. cancer-specific altered DNA9,38–40, RNA41 or proteins42,43). However, none of these efforts have so far convincingly demonstrated a clinical benefit over existing imaging-based strategies, such as mammography or breast MRI. These imaging-based methods often lead to overdiagnosis44,45 and do not effectively detect TNBC and other BCs with poor prognosis, which have higher mortality rates compared to screen detectable cancers46,47.

PRS, which can be used to individualise BC risk prior to clinical manifestation, also have substantial limitations. A commonly used PRS, consisting of 313 common genetic variants preferentially predicts risk for estrogen-receptor positive BCs48. A new PRS, based on analysis of a more diverse cohort led by the US National Cancer Institute (Confluence), may help to overcome this issue49. PRS is being used in conjunction with other risk factors, such as age, to measure changing risk over time. Nevertheless, due to the nature of single nucleotide polymorphisms, a PRS per se cannot be used to monitor individual risk in response to an intervention.

Two parameters that directly assess breast tissue and may reflect cancer risk have gained some attention: (i) mammographic density is associated with BC risk, however, the association is weaker and has not been evaluated extensively in women 35 years of age or younger50. Mammographic density also depends on menstrual cycle51. Most importantly, women with TNBC tend to have lower mammographic density, less MRI-assessed fibroglandular tissue, and lower background parenchymal enhancement compared to non-TNBC14. Therefore, although suitable for monitoring risk modulation in older women on SERMs52,53, imaging-based risk monitoring in young BRCA1 PV carriers at risk for TNBC is unlikely to be safe and feasible. (ii) Ki67, a marker for cell proliferation, has been used to assess SERM efficacy54,55. However, Ki67 expression in normal breast tissue is weakly associated with BC risk56. Additionally, it provides only a snapshot of current proliferation in breast tissue, is dependent on the menstrual cycle, and is difficult to assess in small breast biopsies with limited numbers of epithelial cells, leading to limited interlaboratory reproducibility57.

Progesterone Receptor Modulators for prevention

Progesterone Receptor Modulators (PRMs; also called antiprogestins), such as mifepristone, play a pivotal role in reproductive health through their effects on the cervix and uterus58. PRMs have also demonstrated effects on breast epithelial cell proliferation20,59–61 and show BC preventive effects in mice61,62.

PRMs are currently in use for emergency-63 or on-demand contraception and are well-established for use in medical abortion64–66. Their efficacy for treating symptoms related to uterine fibroids67 and other reproductive health conditions68 was demonstrated many years ago. When administered at appropriate dosages and suitable delivery methods, PRMs like mifepristone offer a woman-centred contraceptive option with additional health benefits, supporting autonomy, while offering added non-contraceptive health benefits. Based on existing data, long-term treatment with mifepristone has found to be safe69,70 and is undergoing further exploration71.

One particular aspect of safety relates to the endometrium. PRMs have previously been observed to impact the endometrium but effects differ across PRM type, dose, timing of administration within the menstrual cycle, duration, and possibly also ethnicity72. Most of the evidence has been generated for mifepristone with less evidence for the other PRMs such as ulipristal acetate (UPA; now discontinued as a treatment for fibroids) and others that were under clinical development. Follicular phase administration has little effect on the endometrium, but depending on the dose used ovulation may be delayed or inhibited. Continuous administration of PRMs in low doses that do not affect ovulation can induce endometrial effects that are potentially contraceptive73. Prolonged use of doses that inhibit ovulation has led to concerns about endometrial hyperplasia due to unopposed estrogen. However, the endometrial changes that occur are a distinct histological entity known as PR modulator-associated endometrial changes (PAEC)74. Specifically, PAEC reveals an antiproliferative state and the endometrial glandular epithelium shows reduced mitotic activity compared to the proliferative phase although extensive cystic glandular dilatation is seen. Evidence indicates that PAEC regresses upon cessation of treatment75. Recent evidence demonstrates that three months of mifepristone exposure does not induce molecular changes associated with endometrial carcinogenesis76.

A summary of current indications and potential side effects of mifepristone are displayed in Table 1.

Table 1.

Side effects of mifepristone in studies for a range of indications

Indication Treatment dose, duration Potential adverse effects Endometrium Liver function Refs
Contraception 2–200 mg daily/weekly/ monthly, up to 12 months Nausea, breast distention, pelvic/abdominal pain, bloating and headache, have been reported (at doses of 10–50 mg weekly). PAEC (5 mg daily use for 6 months)126. Isolated reports of elevated transaminases127,128, returned to normal within two months. 126–135
Emergency contraception Single dose 10–50 mg Nausea, vomiting. N/A 58,136
Uterine fibroiids 2.5–50 mg daily or every other day, for 3–12 months Headache, nausea, vomiting, mood swings, diarrhea, decreased libido, weakness, fatigue, hot flashes, nervousness. Endometrial hyperplasia, PAEC (dilated cystic glandular formations). No atypia or malignancy. Isolated reports of elevated transaminases. 137
Endometriosis 5–100 mg daily for 3–6 months Nausea, vomiting, fatigue, hot flashes. PAEC. Isolated reports of elevated transaminases. 137
Obstetrics: Cervical ripening at term, induction of labor, delivery of still birth

Single dose 50–200 mg

(recommended dose)

Hypoglycemia in newborn. N/A 138,139
Induced abortion, management of missed miscarriage, cervical pretreatment before surgical abortion Single dose 200–600 mg (recommended dose) Urticarial skin rash, self-resolving. N/A 140–143
Meningioma 200 mg daily for prolonged use (recommended dose) Fatigue, hot flashes, breast tenderness, nausea, mood swings, rash, partial alopecia, edema and biochemical hypothyroidism. Endometrial hyperplasia (no atypia). Not affected (evaluated in few studies). 144
Cushing syndrome

300–1200 mg

daily for prolonged use

(recommended dose)

Hyper/hypokalemia, hyper/hypotension, hyponatremia, low cortisol levels, mineralocorticoid deficiency, maculopapular rash (in patients with hypercortisolism), edema, hyper/hypoglycemia, nausea/vomiting, headache, fatigue, secondary hypothyroidism. Endometrial hyperplasia (no atypia). Three reported cases of drug-induced liver injury (cholestatic liver injury) in patients with Cushing145. 137,144

PAEC PR modulator-associated endometrial changes; N/A not available

Accumulating evidence suggests that PRMs can prevent breast cancers, including poor prognostic TNBCs.

Although UPA is also highly effective60,77, its association with liver injuries78 precludes its use for BC risk reduction.

A downstream effector of progesterone – RANKL – can be targeted with antibodies such as denosumab (Amgen), which is in clinical use to treat bone loss79. Unlike mifepristone68, denosumab is not known to be lipophilic and, hence, would not be enriched in the fat-containing breast tissue. Targeting RANKL has been shown to prevent mammary gland cancer in mice22,80 but has no effect on contralateral breast cancer risk in postmenopausal BC patients81. The BRCA-P study is currently evaluating the BC risk reducing effect of denosumab in women carrying a germline BRCA1 pathogenic variant (EudraCT 2017-002505-35 and NCT04711109). The acceptance rate is, however, considerably impaired by potential participants’ wishes to become pregnant and the fear of side effects.

Compared with denosumab, mifepristone has several features that may make it considerably more acceptable to young BRCA1 PV carriers in the context of a prevention trial. First, mifepristone is taken orally at home and does not require clinic-based injections, conferring a meaningful practical advantage over denosumab (given as a subcutaneous injection every six months) that is likely to improve both recruitment and long-term adherence. Second, because low-dose mifepristone has well-documented contraceptive efficacy, it could simultaneously serve as the required contraception during the trial period - a prerequisite in any prevention trial involving reproductive-age women - thereby reducing the perceived burden of participation compared to alternative prevention drugs, which necessitates separate contraception. Third, unlike denosumab, mifepristone is anticipated to reduce the risk of both breast cancer and ovarian cancer in BRCA1 PV carriers, given accumulating evidence that elevated or heightened progesterone responsiveness contributes to ovarian cancer risk in this population33–35. The prospect of a single oral agent that may simultaneously lower risk across both organs is a compelling patient-relevant argument that denosumab cannot offer. Fourth, short-term hormonal modulation with mifepristone has recently been shown not to induce oncogenic endometrial changes in BRCA1/2 PV carriers76, providing direct reassurance about safety in this specific population.

The role of the epigenome in assessing and monitoring TNBC risk

The role of the epigenome in cancer development

Historically, cancer was considered a purely genetic disease, with the presence of somatic structural DNA alterations considered nearly conclusive evidence for the presence of a cancer82. It is now clear that DNA mutations including pathogenic driver mutations are present in normal tissues and are particularly evident in hormone-sensitive tissues like the endometrium83,84 and breast85, even at a very young age. Cancers can develop in the absence of DNA mutations, purely triggered by epigenetic alterations86 and epigenetic modifiers like those suppressing the activity of the polycomb repressor complex 2 component EZH2 frequently drive cancer formation87. Indeed, DNA methylation (DNAme) at promoter regions occupied by the polycomb repressor complex 2, belonging to the so called polycomb group target genes (PCGTs), is one of the most prevalent findings across all cancer entities88–90. Together data indicating that PCGT gene expression is essential for cellular differentiation91 and that methylation of promoter CpG islands leads to an almost irreversible gene suppression92, suggest DNAme at PCGT gene promoters is an essential factor in cancer development as it locks stem/progenitor cells in an undifferentiated state93.

