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Tinospora cordifolia (Willd.) Miers is a medicinal plant recognised for its pharmacological potential. This work presents the development of an innovative nano-liposomal formulation and assesses its anticancer efficacy against breast cancer cell lines. A sustainable green extraction method was employed to isolate bioactive compounds from T. cordifolia, followed by the development of a nano-liposomal formulation. Particle size and morphology were assessed using field emission scanning electron microscopy (FESEM), revealing soft, globular vesicles with an average diameter of ~ 153 nm. GC-MS profiling identified 35 phytoconstituents subjected to molecular docking against topoisomerase IIα to predict anticancer potential. The biological activity of the formulation was validated through MTT assay for cell viability, scratch assay for cell migration, and apoptosis assays in MCF-7 and MDA MB 231 breast cancer cell lines. Immunocytochemistry was used to evaluate the expression of Bcl-2, cytochrome-C, and caspase-3. ROS generation was also quantified to confirm the mechanism of action. In silico analysis identified glucobrassicin as a potent topoisomerase IIα inhibitor (docking score: - 10.2655). The formulation exhibited dose-dependent cytotoxicity, inhibited cell migration, and induced apoptosis in both cell lines. ROS-mediated cell death was associated with increased cytochrome-C and caspase-3 expression and decreased Bcl-2 levels. This study underscores the value of integrating green nanotechnology, computational docking, and functional cell-based assays to identify and characterise the bioactive phytochemicals. The T. cordifolia-based liposomal formulation demonstrated promising anticancer activity and warrants further preclinical evaluation as a candidate for breast cancer therapy.
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http://dx.doi.org/10.1007/s12032-025-02777-3 | 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.