Women go through several predictable conditions and symptoms during menopause that are caused by age, changes in sex hormone levels, and other factors. Conventional menopause hormone therapy has raised serious concerns about the increased risks of cancers, blood clots, depression, etc. Selective estrogen receptor modulators (SERMs) that can be both agonists and antagonists of estrogen receptors in a tissue-specific manner are being developed to reduce the health concerns associated with menopause hormone therapy. Here, we have searched the Chinese national traditional Chinese medicine (TCM) patent database to identify potential SERM-like compounds with reduced health risks. TCM has been widely used for treating complex symptoms associated with menopause syndrome and thus can be a particularly rich source for pharmaceutical alternatives with SERM properties. After extensive literature review and molecular simulation, we conclude that protopanaxatriol, paeoniflorin, astragalin, catalpol, and hyperoside among others may be particularly promising as SERM-like compounds in treating the menopausal syndrome. Compounds in TCM hold promise in yielding comparable outcomes to hormone therapy but with reduced associated risks, thus presenting promising avenues for their clinical applications.

OBJECTIVE: This research aimed to probe the expression of long noncoding RNA TMEM147 antisense RNA 1 (TMEM147-AS1)/micro-RNA (miR)-124/signal transducer and activator of transcription 3 (STAT3) axis in estrogen receptor (ER)-positive breast cancer (BC).
METHODS: Sixty ER-positive BC patients undergoing surgical treatment were gathered. TMEM147-AS1, miR-124, and STAT3 expression levels in BC cells and tissues were measured. The binding sites of TMEM147-AS1 and miR-124, miR-124, and STAT3 were analyzed and validated. The miR-124, STAT3 overexpression (oe) sequences, TMEM147-AS1 oe, and interference sequences and their control sequences were planned and cells were transfected to assess their functions in BC cells biological functions.
RESULTS: TMEM147-AS1, as well as STAT3 was extremely expressed and miR-124 was lowly expressed in BC cells and tissues. Interference with TMEM147-AS1 restrained ER-positive BC cell malignant activities. Mechanistically, TMEM147-AS1 could competitively bind miR-124 in refraining miR-124 expression, and STAT3 was a target gene of miR-124. Oe of miR-124 effectively reversed the enhancement of BC cell proliferation and invasion induced by TMEM147-AS1 upregulation. Oe of STAT3 could reverse the inhibitory effect of miR-124 on BC cell malignant behaviors.
CONCLUSIONS: TMEM147-AS1 has oncogenic activity in ER-positive BC, which may be a result of the altered miR-124/STAT3 axis. Therefore, targeting the TMEM147-AS1/miR-124/STAT3 axis may be a target for ER-positive BC therapy.

The estrogen receptor (ER), a ligand-dependent transcription factor, is critical for vertebrate reproduction. However, its role in bivalves is not well understood, with ongoing debates regarding its function in regulating reproduction similarly to vertebrates. To investigate ER\'s function, we conducted a 21-day RNA interference experiment focusing on its role in gonadal development in bivalves. Histological analyses revealed that ER inhibition significantly suppressed ovarian development in females and, conversely, promoted gonadal development in males. Additionally, levels of 17β-estrogen (E2) were markedly reduced in the gonads of both sexes following ER suppression. Transcriptomic analysis from RNA-seq of testes and ovaries after ER interference showed changes in the expression of key genes such as Vtg, CYP17, 3β-HSD, and 17β-HSD. These genes are involved in the estrogen signaling pathway and steroid hormone biosynthesis. Furthermore, ER suppression significantly affected the expression of genes linked to gametogenesis and the reproductive cycle. Our findings highlight ER\'s crucial, yet complex and sex-specific roles in gonadal development in bivalves, emphasizing the need for further detailed studies.

Metformin shows promise in breast cancer prevention, but its underlying mechanisms remain unclear. This study investigated the impact of metformin on the repopulation dynamics of mammary epithelial cells (MECs) and the signaling pathways in non-tumorigenic FVB/N mice. This study aimed to enhance our understanding of the role of metformin in reducing the susceptibility of MECs in premalignant tissues to oncogenic factors. In this study, female mice were administered 200 mg/kg/day of metformin via intraperitoneal (i.p.) injection from 8 to 18 weeks of age. After this treatment period, morphogenesis, flow cytometry, analyses of MEC stemness, and RNA sequencing were performed. The study findings indicated that metformin treatment in adult mice reduced mammary gland proliferation, as demonstrated by decreased Ki67+ cells and lateral bud formation. Additionally, metformin significantly reduced both basal and mammary repopulating unit subpopulations, indicating an impact on mammary epithelial cell repopulation. Mammosphere, colony-forming cell, and 3D culture assays revealed that metformin adversely affected mammary epithelial cell stemness. Furthermore, metformin downregulated signaling in key pathways including AMPK/mTOR, MAPK/Erk, PI3K/Akt, and ER, which contribute to its inhibitory effects on mammary proliferation and stemness. Transcriptome analysis with RNA sequencing indicated that metformin induced significant downregulation of genes involved in multiple critical pathways. KEGG-based pathway analysis indicated that genes in PI3K/Akt, focal adhesion, ECM-receptor, small cell lung cancer and immune-modulation pathways were among the top groups of differentially regulated genes. In summary, our research demonstrates that metformin inhibits MEC proliferation and stemness, accompanied by the downregulation of intrinsic signaling. These insights suggest that the regulatory effects of metformin on premalignant mammary tissues could potentially delay or prevent the onset of breast cancer, offering a promising avenue for developing new preventive strategies.

