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Incidents of breast cancer (BC) are on the rise on a daily basis and have proven to be the most prevelant cause of death for women in both developed and developing countries. Among total BC cases diagnosed after menopause, 70% of cases are Estrogen Receptor (ER) positive (ER-positive or ER+). Mutations in the LBD (ligand-binding domain) of the ER have recently been reported to be the major cause of resistance to potent antagonists. In this study, the experimentally reported mutations K303R, E380Q, V392I, S463P, V524E, P535H, P536H, Y537C, Y537N, Y537S, and D538G were analyzed, and the most significant mutations were shortlisted based on multiple analyses. Initial analyses, such as mCSM stability, occluded depth analysis, mCSM-binding affinity, and FoldX energy changes shortlisted only six mutations as being highly resistant. Finally, simulations of force field-based molecular dynamics (MD on wild type (WT) ERα) on six mERα variants (E380Q, S463P, Y537S, Y537C, Y537N, and D538G) were carried out to justify mechanism of the resistance. It was observed that these mutations increased the flexibility of the H12. A bonding analysis suggested that previously reported important residue His524 lost bonding upon mutation. Other parameters, such as PCA (principal component analysis), DCCM (dynamics cross-correlation), and FEL (free energy landscape), verified that the shortlisted mutations affect the H12 helix, which opens up the co-activator binding conformation. These results provide deep insight into the mechanism of relative resistance posed to fulvestrant due to mutations in breast cancer. This study will facilitate further understanding of the important aspects of designing specific and more effective drugs.
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http://dx.doi.org/10.3389/fmolb.2019.00159 | DOI Listing |
JCO Glob Oncol
May 2025
Department of Biochemistry, All India Institute of Medical Sciences, New Delhi, India.
Purpose: Breast cancer remains a significant public health challenge globally, as well as in India, where it is the most frequently diagnosed cancer in females. Significant disparities in incidence, mortality, and access to health care across India's sociodemographically diverse population highlight the need for increased awareness, policy reform, and research.
Design: This review consolidates data from national cancer registries, global cancer databases, and institutional findings from a tertiary care center to examine the epidemiology, clinical challenges, and management gaps specific to India.
J Med Screen
September 2025
The Cancer Registry of Norway, Department of Screening programs, Norwegian Institute of Public Health, Oslo, Norway.
ObjectiveTo study the implications of implementing artificial intelligence (AI) as a decision support tool in the Norwegian breast cancer screening program concerning cost-effectiveness and time savings for radiologists.MethodsIn a decision tree model using recent data from AI vendors and the Cancer Registry of Norway, and assuming equal effectiveness of radiologists plus AI compared to standard practice, we simulated costs, effects and radiologist person-years over the next 20 years under different scenarios: 1) Assuming a €1 additional running cost of AI instead of the €3 assumed in the base case, 2) varying the AI-score thresholds for single vs. double readings, 3) varying the consensus and recall rates, and 4) reductions in the interval cancer rate compared to standard practice.
View Article and Find Full Text PDFJ Natl Cancer Inst
September 2025
Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, United States.
Background: Among childhood cancer survivors, germline rare variants in autosomal dominant cancer susceptibility genes (AD CSGs) could increase subsequent neoplasm (SNs) risks, but risks for rarer SNs and by age at onset are not well understood.
Methods: We pooled the Childhood Cancer Survivor Study and St Jude Lifetime Cohort (median follow-up = 29.7 years, range 7.
PLoS One
September 2025
Institute of Computational Science and Technology, Guangzhou University, Guangzhou, China.
MicroRNAs (miRNAs) are critical regulators of gene expression in cancer biology, yet their spatial dynamics within tumor microenvironments (TMEs) remain underexplored due to technical limitations in current spatial transcriptomics (ST) technologies. To address this gap, we present STmiR, a novel XGBoost-based framework for spatially resolved miRNA activity prediction. STmiR integrates bulk RNA-seq data (TCGA and CCLE) with spatial transcriptomics profiles to model nonlinear miRNA-mRNA interactions, achieving high predictive accuracy (Spearman's ρ > 0.
View Article and Find Full Text PDFPLoS One
September 2025
Department of Hepatobiliary Surgery, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
Objective: This study employs integrated network toxicology and molecular docking to investigate the molecular basis underlying 4-nonylphenol (4-NP)-mediated enhancement of breast cancer susceptibility.
Methods: We integrated data from multiple databases, including ChEMBL, STITCH, Swiss Target Prediction, GeneCards, OMIM and TTD. Core compound-disease-associated target genes were identified through Protein-Protein Interaction (PPI) network analysis.