The most unifying model of cancer development available today is that both exogenous factors and factors triggered by genetic predispositions drive the division of epithelial (stem/progenitor) cells and thereby increase cancer risk. For BC, exogenous factors include progesterone-containing hormone therapy26, which is associated with development of BCs with poor prognoses. Importantly, known genetic risk factors indirectly influence exposure to factors driving proliferation in specific at-risk cells. BRCA1 deletion in granulosa cells in mice94–96 and BRCA1 pathogenic variants in humans alter hormone levels (notably elevating luteal phase progesterone)17,18,20, immune function19 and microbiome composition97. These exogenous and genetically-triggered factors collectively promote proliferation of certain cell types and may ultimately lead to cancer formation21,98. They are integrated at the level of the epigenome, where integration depends on individual genotypes (i.e. single nucleotide polymorphisms; SNPs) which impact on DNAme patterns (i.e. methylation quantitative trait loci; meQTLs) in a cell-type-specific manner99. Most importantly, the epigenome is dynamic and malleable over time20,93,100.

Monitoring cancer field defects

Tumors arise from a field of molecularly altered epithelial cells of a specific type – a “field defect” comprising DNAme and somatic DNA mutation – that creates a permissive environment for malignant evolution. Field defects mostly occur without visible, morphological changes. Quantifying and monitoring cancer risk could be achieved through identification of these field defects.

Field defects for cervical, ovarian, breast and lung cancers have been identified. Cervical cancer field cancerization has been studied most extensively due to accessible at-risk tissue prior to disease onset, allowing prediction of (pre)cancer development years in advance through DNAme- tests101–103. Most recently, DNAme markers assessed in samples with normal cytology were shown to predict 80% of invasive cervical cancers within six years following sample collection102.

Breast field cancerization has also been described: expression of the retinoic acid receptor beta (RAR-β) was absent in normal adjacent breast tissue104 due to DNAme of the RARB gene105,106. A large component of field cancerization is a consequence of stem/progenitor cell proliferation triggered by certain conditions17,20,21 which drive the accumulation of DNAme at PCGTs88,91. A DNAme-based mitotic clock, which reflects replicative age by focusing on promoter CpG sites that localize to PCGTs and are unmethylated in 11 different foetal tissue types, is universally accelerated in cancer, including pre-cancerous lesions (both of the breast and lung), and is also accelerated in normal breast tissue adjacent to cancers20,107,108. Importantly, this process appears to be reversible up to a certain stage, by removing the primary proliferative stimulus (e.g. with PRMs)20.

An example of field cancerization is illustrated in Fig. 220: high progesterone levels from combined hormone therapy26 or a BRCA1 germline PV17,18,20 trigger progesterone-receptor positive luminal mature cells to release RANKL and other factors that, in a paracrine fashion, activate the proliferation of estrogen- and progesterone-receptor negative luminal progenitor cells eventually leading to formation of TNBC21,22,25,80,109. Mechanisms to reduce the luminal progenitor cell population are not yet fully established, but treatment with PRMs may exert a direct effect20 and an indirect effect by enhancing NK cell cytotoxicity19.

Fig. 2. Illustration of field cancerization.

Fig. 2

Progesterone triggers (i) the release of RANKL (Receptor Activator of Nuclear Factor Kappa-B Ligand) in hormone receptor (HR)-positive mature luminal cells leading to increased proliferation and thus accelerated mitotic ageing in HR-negative luminal progenitor cells (this process is marked by increasing DNA methylation at polycomb repressor complex 2 target sites; indicated by blue lines in the luminal cell nuclei); and (ii) a reduction in immune-surveillance32. Both effects result in increased cancer risk. This risk is further enhanced by other cell-autonomous (compromised DNA repair) and non-cell-autonomous factors20. The risk state for individual cells increases from green to yellow to orange to red.

Cancer risk signatures in epithelial cells

As discussed above, DNAme signatures in normal epithelial at-risk tissue are indicative of cancer field defects and are associated with the development of cervical102,103, breast20,110–112, ovarian113,114 and endometrial115 cancers. Breast cancer field defects can be assessed in fine needle aspirates (FNA). These field defects can also be identified in easy-to-access epithelial surrogate tissues which have similar features to the epithelial cells from which the actual cancer is derived. These features could include cell-type (i.e. epithelial), embryological origin and hormone sensitivity. Epithelial cells from the cervix or buccal mucosa (inner cheek) are therefore relevant surrogate tissues in the case of breast cancer.

Utilizing DNAme signatures, there is evidence that the field defects can be identified in cervicovaginal and buccal samples, making them suitable for assessing risk for breast116,117, ovarian118, endometrial119 and lung cancers120. For example, the WID-BC, a BC risk test based on DNAme markers measured in cervicovaginal samples116 had an AUC of 0.81 (95% CI: 0.76–0.86) in an independent external validation dataset with 113 cases and 225 controls. In comparison, the PRS313121, analysed in 314 cases and 816 controls, had an AUC of 0.67 (95% CI: 0.64–0.71). Preliminary evidence suggests that the WID-BC can predict BC development up to 5 years before diagnosis116.

Monitoring cancer risk with malleable markers

Small proof of principle studies have demonstrated that the disease-associated DNAme signatures can change dynamically due to specific interventions such as exposure to PRMs20 or smoking cessation120. Data from a window trial shows that mifepristone reduces both (i) DNAme markers reflective of stem/progenitor cells’ replicative age as well as (ii) the proportion of luminal progenitor and basal cells in normal breast tissue of healthy women without a BRCA1/2 PV and in a proportion of BRCA1/2 PV carriers20. These DNAme markers are higher in normal breast tissue adjacent to TNBC compared to normal breast tissue from age-matched cancer-free women and increase in almost all TNBCs when compared to normal adjacent tissue indicating that these markers are good intermediate surrogate markers. Whether risk indicating DNAme signatures measured in an epithelial surrogate sample, such as the WID-BC test, reflect the efficacy of mifepristone in reducing cancer risk over time has not yet been studied.

Serial breast biopsies are not standard of care and are not a practical solution for biomarker monitoring in a prevention trial. Circulating tumour-derived nucleic acids - whether cell-free DNA (cfDNA) or microRNAs - depend critically on shedding from (pre-)malignant cells and are inherently insensitive in a true primary prevention context where no tumour has yet formed. Fine needle aspiration (FNA) of the breast, whilst less invasive than a core biopsy, requires a clinic visit and trained personnel and is not yet standard of care in asymptomatic BRCA1 PV carriers. Accessible epithelial surrogate tissues - cervicovaginal and buccal cells - share cell type, embryological origin, and hormone sensitivity with breast epithelium and can be obtained through simple non-invasive self-sampling at home. The WID-BC test, a DNAme signature measured in cervicovaginal samples, achieved an AUC of 0.81 in independent external validation and can predict breast cancer development up to five years before diagnosis116. Proof-of-principle from a mouse model demonstrates that mifepristone-induced DNAme changes in the cervix parallel the reduction in mammary tumour incidence62, directly validating the surrogate tissue approach as a pharmacodynamic readout. We therefore propose the following hierarchy of biomarker approaches for a mifepristone prevention trial in BRCA1 PV carriers: (i) cervicovaginal and/or buccal DNAme signatures as the primary non-invasive endpoint; (ii) breast FNA-derived DNAme in a subset of willing participants to validate surrogate tissue signals against tissue-of-origin; and (iii) circulating liquid biopsy approaches (cfDNA methylation, miRNA panels) as exploratory endpoints, acknowledging their current sensitivity limitations in a prevention setting.

Recent findings from a mouse model using medroxyprogesterone acetate and 7,12-dimethylbenzanthracene to induce mammary tumours provide compelling evidence that epigenetic signatures can reflect cancer risk and serve as surrogate markers for monitoring preventive interventions. Treatment with mifepristone reduced mammary cancer incidence by more than 50%, a reduction that was paralleled by decreased epigenetic alterations both in the tissue at risk (normal mammary gland, indicating field cancerization) and in distant, non-target tissues such as the cervix, indicative of field defect62. These results strongly support the continued investigation of epigenetic biomarkers in accessible tissues to monitor the efficacy of cancer prevention strategies – particular of mifepristone - in humans.

The vision: personalised TNBC prevention in BRCA1 PV carriers

Our vision for personalised TNBC prevention includes predicting TNBC-risk in real time through the analysis of DNAme signatures in breast tissue (obtained through biopsy or more fine-needle aspiration which is more acceptable) or, eventually, in a more easily accessible epithelial surrogate sample. These markers would enable the ongoing assessment of primary prevention efficacy, for example, with mifepristone. They would also allow for personalised adjustments, such as changes in dosage, frequency or even medication choice which in addition to mifepristone includes drugs which have shown potential for breast cancer prevention (e.g. selective estrogen receptor modulators or thiazolidinediones122 or which are specifically active in BRCA1 PV carriers (e.g. PARP inhibitors)123. Engagement with the patient community and integration of the aspects that matter most to them into the final solution, around risk communication and ease/invasiveness of sample collection and drug administration, would enhance the participatory nature of these endeavours (Fig. 3).

Fig. 3. Approach to TNBC prevention in BRCA1 PV carriers using the PRM mifepristone and potential complementary approaches alongside real-time risk assessment.

