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Background: Circular RNAs (circRNAs) are important in tumorigenesis and cancer progression, highlighting their potential as biomarkers for diagnosis, prognosis, and treatment monitoring.
Methods: This study consists of experimental and phases. In the experimental phase, the expression of hsa_circ_0052112 in tumor and blood samples from 40 breast cancer women was analyzed, compared to the control group using Sybr Green real-time RT-PCR followed by total RNA extraction and cDNA synthesis. Statistical analysis was performed using the gene as a normalizer, compared to the normal control group as a fold change. In the phase, interactions among circRNA, RNA-Binding Proteins (RBPs), and microRNAs (miRNAs) were investigated using Interactome Database. The miRcancer database was utilized to assess breast cancer-related miRNAs linked to hsa_circ_0052112. Target miRNAs were identified with TargetScan and filtered for relevance through DisGeNET. K-means clustering grouped genes by expression patterns, visualized in Cytoscape to illustrate circRNA-miRNA-mRNA relationships. Hub genes underwent pathway enrichment analysis using Reactome database to determine their functional significance.
Results: Data revealed a significant increase in hsa_circ_0052112 expression in both blood and tumour of breast cancer patients. This increase was especially pronounced in patients with estrogen, progesterone, and HER2 receptor positivity, as well as in advanced disease stages with lymph node involvement. Enrichment analysis of hub genes indicates their role in the PI3K/AKT signaling pathway.
Conclusion: hsa_circ_0052112 shows promise as a multifaceted biomarker for breast cancer, enhancing diagnosis and prognosis; while supporting personalized treatment strategies. Further clinical validation is necessary to confirm its utility.
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http://dx.doi.org/10.18502/ajmb.v17i2.18565 | 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.