This study aims to explore the roles of three estrogen receptors (Esr1, Esr2, and Gper1) in early differentiation of embryonic gonads of Trachemys scripta. The expression characteristics of the receptor genes were studied first. The Esr1, Esr2, and Gper1 agonists PPT, WAY 200070, and G-1 were respectively injected into the embryos at the male-producing temperature (MPT) before initiation of gonadal differentiation. The sex reversal of the treated embryonic gonads was analyzed in terms of morphological structure of gonads, distribution pattern of germ cells, and expression of key genes and proteins involved in sex differentiation. The expression level of esr1 during the critical stage of sex differentiation was higher than those of esr2 and gper1 (very low expression) and was particularly high in the gonads at the female-producing temperature (FPT). After treatment with PPT, the MPT gonads presented obviously feminized morphology and structure, with the germ cells exhibiting a female distribution pattern. Furthermore, the mRNA expression levels of the key genes (dmrt1, amh, and sox9) for male differentiation were down-regulated significantly, while those of the key genes (foxl2 and cyp19a1) for female differentiation were up-regulated observably. The fluorescent signals of Amh and Sox9 expression almost disappeared, while Foxl2 and Arom were activated to express abundantly, which fully demonstrated the sex reversal of the gonads from male to female (sex reversal rate: 70.27%). However, the MPT gonads treated with WAY 200070 and G-1 still differentiated into testes, and the expression patterns of the key genes and proteins were similar to those in male gonads. The above results demonstrate that activation of Esr1 alone can fully initiate the early female differentiation process of gonads, suggesting that estrogen may induce early ovarian differentiation via Esr1 in Trachemys scripta. The findings provide a basis for further revealing the mechanisms of estrogen regulation in sex determination and differentiation of turtles.

Estrogen receptor-positive (ER+) breast cancer seriously endangers the women\'s physical and mental health worldwide and ER targeting therapy is vital. Here, we found that a citrus polymethoxyflavones (PMFs)-rich hydrolysate (C-H) and its major components (nobiletin and 3-methoxynobiletin) potently degrade ERα protein via the ubiquitin-proteasome pathway, thereby impairing the proliferation of ER+ breast cancer cells. Moreover, our study exhibited that C-H combined with tamoxifen (TAM) inhibited the cell proliferation of ER+ breast cancer in vitro. It was further confirmed that C-H decreased tumor growth of ER+ breast cancer in tumor-bearing 129 mice in vivo and improved the efficacy of tamoxifen. Our study revealed that the citrus PMFs have potential applications as pharmaceutical and healthcare products in breast cancer treatment by targeting ERα protein degradation.

Widespread use of the new chiral triazole fungicide mefentrifluconazole (MFZ) poses a threat to soil organisms. Although triazole fungicides have been reported to induce reproductive disorders in vertebrates, significant research gaps remain regarding their impact on the reproductive health of soil invertebrates. Here, reproduction-related toxicity end points were explored in earthworms (Eisenia fetida) after exposure for 28 d to soil containing 4 mg/kg racemic MFZ, R-(-)-MFZ, and S-(+)-MFZ. The S-(+)-MFZ treatment resulted in a more pronounced reduction in the number of cocoons and juveniles compared to R-(-)-MFZ treatment, and the expression of annetocin gene was significantly downregulated following exposure to both enantiomers. This reproductive toxicity has been attributed to the disruption of ovarian steroidogenesis at the transcriptional level. Further studies revealed that MFZ enantiomers were able to activate the estrogen receptor (ER). Indirect evidence for this estrogenic effect is provided by the introduction of 17β-estradiol, which also induces reproductive disorders through ER activation.