Fig. 3

The blue bars in the centre of the cells reflect DNA methylation as a reflection of replicative age (the higher the number of blue bars, i.e. DNA methylation at PCGTs, the higher the replicative age of these cells). The risk state for individual cells increases from green to yellow to orange to red. A Scenario illustrating gradual development of mifepristone resistance where additional preventive treatments could temporarily offset resistance and sustain preventive efficacy; B Scenario showing sustained and high mifepristone sensitivity, where primary prevention remains effective without the need for complementary therapies.

Trial design and challenges

Figure 4 shows the proposed design for a definitive study aimed at testing a personalised primary TNBC prevention approach in BRCA1 PV carriers.

Fig. 4. Proposed trials design.

Fig. 4

Proposed design for a trial assessing a personalised primary prevention approach utilising the progesterone receptor modulator mifepristone.

Detailed discussions around the clinical trial design, including randomisation, control groups, statistics, inclusion/exclusion criteria, contraception, early BC detection, and risk communication during the trial, and more, are needed. In addition, a critical question is which intermediate surrogate markers reflective of the real time risk should be implemented and, most importantly, how these should be validated before inclusion in a clinical trial. The general criteria for such markers are as follows:

  • (i)

    They should demonstrate a gradual increase with increasing risk across a range of age and disease statuses, as measured in normal breast tissue, normal breast tissue adjacent to cancer, and cancer tissue. We note that the lack of longitudinal, population-based collection of normal breast tissue limits the scope of specific assessment and validation possible.

  • (ii)

    They must clearly indicate either a positive or negative response to an intervention.

Consensus from the scientific and regulatory communities on the extent of evidence supporting a biomarker’s effectiveness would be needed before embarking on a prevention study.

In light of the accrual challenges experienced by the BRCA-P trial and the current state of evidence for mifepristone in breast cancer prevention, a randomised phase IIB proof-of-concept trial with a short-term biomarker endpoint is a more immediately feasible first step than a large-scale randomised controlled trial (RCT) powered for TNBC incidence. Such a phase IIB trial would serve to assess drug acceptability, safety, and preliminary pharmacodynamic response, and could inform the design of a subsequent definitive prevention trial. The duration of drug intervention in such a trial would ideally be biomarker-guided - adapted in response to the individual’s risk trajectory as measured by intermediate surrogate markers - rather than fixed at a predetermined timepoint.

An important consideration in selecting the biomarker endpoint for such a phase IIB trial is its biological relevance to the specific cancer subtype at risk. Background parenchymal enhancement (BPE) on breast MRI has been proposed as a potential short-term endpoint given that annual breast MRI is standard of care in BRCA1 PV carriers. However, a recently published large pooled analysis of the Breast Cancer Association Consortium (BCAC) demonstrated that mammographic density (percentage density) shows a markedly attenuated - effectively null - association with breast cancer risk specifically in BRCA1 PV carriers (OR per SD: 1.02, 95% CI 0.78–1.34), in contrast to BRCA2 carriers (OR per SD: 1.55, 95% CI 1.08–2.24), and attributes this finding to the predominance of the triple-negative subtype in BRCA1-associated cancers124. Because BPE and mammographic density are inter-related imaging surrogates of fibroglandular tissue, and because women with TNBC characteristically have lower BPE and mammographic density compared to women with non-TNBC, BPE is likely to be insensitive - or even directionally misleading - as a pharmacodynamic endpoint for monitoring TNBC risk reduction in BRCA1 PV carriers. For this reason, DNA methylation (DNAme)-based biomarkers in accessible surrogate tissues (see below) are preferred as intermediate endpoints in this population.

Challenges of mifepristone

Due to fact that mifepristone has been shown to have an acceptable safety profile without liver toxicity, it is the most suitable PRM for consideration in the context a future breast cancer prevention trial.

Despite evidence from mouse models and a very limited number of window trials, the evaluation of mifepristone20,59 for breast cancer prevention has not been extensive. Data generated with mifepristone are supported with trials using other PRMs such as ulipristal acetate20,60. Large-scale evidence from adjuvant trials similar to that which exists for SERMs – agents that are central components of adjuvant breast cancer treatment – are unlikely to become available for PRMs. Data from ongoing contraceptive trials with mifepristone add to its long-term safety profiles71.

Evaluation of mifepristone’s effectiveness could start within the context of a randomised clinical trial amongst very high-risk women. To walk towards this already challenging starting point, additional hurdles have to be overcome. Chiefly, these revolve around the negative political and cultural perceptions of mifepristone, which is primarily known as an abortion drug, and the limited access to it in countries where abortion laws are restrictive. Additionally, funding and regulatory challenges exist. The interest from the pharmaceutical industry is low, in part because of the association of mifepristone with abortion, but also because mifepristone is off-patent and prevention trials can be multi-national, long and expensive. Who will fund such a trial in the absence of pharma interest? Consensus from regulators on the design of clinical trials, and the biomarkers used within them, would also be needed to ensure results can be used to support implementation.

Nevertheless, when compared with denosumab (the agent being tested in the BRCA-P trial), mifepristone has several important potential advantages for acceptability and feasibility. These are elaborated in the context of a possible stepwise trial approach described in the previous section.

An additional topic requiring clarification is which drugs, when applied at low doses for short periods, could affect mifepristone-resistant cells (see Fig. 3 panel A). Several options exist and could potentially be applied in the same trial. These include intermittent fasting, a ketogenic diet/supplement (unpublished data), PARP inhibitors, which have particularly high antineoplastic activity in BRCA1 PV carriers compared to non-carriers125, and – still very speculatively – thiazolidinediones, which may help prevent breast cancer by activating PPARγ, which reduces cell proliferation, promotes cellular differentiation, and improves insulin and inflammatory signalling pathways122. The effectiveness of these approaches, particularly if applied in combination, will need to be considered.

New, personalised approaches to primary breast cancer prevention are urgently needed and could be developed by building on the last 15 years of research into the pathogenesis of TNBC in BRCA1 PV carriers and methods to monitor risk. However, a community effort is needed to reach this goal of a new personalised cancer prevention approach. A consensus workshop, held in Innsbruck in September 2024, began this community effort. This group – the International Mifepristone Breast Cancer Prevention (IMBCP) Group – will now broaden its reach and continue to work towards ensuring that the necessary discussions take place, ultimately bringing about tangible change for women at the highest risk.Table 2

Table 2.

The role of progesterone receptor modulators in breast cancer prevention

Study Preventive effects Type of PRM Type of study Methodology Main Findings Ref
Barrett et al., 2025 Yes Mifepristone Mouse model

Medroxyprogesterone acetate and 7,12-dimethylbenzanthracene was used to

induce mammary gland cancers in mice

Mifepristone reduced mammary gland cancers by >50% 62
Lee et al., 2023 Likely Onapristone and ulipristal acetate Tamoxifen-insensitive mouse model Genetically modified C3(1)-TAg mice, which develop aggressive ER+ mammary tumors, were used to evaluate Z-endoxifen (5 mg/kg/day) as monotherapy and combined with selective progesterone receptor modulators ulipristal acetate (16.7 mg/kg/day) or onapristone (20 mg/kg/day). (n  = 10–12 mice per group). Ulipristal acetate (81 mg/day) significantly delayed tumor onset (p = 0.03; latency 114 days, p = 0.005), but did not reduce tumor growth or multiplicity; Onapristone (98 mg/day) showed no preventive effect. 146
Ranjan et al., 2021 Yes Mifepristone and telapristone Mouse Ovariectomized mice were randomized into four groups (9 mice/group): sham, estrogen (0.3 mg) and progesterone (30 mg), estrogen and progesterone with telapristone (30 mg), and estrogen and progesterone with mifepristone (30 mg). After 14 days of treatment, mammary glands were collected for RNA sequencing and splicing analysis.

Estrogen and progesterone significantly increased MSC and luminal mature fractions and reduced luminal progenitor cells in breast. Moreover, they strongly activate Wnt signaling, most prominently in MSC.

Progesterone receptor antagonists reversed progesterone driven tumorigenic effects in mammary cells.

147
Lee et al., 2021 Yes Telapristone acetate, ulipristal acetate, and mifepristone BRCA1 knockout mouse model Mice were treated with (30 mg/90 days) of mifepristone (n = 13), telapristone acetate (n = 10), or ulipristal acetate (n = 6) via subcutaneous pellets. The control group had 28 mice, Tumorigenesis was monitored, and histological analysis was performed at euthanasia. RNA was extracted from benign mammary glands for sequencing and gene expression analysis.

Ulipristal acetate significantly reduced tumor development (p = 0.04), achieving a 37% reduction in adenocarcinoma compared with an 18% reduction by Telapristone and no effect by mifepristone.

Ulipristal acetate delayed tumor onset by >2 months

148
Lee et al., 2016 Yes Telapristone acetate Rat/mouse Mice (n = 10–11) were treated with subcutaneous medroxyprogesterone acetate(MPA) (25 mg/pellet) alone or with telapristone acetate (25 mg/pellet), followed by weekly gavage of DMBA (1 mg) for 4 weeks. In the rat model (n = 10–11), a single injection of MNU (50 mg/kg) was followed by implantation of medroxyprogesterone acetate (MPA), progesterone, or telapristone acetate (identical doses to the mice study). Tumor formation and histology were assessed at study termination (65 days).

In mouse, Telapristone acetate opposed the pro-hyperplastic effects of MPA (p = 0.002)

In a rat mammary carcinogenesis model induced by MNU, MPA and progesterone increased tumor incidence and tumor burden compared with controls.

