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Breast cancer is a highly heterogeneous disease that has been clinically divided into three main subtypes: estrogen receptor (ER)- and progesterone receptor (PR)-positive, human epidermal growth factor receptor 2 (HER 2)-positive, and triple-negative breast cancer (TNBC). With its high metastatic potential and resistance to endocrine therapy, HER 2-targeted therapy, and chemotherapy, TNBC represents an enormous clinical challenge. The genus is used to treat breast cancer in traditional medicine. Here, we applied aqueous extracts from two Taraxacum species, and , to compare their potential antitumor effects against three human breast cancer cell lines: MDA-MB-231 (ER, PR, and HER2), ZR-75-1 (ER, PR, and HER2), and MCF-7 (ER, PR, and HER2). Our results show that exerted cytotoxic effects against MDA-MB-231 cells, including the induction of apoptosis, the reduction of cell proliferation, the disruption of the mitochondrial membrane potential, and/or the downregulation of the oxygen consumption rate. Both and decreased cell migration and colony formation in the three cell-lines and exerted suppressive effects on MCF-7 cell proliferation based on metabolic activity and BrdU incorporation, but an enhanced proliferation of ZR-75-1 cells based on BrdU incorporation. induced ribotoxic stress in MDA-MB-231and ZR-75-1 cells; did not. In summary, these findings suggest that showed greater cytotoxicity against all three tested breast cancer cell lines, especially the TNBC MDA-MB-231 cell line.
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http://dx.doi.org/10.3390/ijms231911918 | 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.