BACKGROUND: Evidence indicates that the risk of developing a secondary ovarian cancer (OC) is correlated with estrogen receptor (ER) status. However, the clinical significance of the relationship between ER-associated breast cancer (BC) and clear cell ovarian cancer (CCOC) remains elusive.
METHODS: Independent single nucleotide polymorphisms (SNPs) strongly correlated with exposure were extracted, and those associated with confounders and outcomes were removed using the PhenoScanner database. SNP effects were extracted from the outcome datasets with minor allele frequency > 0.01 as the filtration criterion. Next, valid instrumental variables (IVs) were obtained by harmonizing exposure and outcome effects and further filtered based on F-statistics (> 10). Mendelian randomization (MR) assessment of valid IVs was carried out using inverse variance weighted (IVW), MR Egger (ME), weighted median (WM), and multiplicative random effects-inverse variance weighted (MRE-IVW) methods. For sensitivity analysis and visualization of MR findings, a heterogeneity test, a pleiotropy test, a leave-one-out test, scatter plots, forest plots, and funnel plots were employed.
RESULTS: MR analyses with all four methods revealed that CCOC was not causally associated with ER-negative BC (IVW results: odds ratio (OR) = 0.89, 95% confidence interval (CI) = 0.66-1.20, P = 0.431) or ER-positive BC (IVW results: OR = 0.99, 95% CI = 0.88-1.12, P = 0.901). F-statistics were computed for each valid IV, all of which exceeded 10. The stability and reliability of the results were confirmed by sensitivity analysis.
CONCLUSIONS: Our findings indicated that CCOC dids not have a causal association with ER-associated BC. The absence of a definitive causal link between ER-associated BC and CCOC suggested a minimal true causal influence of ER-associated BC exposure factors on CCOC. These results indicated that individuals afflicted by ER-associated BC could alleviate concerns regarding the developing of CCOC, thereby aiding in preserving their mental well-being stability and optimizing the efficacy of primary disease treatment.

BACKGROUND: The estrogen receptor (ER) serves as a pivotal indicator for assessing endocrine therapy efficacy and breast cancer prognosis. Invasive biopsy is a conventional approach for appraising ER expression levels, but it bears disadvantages due to tumor heterogeneity. To address the issue, a deep learning model leveraging mammography images was developed in this study for accurate evaluation of ER status in patients with breast cancer.
OBJECTIVE: To predict the ER status in breast cancer patients with a newly developed deep learning model leveraging mammography images.
METHODS: Datasets comprising preoperative mammography images, ER expression levels, and clinical data spanning from October 2016 to October 2021 were retrospectively collected from 358 patients diagnosed with invasive ductal carcinoma. Following collection, these datasets were divided into a training dataset (n = 257) and a testing dataset (n = 101). Subsequently, a deep learning prediction model, referred to as IP-SE-DResNet model, was developed utilizing two deep residual networks along with the Squeeze-and-Excitation attention mechanism. This model was tailored to forecast the ER status in breast cancer patients utilizing mammography images from both craniocaudal view and mediolateral oblique view. Performance measurements including prediction accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curves (AUCs) were employed to assess the effectiveness of the model.
RESULTS: In the training dataset, the AUCs for the IP-SE-DResNet model utilizing mammography images from the craniocaudal view, mediolateral oblique view, and the combined images from both views, were 0.849 (95% CIs: 0.809-0.868), 0.858 (95% CIs: 0.813-0.872), and 0.895 (95% CIs: 0.866-0.913), respectively. Correspondingly, the AUCs for these three image categories in the testing dataset were 0.835 (95% CIs: 0.790-0.887), 0.746 (95% CIs: 0.793-0.889), and 0.886 (95% CIs: 0.809-0.934), respectively. A comprehensive comparison between performance measurements underscored a substantial enhancement achieved by the proposed IP-SE-DResNet model in contrast to a traditional radiomics model employing the naive Bayesian classifier. For the latter, the AUCs stood at only 0.614 (95% CIs: 0.594-0.638) in the training dataset and 0.613 (95% CIs: 0.587-0.654) in the testing dataset, both utilizing a combination of mammography images from the craniocaudal and mediolateral oblique views.
CONCLUSIONS: The proposed IP-SE-DResNet model presents a potent and non-invasive approach for predicting ER status in breast cancer patients, potentially enhancing the efficiency and diagnostic precision of radiologists.

Endocrine therapies targeting the estrogen receptor (ER/ESR1) are the cornerstone to treat ER-positive breast cancers patients, but resistance often limits their effectiveness. Understanding the molecular mechanisms is thus key to optimize the existing drugs and to develop new ER-modulators. Notable progress has been made although the fragmented way data is reported has reduced their potential impact. Here, we introduce EstroGene2.0, an expanded database of its precursor 1.0 version. EstroGene2.0 focusses on response and resistance to endocrine therapies in breast cancer models. Incorporating multi-omic profiling of 361 experiments from 212 studies across 28 cell lines, a user-friendly browser offers comprehensive data visualization and metadata mining capabilities (https://estrogeneii.web.app/). Taking advantage of the harmonized data collection, our follow-up meta-analysis revealed substantial diversity in response to different classes of ER-modulators including SERMs, SERDs, SERCA and LDD/PROTAC. Notably, endocrine resistant models exhibit a spectrum of transcriptomic alterations including a contra-directional shift in ER and interferon signaling, which is recapitulated clinically. Furthermore, dissecting multiple ESR1-mutant cell models revealed the different clinical relevance of genome-edited versus ectopic overexpression model engineering and identified high-confidence mutant-ER targets, such as NPY1R. These examples demonstrate how EstroGene2.0 helps investigate breast cancer\'s response to endocrine therapies and explore resistance mechanisms.