Telapristone acetate significantly reduced tumor incidence when combined with MPA (p = 0.037) or progesterone (p = 0.032).

The lowest tumor incidence (36%) was observed in rats treated with progesterone plus Telapristone acetate.

Tumor burden was significantly reduced by Telapristone acetate in combination with progesterone compared with progesterone alone (p = 0.042).

149
Communal et al., 2016 Yes Ulipristal acetate Mouse xenograft model Breast tissue from 6 control and 5 BRCA1 PV carriers was xenografted into 4-week-old ovariectomized mice. Treatments included control, estradiol (1.5 mg/pellet), estradiol + progesterone (25 mg/pellet), or estradiol + progesterone + ulipristal acetate (30 mg/pellet) (n = 4 mice/group). Mice were sacrificed after 28 days for analysis. Ulipristal acetate inhibited progesterone driven proliferation in BRCA1 PV breast tissue. 150
Communal et al., 2012 Unclear Ulipristal acetate In vitro (Human) and xenograft athymic mouse model

Normal human breast epithelial were

xenografted in athymic mice (n = 4) treated with 20 mg UPA per pellet for 28 days.

Ulipristal acetate had no effect on the mitotic index of xenografted human breast tissue exposed to gonadal hormones at levels similar to those in normal women.

In vitro findings indicated that Ulipristal acetate reduced the proliferation of normal breast cells but promoted growth in breast cancer cells.

151
Wiehle et al., 2011 Yes Telapristone acetate Rat Rats at the age of 50 days were injected with N-methyl-N-nitrosourea to initiate mammary carcinogenesis, and 6 days later, Telapristone acetate (CDB-4124) pellets (30.0 and 3.0 mg/pellet) were implanted subcutaneously for a duration of 3 months. (n = 16 to 20 rats/group)

Telapristone acetate (CDB-4124) demonstrated strong chemopreventive efficacy in rat mammary cancer models, with the following outcomes:

- Increased tumor latency from (66 ± 24 to 87 ± 20 days) (P < 0.02)

- Reduced tumor incidence from 85% → 35% (P < 0.001)

- Decreased tumor multiplicity by from 3.0 → 1.1 tumors/animal (P < 0.001)

- Lowered tumor burden from (2.6 → 0.26 g/animal)

- Prevented spontaneous premalignant lesions at 200 mg/kg over 24 months

152
Gonzalez-Suarez et al., 2010 Yes Mifepristone Mouse Mice were treated with 10 mg/kg muRANK-muFc, PBS, or zoledronic acid. Tumor growth was monitored by palpation, and mice were euthanized when tumors exceeded a certain size. Proliferation assays were conducted using BrdU, and progesterone and mifepristone (10 mg/kg) were administered to examine hormonal effects. (n = 24-32). Mifepristone reduced 98% of progesterone-induced proliferation (P < 0.001 versus control) whereas RANK-Fc reduced proliferation by 82% (P < 0.001 versus control). 22
Kariagina et al., 2010 Yes Mifepristone Organoid T47D-Y, T47D-YA, and T47D-YB cells were cultured in serum-free media, treated with R5020 (20 nM) ± Iressa (500 nM) or mifepristone (100 nM) for 24 hours, followed by 25 nM Areg for 30 minutes.

Estrogen and progesterone act synergistically to drive mammary epithelial proliferation, with combined estrogen and progesterone treatment inducing robust proliferation in ducts (24%) and lobules (39%), compared with minimal effects of estrogen alone (3-4%) and no effect of progesterone alone.

In primary mammary organoids, Mifepristone significantly reduced the proliferative effect of Areg + progesterone, indicating that active progesterone receptor signalling is required for hormone-induced epithelial growth

Mifepristone reduced the proportion of S-phase cells back to basal levels, confirming suppression of cell-cycle progression.

153
Lim et al., 2009 No Mifepristone and onapristone In vitro Mammary epithelial subsets from human tissue, including BRCA1 PV carriers, were analyzed using flow cytometry. Cells were cultured in Matrigel with supplemented medium, including mifepristone or onapristone. The clonogenic activity of luminal progenitor cells from BRCA1 PV carriers was not inhibited by mifepristone or onapristone despite higher progesterone receptor expression in these cells. 154
Poole et al., 2006 Yes Mifepristone Brca1/p53-deficient mouse model Mice were implanted with a pellet containing 35 mg/60-day constant-release mifepristone (n = 14) or a placebo pellet (n = 4). The study assessed the impact of mifepristone on tumor development and the role of BRCA1 in regulating progesterone receptors.

Mifepristone prevented mammary tumorigenesis in Brca1/p53-deficient mice, with no palpable tumors detected up to 12 months of age in treated animals (n = 14), compared with 100% tumor penetrance and a median tumor latency of 6.6 months in control mice (n = 25).

Mifepristone significantly reduced ductal branching and alveologenesis

61
Li et al., 1995 Yes PRM ZK114043 Mouse Whole organ cultures of mammary glands from estradiol/progesterone-primed virgin mice maintained in a serum-free medium with aldosterone, prolactin, insulin, and hydrocortisone. The cultures were treated with the PRM ZK114043 (5 ng/ml) for 4 days.

ZK114043 promoted differentiation in mammary cells.

ZK114043 showed potent antiproliferative and pro-differentiation effects in the normal mammary gland.

ZK114043 strongly inhibited epithelial DNA synthesis

ZK114043 induced a differentiated secretory phenotype, with increased lipid accumulation in alveolar cells.

155
Study Preventive effects Type of PRM Study Duration Type of study Sample Size (N) / Main Inclusion and Exclusion criteria Methodology Main Findings Ref
Simões et al, 2025 Yes Ulipristal acetate: 5 mg daily 12 weeks Window-of-opportunity clinical trial

N = 24

Inclusion: Premenopausal women (25–45 years old) with regular cycles and BRCA1/2 mutation or women at moderate to high familial BC risk.

Exclusion: history of breast, uterine, cervical or ovarian cancer; pregnancy/breastfeeding, prior breast enhancement, or use of hormonal therapies, steroids, anticoagulants, or CYP3A4 inhibitors; liver disease/cirrhosis

Effect of ulipristal acetate on surrogate markers of breast cancer risk in 24 premenopausal women

Significant reduction in Ki67 (8.2% → 2.9%, P < 0.0001) alongside a drop in progesterone levels (36 → <3 nmol/L, P < 0.0001), effectively suppressing the luteal phase.

Decreased epithelial area in lobules and reduced acinar structure size following treatment.

Luminal progenitor cells significantly reduced (from 43% to 30%, P < 0.001), with no changes in luminal mature or basal cells

50 genes differentially expressed (log2FC > 1.5, P < 0.05) after the treatment.

156
Utjés et al., 2024 Yes Mifepristone: 50 mg every other day 8 weeks Secondary Outcomes of a RCT

N = 16

Inclusion: Healthy premenopausal women (18–43 years old) with regular cycles, no treatment contraindications.

Exclusion: history of cancer, pregnancy/breastfeeding

Breast biopsies were collected from 16 women at baseline and after two months of treatment with 50 mg mifepristone every other day, yielding 32 paired samples. Breast cancer-related signatures and progesterone receptor signalling pathways were analyzed.

27 differentially expressed genes identified, mainly linked to extracellular matrix remodelling.

Mifepristone-induced gene signature in vivo closely matched in vitro findings

Gene signature associated with breast carcinogenesis and progesterone receptor status

157
Bartlett et al., 2022 Yes Mifepristone: 50 mg every other day; UPA: 5 mg daily 12 weeks RCT

N = 44

Inclusion: Healthy premenopausal women (18–45 years old) with regular cycles and confirmed BRCA1/2 mutation (or non-carrier controls).

Exclusion: recent hormonal medication, pregnancy/breastfeeding, history of cancer, or prior bilateral salpingo-oophorectomy

Two cohorts were studied: the first received mifepristone (50 mg every other day), and the second received ulipristal acetate (5 mg daily). Effects on breast cancer risk markers, including cell composition, proliferation, TP53 mutation, and methylation, were assessed in women with and without BRCA PV.

Progesterone levels are higher in luteal phase in BRCA1 PV carriers, suggesting progesterone as a target for cancer risk reduction.

Triple Negative Breast Cancers show elevated DNA methylation signatures reflecting higher mitotic age and higher proportion of luminal progenitor cells supporting the idea that luminal progenitor cells with high replicative age represent a predisposition to malignant transformation.

Mifepristone reduces both mitotic age and luminal progenitor cell proportion in normal breast tissue in all controls and 64% of BRCA1/2 PV carriers. Moreover, Ulipristal acetate produces similar effects, validating the role of progesterone pathway targeting.

Mifepristone decreases TP53 mutation frequency and the number of mutations in normal breast tissue of mitotic-age responders.

20
Westhoff et al., 2022 Yes Ulipristal acetate: 10 mg daily 12 weeks (84 days) RCT

N = 25

Inclusion: Healthy women (18–39 years old, BMI ≤ 35 kg/m²) with regular cycles, no baseline breast mass/ovarian cysts, and no contraindications to COCs.

Exclusion: recent exogenous hormones, pregnancy, breastfeeding, or interacting medications.

Women aged 18–39 received ulipristal acetate (10 mg daily) or combination oral contraceptives for 84 days, with breast cell proliferation and background parenchymal enhancement monitored.

