AIMC Topic: Receptors, Estrogen
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A lipid metabolism-related gene signature predicts prognosis after tamoxifen treatment in ER + breast cancer and reflects tumor microenvironment heterogeneity through single-cell analysis.
BMC medical genomics
Jul 31, 2025
BACKGROUND: Although the clinical outcome of ER + breast cancer patients receiving tamoxifen after surgery is favorable, a proportion of patients experience recurrence or death due to disease progression.
Multiomic integration reveals subtype-specific predictors of neoadjuvant treatment response in breast cancer.
Science advances
Jul 4, 2025
Neoadjuvant therapy has been widely used in breast cancer, but treatment response varies among individuals. We conducted multiomic profiling on tumor samples from 149 Chinese patients with breast cancer across ERHER2, ERHER2, and ERHER2 subtypes, cat...
A review of the use of tumour DNA methylation for breast cancer subtyping and prediction of outcomes.
Clinical epigenetics
Jul 2, 2025
DNA methylation in breast tumours has been extensively studied and has provided valuable insights into the clinical heterogeneity of breast cancer. In this review, we summarise the current literature that has used DNA methylation markers to subtype b...
Deep learning assessment of metastatic relapse risk from digitized breast cancer histological slides.
Nature communications
Jul 1, 2025
Accurate risk stratification is critical for guiding treatment decisions in early breast cancer. We present an artificial intelligence (AI)-based tool that analyzes digitized tumor slides to predict 5-year metastasis-free survival (MFS) in patients w...
ERRα-Predictor: A Framework of Ensemble Models for Prediction of ERRα Binders, Antagonists, and Agonists Using Artificial Intelligence.
Journal of chemical information and modeling
Jun 30, 2025
Estrogen-related receptor α (ERRα) is considered a promising target for the treatment of cancer and metabolic diseases. The development of comprehensive predictive models for ERRα binders, antagonists, and agonists is of significant importance. In th...
Efficacy and safety of first-line CDK4/6 inhibitors plus AI therapy for patients with HR +/HER2- advanced breast cancer: a network meta-analysis.
BMC cancer
May 8, 2025
BACKGROUND: CDK4/6 inhibitors plus aromatase inhibitors (AI) significantly improve the therapeutic effect of initial treatment for HR + /HER2- advanced breast cancer. However, there is a lack of head-to-head randomized controlled trials involving the...
Aminopyridines
Cyclin-Dependent Kinase 4
Cyclin-Dependent Kinase 6
Network Meta-Analysis as Topic
Receptor, ErbB-2
Aromatase Inhibitors
Protein Kinase Inhibitors
Benzimidazoles
Receptors, Estrogen
Purines
Receptors, Progesterone
Antineoplastic Combined Chemotherapy Protocols
Treatment Outcome
Randomized Controlled Trials as Topic
Progression-Free Survival
Humans
Female
Breast Neoplasms
From Nuclear Receptors to GPCRs: a Deep Transfer Learning Approach for Enhanced Environmental Estrogen Recognition.
Environmental science & technology
Apr 30, 2025
Environmental estrogens (EEs), as typical endocrine-disrupting chemicals (EDCs), can bind to classic estrogen receptors (ERs) to induce genomic effects, as well as to G protein-coupled estrogen receptor (GPER) located on the membrane, thereby inducin...
Toward Accurate Deep Learning-Based Prediction of Ki67, ER, PR, and HER2 Status From H&E-Stained Breast Cancer Images.
Applied immunohistochemistry & molecular morphology : AIMM
Mar 27, 2025
Despite improvements in machine learning algorithms applied to digital pathology, only moderate accuracy, to predict molecular information from histology alone, has been achieved so far. One of the obstacles is the lack of large data sets to properly...
Screening of estrogen receptor activity of per- and polyfluoroalkyl substances based on deep learning and in vivo assessment.
Environmental pollution (Barking, Essex : 1987)
Feb 11, 2025
Over the past decades, exposure to per- and polyfluoroalkyl substances (PFAS), a group of synthetic chemicals notorious for their environmental persistence, has been shown to pose increased health risks. Despite that some PFAS were reported to have e...
An assessment of breast cancer HER2, ER, and PR expressions based on mammography using deep learning with convolutional neural networks.
Scientific reports
Feb 9, 2025
Mammography is the recommended imaging modality for breast cancer screening. Expressions of human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), and progesterone receptor (PR) are critical to the development of therapeutic strateg...
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