Ulipristal acetate reduced Ki67 by 84% (p = 0.040), while the COC group showed an 8% increase (p = 0.85)

BPE scores decreased from 3 to 1 (p = 0.008) with ulipristal, with no change in the COC group

60
Engman et al., 2008 Yes Mifepristone: 50 mg every other day 12 weeks RCT

N = 28

Inclusion: Premenopausal women referred for leiomyoma surgery (due to menorrhagia/pressure symptoms).

Exclusion: recent steroidal hormone therapy, history of cancer, abnormal baseline breast/pelvic imaging, urgent surgery needs, postmenopausal FSH levels, or significant systemic/hormonal dysfunction.

30 women, scheduled for surgical treatment of leiomyomas, randomized to either 50 mg mifepristone or placebo every other day, for 3 months.

Mifepristone significantly reduced Ki-67 index after 3 months (P = 0.012) with lower inter-individual variability.

Mifepristone did not affect cortisol but increased serum testosterone levels.

Mifepristone reduced breast soreness and swelling but increased the incidence of hot flushes.

59

RCT Randomized Controlled trial; ER, Estrogen Receptor; EP Estrogen and Progesterone (EP); MSC Mammary stem cell; LP Luminal Progenitor; PV Pathogenic Variant; TAg SV40 Large T Antigen; DMBA Dimethylbenzanthracene; MPA Medroxyprogesterone Acetate; MNU N-Methyl-N-nitrosourea; muRANK murine RANK (Receptor Activator of NF-κB); muFc murine Fc region; PBS Phosphate-Buffered Saline; RANK-FC recombinant fusion protein consisting of the extracellular ligand-binding domain of RANK coupled to an immunoglobulin Fc region, which acts as a soluble decoy receptor to neutralize RANKL and thereby inhibit RANK signaling; PRM Progesterone Receptor Modulator; BPE Background Parenchymal Enhancement.

Acknowledgements

We thank Dr. Sara Sleigh for editorial support.

Author contributions

Martin Widschwendter (Conceptualization; Writing—original draft; Writing—review & editing), Rita Schmutzler (Conceptualization; Writing—review & editing), Nora Pashayan (Conceptualization; Writing—review & editing), Jelle Wesseling (Conceptualization; Writing—review & editing), Marc Tischkowitz (Conceptualization; Writing—review & editing), Michal Zikan (Conceptualization; Writing—review & editing), Miranda Steenbeek (Conceptualization; Writing—review & editing), Marike Gabrielson (Conceptualization; Writing—review & editing), Christian Singer (Conceptualization; Writing—review & editing), Cathrin Brisken (Conceptualization; Writing—review & editing), Rebecca Gomperts (Conceptualization; Writing—review & editing), Sharon Cameron (Conceptualization; Writing—review & editing), Dafydd Gareth Evans (Conceptualization; Writing—review & editing), Andri Papakonstantinou (Conceptualization; Writing—review & editing), Marc Buyse (Conceptualization; Writing—review & editing), Kerstin Rhiem (Conceptualization; Writing—review & editing), Mateja Krajc (Conceptualization; Writing—review & editing), Charlotte Vavourakis (Conceptualization; Writing—review & editing), Elisa Redl (Conceptualization; Writing—review & editing), Chiara Herzog (Conceptualization; Writing—review & editing), James Barrett (Conceptualization; Writing—review & editing), Mohammed Fatih Rasul (Conceptualization; Writing—review & editing), Deborah Utjé (Conceptualization; Writing—review & editing), Kiriaki Papaikonomou (Conceptualization; Writing—review & editing), Angelique Flöter Rådestad (Conceptualization; Writing—review & editing), Athanasios Zouzos (Conceptualization; Writing—review & editing), Twana Alkasalias (Conceptualization; Writing—review & editing), Kristina Gemzell-Danielsson (Conceptualization; Writing—review & editing).

Data availability

No datasets were generated or analysed during the current study.

Competing interests

Martin Widschwendter, Chiara Herzog, and James Barrett declare no Competing Non-Financial Interests but the following Competing Financial Interests: they are shareholders of SOLA Diagnostics GmbH, which holds an exclusive licence to the intellectual property related to the WID-BC test. The other authors declare no Competing Financial or Non-Financial Interests.

Footnotes

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  • 1.Ginsburg, O. et al. Women, power, and cancer: a Lancet Commission. Lancet402, 2113–2166 (2023). [DOI] [PubMed] [Google Scholar]
  • 2.Breast et al. Pathology of tumors associated with pathogenic germline variants in 9 breast cancer susceptibility genes. JAMA Oncol.8, e216744 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Bianchini, G., Balko, J. M., Mayer, I. A., Sanders, M. E. & Gianni, L. Triple-negative breast cancer: challenges and opportunities of a heterogeneous disease. Nat. Rev. Clin. Oncol.13, 674–690 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Hartmann, L. C. & Lindor, N. M. The role of risk-reducing surgery in hereditary breast and ovarian cancer. N. Engl. J. Med.374, 454–468 (2016). [DOI] [PubMed] [Google Scholar]
  • 5.De Felice, F. et al. Bilateral risk-reduction mastectomy in BRCA1 and BRCA2 mutation carriers: a meta-analysis. Ann. Surg. Oncol.22, 2876–2880 (2015). [DOI] [PubMed] [Google Scholar]
  • 6.Ingham, S. L. et al. Risk-reducing surgery increases survival in BRCA1/2 mutation carriers unaffected at time of family referral. Breast Cancer Res. Treat.142, 611–618 (2013). [DOI] [PubMed] [Google Scholar]
  • 7.Cuzick, J. et al. Use of anastrozole for breast cancer prevention (IBIS-II): long-term results of a randomised controlled trial. Lancet395, 117–122 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Cuzick, J. et al. Investigators I-I: Tamoxifen for prevention of breast cancer: extended long-term follow-up of the IBIS-I breast cancer prevention trial. Lancet Oncol.16, 67–75 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Schrag, D. et al. Blood-based tests for multicancer early detection (PATHFINDER): a prospective cohort study. Lancet402, 1251–1260 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Lennon A. M., et al. Feasibility of blood testing combined with PET-CT to screen for cancer and guide intervention. Science369, 6499 (2020). [DOI] [PMC free article] [PubMed]
  • 11.Kuchenbaecker, K. B. et al. Risks of Breast, Ovarian, and Contralateral Breast Cancer for BRCA1 and BRCA2 Mutation Carriers. JAMA317, 2402–2416 (2017). [DOI] [PubMed] [Google Scholar]
  • 12.Engel, C. et al. Breast cancer risk in BRCA1/2 mutation carriers and noncarriers under prospective intensified surveillance. Int J. Cancer146, 999–1009 (2020). [DOI] [PubMed] [Google Scholar]
  • 13.Tuchler, A. et al. Clinical implications of incorporating genetic and non-genetic risk factors in CanRisk-based breast cancer risk prediction. Breast73, 103615 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Mema, E. et al. The relationship of breast density in mammography and magnetic resonance imaging in women with triple negative breast cancer. Eur. J. Radio.124, 108813 (2020). [DOI] [PubMed] [Google Scholar]
  • 15.Venkitaraman, A. R. Cancer suppression by the chromosome custodians, BRCA1 and BRCA2. Science343, 1470–1475 (2014). [DOI] [PubMed] [Google Scholar]
  • 16.Kautz-Freimuth, S. et al. Effectiveness of evidence-based decision aids for women with pathogenic BRCA1 or BRCA2 variants in the german health care context: results from a randomized controlled trial. BMC Med. Inf. Decis. Mak.23, 223 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Widschwendter, M. et al. The sex hormone system in carriers of BRCA1/2 mutations: a case-control study. Lancet Oncol.14, 1226–1232 (2013). [DOI] [PubMed] [Google Scholar]
  • 18.Widschwendter, M. et al. Osteoprotegerin (OPG), The Endogenous Inhibitor of Receptor Activator of NF-kappaB Ligand (RANKL), is Dysregulated in BRCA Mutation Carriers. EBioMedicine2, 1331–1339 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Haran S., et al. Natural killer cell dysfunction in premenopausal brca1 mutation carriers: A potential mechanism for ovarian carcinogenesis. Cancers (Basel)16,(2024). [DOI] [PMC free article] [PubMed]
  • 20.Bartlett, T. E. et al. Antiprogestins reduce epigenetic field cancerization in breast tissue of young healthy women. Genome Med.14, 64 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Schramek, D. et al. Osteoclast differentiation factor RANKL controls development of progestin-driven mammary cancer. Nature468, 98–102 (2010). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Gonzalez-Suarez, E. et al. RANK ligand mediates progestin-induced mammary epithelial proliferation and carcinogenesis. Nature468, 103–107 (2010). [DOI] [PubMed] [Google Scholar]
  • 23.Tanos, T. et al. Progesterone/RANKL is a major regulatory axis in the human breast. Sci. Transl. Med5, 182ra155 (2013). [DOI] [PubMed] [Google Scholar]
  • 24.Brisken, C. Progesterone signalling in breast cancer: a neglected hormone coming into the limelight. Nat. Rev. Cancer13, 385–396 (2013). [DOI] [PubMed] [Google Scholar]
  • 25.Tharmapalan, P., Mahendralingam, M., Berman, H. K. & Khokha, R. Mammary stem cells and progenitors: targeting the roots of breast cancer for prevention. EMBO J.38, e100852 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Chlebowski, R. T. et al. Association of Menopausal Hormone Therapy With Breast Cancer Incidence and Mortality During Long-term Follow-up of the Women’s Health Initiative Randomized Clinical Trials. JAMA324, 369–380 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Fitzpatrick, D., Pirie, K., Reeves, G., Green, J. & Beral, V. Combined and progestagen-only hormonal contraceptives and breast cancer risk: A UK nested case-control study and meta-analysis. PLoS Med20, e1004188 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Kumar, N. et al. The unique risk factor profile of triple-negative breast cancer: a comprehensive meta-analysis. J. Natl. Cancer Inst.116, 1210–1219 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.O’Brien et al. Hormone therapy use and young-onset breast cancer: a pooled analysis of prospective cohorts included in the Premenopausal Breast Cancer Collaborative Group. Lancet Oncol.26, 911–923 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Stjepanovic, N. et al. Association of premenopausal risk-reducing salpingo-oophorectomy with breast cancer risk in BRCA1/2 mutation carriers: Maximising bias-reduction. Eur. J. Cancer132, 53–60 (2020). [DOI] [PubMed] [Google Scholar]
  • 31.Choi, Y. H. et al. Association of Risk-Reducing Salpingo-Oophorectomy With Breast Cancer Risk in Women With BRCA1 and BRCA2 Pathogenic Variants. JAMA Oncol.7, 585–592 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Yu J. et al. Progestogen-driven B7-H4 contributes to onco-fetal immune tolerance. Cell (2024). [DOI] [PMC free article] [PubMed]
  • 33.Kim O., et al. Targeting progesterone signaling prevents metastatic ovarian cancer. Proc. Natl. Acad. Sci. USA (2020). [DOI] [PMC free article] [PubMed]
  • 34.Mauro, L. J., Spartz, A., Austin, J. R. & Lange, C. A. Reevaluating the Role of Progesterone in Ovarian Cancer: Is Progesterone Always Protective? Endocr. Rev.44, 1029–1046 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Mauro, L. J. et al. Progesterone Receptors Promote Quiescence and Ovarian Cancer Cell Phenotypes via DREAM in p53-Mutant Fallopian Tube Models. J. Clin. Endocrinol. Metab.106, 1929–1955 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Yu, M. et al. Circulating breast tumor cells exhibit dynamic changes in epithelial and mesenchymal composition. Science339, 580–584 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Bae S. Y. et al. Dissemination of Circulating Tumor Cells in Breast and Prostate Cancer: Implications for Early Detection. Endocrinology165, (2024). [DOI] [PMC free article] [PubMed]
  • 38.Cohen, J. D. et al. Detection and localization of surgically resectable cancers with a multi-analyte blood test. Science359, 926–930 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Klein, E. A. et al. Clinical validation of a targeted methylation-based multi-cancer early detection test using an independent validation set. Ann. Oncol.32, 1167–1177 (2021). [DOI] [PubMed] [Google Scholar]
  • 40.Widschwendter, M. et al. Methylation patterns in serum DNA for early identification of disseminated breast cancer. Genome Med.9, 115 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Zou, R. et al. Development and validation of a circulating microRNA panel for the early detection of breast cancer. Br. J. Cancer126, 472–481 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Nicholson, B. D. et al. Multi-cancer early detection test in symptomatic patients referred for cancer investigation in England and Wales (SYMPLIFY): a large-scale, observational cohort study. Lancet Oncol, (2023). [DOI] [PubMed]
  • 43.Kazarian, A. et al. Testing breast cancer serum biomarkers for early detection and prognosis in pre-diagnosis samples. Br. J. Cancer116, 501–508 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Welch, H. G., Prorok, P. C., O’Malley, A. J. & Kramer, B. S. Breast-Cancer Tumor Size, Overdiagnosis, and Mammography Screening Effectiveness. N. Engl. J. Med.375, 1438–1447 (2016). [DOI] [PubMed] [Google Scholar]
  • 45.Biller-Andorno, N. & Juni, P. Abolishing mammography screening programs? A view from the Swiss Medical Board. N. Engl. J. Med.370, 1965–1967 (2014). [DOI] [PubMed] [Google Scholar]
  • 46.Niraula, S., Biswanger, N., Hu, P., Lambert, P. & Decker, K. Incidence, Characteristics, and Outcomes of Interval Breast Cancers Compared With Screening-Detected Breast Cancers. JAMA Netw. Open3, e2018179 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.McCarthy, A. M. et al. Relationship of established risk factors with breast cancer subtypes. Cancer Med.10, 6456–6467 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Lopes Cardozo et al. Associations of a Breast Cancer Polygenic Risk Score With Tumor Characteristics and Survival. J. Clin. Oncol. JCO2201978 (2023). [DOI] [PMC free article] [PubMed]
  • 49.Confluence: https://confluence.cancer.gov/#home. In.
  • 50.Kerlikowske, K. et al. Breast cancer risk by breast density, menopause, and postmenopausal hormone therapy use. J. Clin. Oncol.28, 3830–3837 (2010). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Morrow, M. et al. A prospective study of variability in mammographic density during the menstrual cycle. Breast Cancer Res. Treat.121, 565–574 (2010). [DOI] [PubMed] [Google Scholar]
  • 52.Cuzick, J. et al. Tamoxifen-induced reduction in mammographic density and breast cancer risk reduction: a nested case-control study. J. Natl. Cancer Inst.103, 744–752 (2011). [DOI] [PubMed] [Google Scholar]
  • 53.Evans, D. G., Howell, S. J. & Howell, A. Personalized prevention in high risk individuals: Managing hormones and beyond. Breast39, 139–147 (2018). [DOI] [PubMed] [Google Scholar]
  • 54.Gabrielson, M. et al. Baseline breast tissue characteristics determine the effect of tamoxifen on mammographic density change. Int J. Cancer155, 339–351 (2024). [DOI] [PubMed] [Google Scholar]
  • 55.Oceguera-Basurto, P. et al. Selective estrogen receptor modulators in the prevention of breast cancer in premenopausal women: a review. Transl. Cancer Res9, 4444–4456 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Oh, H. et al. Expression of estrogen receptor, progesterone receptor, and Ki67 in normal breast tissue in relation to subsequent risk of breast cancer. NPJ Breast Cancer2, 16032 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.Polley, M. Y. et al. An international Ki67 reproducibility study. J. Natl. Cancer Inst.105, 1897–1906 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58.Nelson, A. & Shapiro, M. P. Promising selective progesterone receptor modulators: what’s new in female contraception? Expert Opin Investig. Drugs, (2024). [DOI] [PubMed]
  • 59.Engman, M., Skoog, L., Soderqvist, G. & Gemzell-Danielsson, K. The effect of mifepristone on breast cell proliferation in premenopausal women evaluated through fine needle aspiration cytology. Hum. Reprod.23, 2072–2079 (2008). [DOI] [PubMed] [Google Scholar]
  • 60.Westhoff C. L., et al. The progesterone-receptor modulator, ulipristal acetate, drastically lowers breast cell proliferation. Breast Cancer Res. Treat (2022). [DOI] [PMC free article] [PubMed]
  • 61.Poole, A. J. et al. Prevention of Brca1-mediated mammary tumorigenesis in mice by a progesterone antagonist. Science314, 1467–1470 (2006). [DOI] [PubMed] [Google Scholar]
  • 62.Barrett, J. E. et al. Epigenetic signatures in surrogate tissues are able to assess cancer risk and indicate the efficacy of preventive measures. Commun. Med (Lond.)5, 97 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63.Gemzell-Danielsson, K., Mandl, I. & Marions, L. Mechanisms of action of mifepristone when used for emergency contraception. Contraception68, 471–476 (2003). [DOI] [PubMed] [Google Scholar]
  • 64.Rydelius, J. et al. First dose of misoprostol administration at home or in hospital for medical abortion between 12-22 gestational weeks in Sweden (PRIMA): a multicentre, open-label, randomised controlled trial. Lancet404, 864–873 (2024). [DOI] [PubMed] [Google Scholar]
  • 65.Gemzell-Danielsson K., et al: Home use of mifepristone for medical abortion: a systematic review. BMJ Sex Reprod. Health (2024). [DOI] [PMC free article] [PubMed]
  • 66.Brandell, K. et al. Group VS: Medical Abortion before Confirmed Intrauterine Pregnancy: A Systematic Review. Semin Reprod. Med.40, 258–263 (2022). [DOI] [PubMed] [Google Scholar]
  • 67.Engman, M. et al. Mifepristone for treatment of uterine leiomyoma. A prospective randomized placebo controlled trial. Hum. Reprod.24, 1870–1879 (2009). [DOI] [PubMed] [Google Scholar]
  • 68.Nieman, L. K. Selective progesterone receptor modulators and reproductive health. Curr. Opin. Endocrinol. Diab Obes.29, 406–412 (2022). [DOI] [PubMed] [Google Scholar]
  • 69.Arora, D., Chawla, J., Kochar, S. P. S. & Sharma, J. C. A randomized control trial to assess efficacy of Mifepristone in medical management of uterine fibroid. Med J. Armed Forces India73, 267–273 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 70.Singh, S. S., Belland, L., Leyland, N., von Riedemann, S. & Murji, A. The past, present, and future of selective progesterone receptor modulators in the management of uterine fibroids. Am. J. Obstet. Gynecol.218, 563–572 e561 (2018). [DOI] [PubMed] [Google Scholar]
  • 71.https://womenandmore.org/en/.
  • 72.Cameron, S. T., Critchley, H. O., Buckley, C. H., Kelly, R. W. & Baird, D. T. Effect of two antiprogestins (mifepristone and onapristone) on endometrial factors of potential importance for implantation. Fertil. Steril.67, 1046–1053 (1997). [DOI] [PubMed] [Google Scholar]
  • 73.Narvekar, N. et al. Low-dose mifepristone inhibits endometrial proliferation and up-regulates androgen receptor. J. Clin. Endocrinol. Metab.89, 2491–2497 (2004). [DOI] [PubMed] [Google Scholar]
  • 74.Berger, C. et al. Molecular characterization of PRM-associated endometrial changes, PAEC, following mifepristone treatment. Contraception98, 317–322 (2018). [DOI] [PubMed] [Google Scholar]
  • 75.Papaikonomou, K., Frisendahl, C., Williams, A. R. W. & Gemzell-Danielsson, K. Effects of the levonorgestrel intrauterine system on the endometrium after long-term exposure to mifepristone: Secondary outcomes of a randomized controlled trial. Eur. J. Obstet. Gynecol. Reprod. Biol.252, 330–335 (2020). [DOI] [PubMed] [Google Scholar]
  • 76.Widschwendter M., et al: Short-term hormonal modulation with mifepristone does not induce oncogenic changes in the endometrium of BRCA1/2 pathogenic variant carriers. Commun. Med. (Lond)6, 150 (2026). [DOI] [PMC free article] [PubMed]
  • 77.Donnez, J. et al. Ulipristal acetate versus placebo for fibroid treatment before surgery. N. Engl. J. Med366, 409–420 (2012). [DOI] [PubMed] [Google Scholar]
  • 78.Dinis-Oliveira, R. J. Pharmacokinetics, toxicological and clinical aspects of ulipristal acetate: insights into the mechanisms implicated in the hepatic toxicity. Drug Metab. Rev.53, 375–383 (2021). [DOI] [PubMed] [Google Scholar]
  • 79.Cummings, S. R. et al. Denosumab for prevention of fractures in postmenopausal women with osteoporosis. N. Engl. J. Med.361, 756–765 (2009). [DOI] [PubMed] [Google Scholar]
  • 80.Joshi, P. A. et al. Progesterone induces adult mammary stem cell expansion. Nature465, 803–807 (2010). [DOI] [PubMed] [Google Scholar]
  • 81.Gnant, M. et al. Adjuvant denosumab in postmenopausal patients with hormone receptor-positive breast cancer (ABCSG-18): disease-free survival results from a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet Oncol.20, 339–351 (2019). [DOI] [PubMed] [Google Scholar]
  • 82.Tomasetti, C. & Vogelstein, B. Cancer etiology. Variation in cancer risk among tissues can be explained by the number of stem cell divisions. Science347, 78–81 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 83.Moore, L. et al. The mutational landscape of normal human endometrial epithelium. Nature580, 640–646 (2020). [DOI] [PubMed] [Google Scholar]
  • 84.Lac, V. et al. Oncogenic mutations in histologically normal endometrium: the new normal? J. Pathol.249, 173–181 (2019). [DOI] [PubMed] [Google Scholar]
  • 85.Cereser, B. et al. The mutational landscape of the adult healthy parous and nulliparous human breast. Nat. Commun.14, 5136 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 86.Parreno, V. et al. Transient loss of Polycomb components induces an epigenetic cancer fate. Nature629, 688–696 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 87.Hsu, C., Konner, J. A. & Gounder, M. M. Epigenetic Therapy in a Rare Ovarian Cancer - A Double-Edged Sword. N. Engl. J. Med.391, 770–772 (2024). [DOI] [PubMed] [Google Scholar]
  • 88.Widschwendter, M. et al. Epigenetic stem cell signature in cancer. Nat. Genet.39, 157–158 (2007). [DOI] [PubMed] [Google Scholar]
  • 89.Ohm, J. E. et al. A stem cell-like chromatin pattern may predispose tumor suppressor genes to DNA hypermethylation and heritable silencing. Nat. Genet39, 237–242 (2007). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 90.Schlesinger, Y. et al. Polycomb-mediated methylation on Lys27 of histone H3 pre-marks genes for de novo methylation in cancer. Nat. Genet39, 232–236 (2007). [DOI] [PubMed] [Google Scholar]
  • 91.Lee, T. I. et al. Control of developmental regulators by Polycomb in human embryonic stem cells. Cell125, 301–313 (2006). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 92.Baylin, S. B. & Jones, P. A. A decade of exploring the cancer epigenome - biological and translational implications. Nat. Rev. Cancer11, 726–734 (2011). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 93.Widschwendter, M. et al. Epigenome-based cancer risk prediction: rationale, opportunities and challenges. Nat. Rev. Clin. Oncol.15, 292–309 (2018). [DOI] [PubMed] [Google Scholar]
  • 94.Widschwendter M., Dubeau L.: Non-Surgical Cancer Risk Reduction in BRCA1 Mutation Carriers: Disabling the Remote Control. Cancers (Basel)12, (2020). [DOI] [PMC free article] [PubMed]
  • 95.Liu, Y. et al. A Mouse Model That Reproduces the Developmental Pathways and Site Specificity of the Cancers Associated With the Human BRCA1 Mutation Carrier State. EBioMedicine2, 1318–1330 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 96.Yen, H. Y. et al. Alterations in Brca1 expression in mouse ovarian granulosa cells have short-term and long-term consequences on estrogen-responsive organs. Lab Invest92, 802–811 (2012). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 97.Nene, N. R. et al. Association between the cervicovaginal microbiome, BRCA1 mutation status, and risk of ovarian cancer: a case-control study. Lancet Oncol.20, 1171–1182 (2019). [DOI] [PubMed] [Google Scholar]
  • 98.Kiechl, S. et al. Aberrant regulation of RANKL/OPG in women at high risk of developing breast cancer. Oncotarget8, 3811–3825 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 99.Herzog, C. et al. DNA methylation at quantitative trait loci (mQTLs) varies with cell type and nonheritable factors and may improve breast cancer risk assessment. NPJ Precis Oncol.7, 99 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 100.Barrett, J. E. et al. Susceptibility to hormone-mediated cancer is reflected by different tick rates of the epithelial and general epigenetic clock. Genome Biol.23, 52 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 101.Herzog, C. et al. DNA methylation-based detection and prediction of cervical intraepithelial neoplasia grade 3 and invasive cervical cancer with the WID-qCIN test. Clin. Epigenetics14, 150 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 102.Schreiberhuber L., et al: Cervical cancer screening using DNA methylation triage in a real-world population. Nat. Med. (2024). [DOI] [PMC free article] [PubMed]
  • 103.Barrett, J. E. et al. The WID-CIN test identifies women with, and at risk of, cervical intraepithelial neoplasia grade 3 and invasive cervical cancer. Genome Med.14, 116 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 104.Widschwendter, M. et al. Loss of retinoic acid receptor beta expression in breast cancer and morphologically normal adjacent tissue but not in the normal breast tissue distant from the cancer. Cancer Res57, 4158–4161 (1997). [PubMed] [Google Scholar]
  • 105.Widschwendter, M., Berger, J., Muller, H. M., Zeimet, A. G. & Marth, C. Epigenetic downregulation of the retinoic acid receptor-beta2 gene in breast cancer. J. Mammary Gland Biol. Neoplasia6, 193–201 (2001). [DOI] [PubMed] [Google Scholar]
  • 106.Widschwendter, M. et al. Methylation and silencing of the retinoic acid receptor-beta2 gene in breast cancer. J. Natl. Cancer Inst.92, 826–832 (2000). [DOI] [PubMed] [Google Scholar]
  • 107.Gao, Y., Widschwendter, M. & Teschendorff, A. E. DNA Methylation Patterns in Normal Tissue Correlate more Strongly with Breast Cancer Status than Copy-Number Variants. EBioMedicine31, 243–252 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 108.Yang, Z. et al. Correlation of an epigenetic mitotic clock with cancer risk. Genome Biol.17, 205 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 109.Nolan, E. et al. RANK ligand as a potential target for breast cancer prevention in BRCA1-mutation carriers. Nat. Med.22, 933–939 (2016). [DOI] [PubMed] [Google Scholar]
  • 110.Teschendorff, A. E. et al. DNA methylation outliers in normal breast tissue identify field defects that are enriched in cancer. Nat. Commun.7, 10478 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 111.Teschendorff, A. E., Jones, A. & Widschwendter, M. Stochastic epigenetic outliers can define field defects in cancer. BMC Bioinforma.17, 178 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 112.Wang, Y., Teschendorff, A. E., Widschwendter, M. & Wang, S. Accounting for differential variability in detecting differentially methylated regions. Brief. Bioinform20, 47–57 (2019). [DOI] [PubMed] [Google Scholar]
  • 113.Bartlett, T. E. et al. Epigenetic reprogramming of fallopian tube fimbriae in BRCA mutation carriers defines early ovarian cancer evolution. Nat. Commun.7, 11620 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 114.Widschwendter, M. et al. HOXA methylation in normal endometrium from premenopausal women is associated with the presence of ovarian cancer: a proof of principle study. Int J. Cancer125, 2214–2218 (2009). [DOI] [PubMed] [Google Scholar]
  • 115.Jones, A. et al. Role of DNA methylation and epigenetic silencing of HAND2 in endometrial cancer development. PLoS Med.10, e1001551 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 116.Barrett, J. E. et al. The WID-BC-index identifies women with primary poor prognostic breast cancer based on DNA methylation in cervical samples. Nat. Commun.13, 449 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 117.Herzog, C. M. S. et al. Systems epigenetic approach towards non-invasive breast cancer detection. Nat. Commun.16, 3082 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 118.Barrett, J. E. et al. The DNA methylome of cervical cells can predict the presence of ovarian cancer. Nat. Commun.13, 448 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 119.Barrett J. E., et al. The WID-EC test for the detection and risk prediction of endometrial cancer. Int. J. Cancer152, 1977–1988 (2022). [DOI] [PubMed]
  • 120.Herzog, C. et al. Cigarette Smoking and E-cigarette Use Induce Shared DNA Methylation Changes Linked to Carcinogenesis. Cancer Res84, 1898–1914 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 121.Mavaddat, N. et al. Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes. Am. J. Hum. Genet104, 21–34 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 122.Pourali, G. et al. Medications to reduce breast cancer risk: a network meta-analysis of randomized controlled trials. Breast Cancer Res.27, 118 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 123.Tung, N. & Garber, J. E. PARP inhibition in breast cancer: progress made and future hopes. NPJ Breast Cancer8, 47 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 124.Zhang X. E., et al: Mammographic density, pathogenic breast cancer susceptibility gene variants, and breast cancer risk: a pooled case–control analysis. Lancet Obstet Gynaecol Womens Health, 2, e451–e459 (2026).
  • 125.Schettini, F. et al. Poly (ADP-ribose) polymerase inhibitors in solid tumours: Systematic review and meta-analysis. Eur. J. Cancer149, 134–152 (2021). [DOI] [PubMed] [Google Scholar]
  • 126.Lakha, F. et al. A novel estrogen-free oral contraceptive pill for women: multicentre, double-blind, randomized controlled trial of mifepristone and progestogen-only pill (levonorgestrel). Hum. Reprod.22, 2428–2436 (2007). [DOI] [PubMed] [Google Scholar]
  • 127.Hapangama, D. K., Brown, A., Glasier, A. F. & Baird, D. T. Feasibility of administering mifepristone as a once a month contraceptive pill. Hum. Reprod.16, 1145–1150 (2001). [DOI] [PubMed] [Google Scholar]
  • 128.Brown, A., Cheng, L., Lin, S. & Baird, D. T. Daily low-dose mifepristone has contraceptive potential by suppressing ovulation and menstruation: a double-blind randomized control trial of 2 and 5 mg per day for 120 days. J. Clin. Endocrinol. Metab.87, 63–70 (2002). [DOI] [PubMed] [Google Scholar]
  • 129.Agarwal, M., Das, V., Agarwal, A., Pandey, A. & Srivastava, D. Evaluation of mifepristone as a once a month contraceptive pill. Am. J. Obstet. Gynecol.200, e27–e29 (2009). [DOI] [PubMed] [Google Scholar]
  • 130.Gemzell-Danielsson, K., Swahn, M. L., Svalander, P. & Bygdeman, M. Early luteal phase treatment with mifepristone (RU 486) for fertility regulation. Hum. Reprod.8, 870–873 (1993). [DOI] [PubMed] [Google Scholar]
  • 131.Marions, L., Danielsson, K. G., Swahn, M. L. & Bygdeman, M. Contraceptive efficacy of low doses of mifepristone. Fertil. Steril.70, 813–816 (1998). [DOI] [PubMed] [Google Scholar]
  • 132.Marions, L. et al. Contraceptive efficacy of daily administration of 0.5 mg mifepristone. Hum. Reprod.14, 2788–2790 (1999). [DOI] [PubMed] [Google Scholar]
  • 133.Cheng, J., Weng, L. & Han, X. Study on weekly low doses of mifepristone for contraception]. Zhonghua Fu Chan Ke Za Zhi36, 424–427 (2001). [PubMed] [Google Scholar]
  • 134.Godfrey, E. M., Mawson, J. T., Stanwood, N. L., Fielding, S. L. & Schaff, E. A. Low-dose mifepristone for contraception: a weekly versus planned postcoital randomized pilot study. Contraception70, 41–46 (2004). [DOI] [PubMed] [Google Scholar]
  • 135.Pei, K. et al. Weekly contraception with mifepristone. Contraception75, 40–44 (2007). [DOI] [PubMed] [Google Scholar]
  • 136.Shen J., Che Y., Showell E., Chen K., Cheng L.: Interventions for emergency contraception. Cochrane Database Syst. Rev. CD001324 (2019). [DOI] [PMC free article] [PubMed]
  • 137.Islam M. S., Afrin S., Jones S. I., Segars J.: Selective Progesterone Receptor Modulators-Mechanisms and Therapeutic Utility. Endocr. Rev.41, (2020). [DOI] [PMC free article] [PubMed]
  • 138.Cabrol, D. et al. Induction of labor with mifepristone (RU 486) in intrauterine fetal death. Am. J. Obstet. Gynecol.163, 540–542 (1990). [DOI] [PubMed] [Google Scholar]
  • 139.Elliott, C. L., Brennand, J. E. & Calder, A. A. The effects of mifepristone on cervical ripening and labor induction in primigravidae. Obstet. Gynecol.92, 804–809 (1998). [DOI] [PubMed] [Google Scholar]
  • 140.Kulier, R. et al. Medical methods for first trimester abortion. Cochrane Database Syst. Rev.2011, CD002855 (2011). [DOI] [PubMed] [Google Scholar]
  • 141.Ghosh, J. et al. Methods for managing miscarriage: a network meta-analysis. Cochrane Database Syst. Rev.6, CD012602 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 142.Newmann S. J., et al. Cervical preparation for second trimester dilation and evacuation. Cochrane Database Syst. Rev. 2010:CD007310. [DOI] [PubMed]
  • 143.In: Medical versus surgical abortion between 13+0 and 24+0 weeks’ gestation: Abortion care: Evidence Review K. edn. London; 2019. [PubMed]
  • 144.Karena, Z. V. et al. Clinical Utility of Mifepristone: Apprising the Expanding Horizons. Cureus14, e28318 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 145.Ault, T. A., Braxton, D. R., Watson, R. A., Marcus, A. O. & Fong, T. L. Mifepristone-induced liver injury in a patient with Cushing syndrome: a case report and review of the literature. J. Med Case Rep.17, 33 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 146.Lee, O. et al. Z-Endoxifen prevents aggressive mammary cancers in mice by inhibiting cell proliferation and creating a tumor suppressive microenvironment. Biomed. Pharmacother.162, 114607 (2023). [DOI] [PubMed] [Google Scholar]
  • 147.Ranjan, M. et al. Progesterone receptor antagonists reverse stem cell expansion and the paracrine effectors of progesterone action in the mouse mammary gland. Breast Cancer Res.23, 78 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 148.Lee, O. et al. Selective progesterone receptor blockade prevents BRCA1-associated mouse mammary tumors through modulation of epithelial and stromal genes. Cancer Lett.520, 255–266 (2021). [DOI] [PubMed] [Google Scholar]
  • 149.Lee, O., Choi, M. R., Christov, K., Ivancic, D. & Khan, S. A. Progesterone receptor antagonism inhibits progestogen-related carcinogenesis and suppresses tumor cell proliferation. Cancer Lett.376, 310–317 (2016). [DOI] [PubMed] [Google Scholar]
  • 150.Communal, L. et al. Proliferation and ovarian hormone signaling are impaired in normal breast tissues from women with BRCA1 mutations: benefit of a progesterone receptor modulator treatment as a breast cancer preventive strategy in women with inherited BRCA1 mutations. Oncotarget7, 45317–45330 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 151.Communal, L. et al. Ulipristal acetate does not impact human normal breast tissue. Hum. Reprod.27, 2785–2798 (2012). [DOI] [PubMed] [Google Scholar]
  • 152.Wiehle, R., Lantvit, D., Yamada, T. & Christov, K. CDB-4124, a progesterone receptor modulator, inhibits mammary carcinogenesis by suppressing cell proliferation and inducing apoptosis. Cancer Prev. Res. (Philos.)4, 414–424 (2011). [DOI] [PubMed] [Google Scholar]
  • 153.Kariagina, A., Xie, J., Leipprandt, J. R. & Haslam, S. Z. Amphiregulin Mediates Estrogen, Progesterone, and EGFR Signaling in the Normal Rat Mammary Gland and in Hormone-Dependent Rat Mammary Cancers. Hormones Cancer1, 229–244 (2010). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 154.Lim, E. et al. Aberrant luminal progenitors as the candidate target population for basal tumor development in BRCA1 mutation carriers. Nat. Med.15, 907–913 (2009). [DOI] [PubMed] [Google Scholar]
  • 155.Li, M. et al. Antiprogestins inhibit growth and stimulate differentiation in the normal mammary gland. J. Cell Physiol.164, 1–8 (1995). [DOI] [PubMed] [Google Scholar]
  • 156.Simoes, B. M. et al. Anti-progestin therapy targets hallmarks of breast cancer risk. Nature648, 736–745 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 157.Utjés D. et al. Transcriptomic Profile of Breast Tissue of Premenopausal Women Following Treatment with Progesterone Receptor Modulator: Secondary Outcomes of a Randomized Controlled Trial. Int. J. Mol. Sci.25, 7590 (2024). [DOI] [PMC free article] [PubMed]

Associated Data

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Data Availability Statement

No datasets were generated or analysed during the current study.


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