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Background: Breast cancer treatment prioritizes molecular subtypes over histologic types. However, considering the unique biological behavior of invasive lobular carcinoma (ILC), its diagnosis is crucial for patient management. Therefore, this study aimed to review breast cancer cases, focusing on the E-cadherin patterns and lobular morphology of cases misclassified in the original reports.
Methods: A comprehensive review was conducted on 481 breast cancer biopsy cases diagnosed as invasive breast carcinoma of no special type (IBC-NST) or ILC with E-cadherin staining. These cases were categorized into six groups based on tumor morphology (ductal/lobular) and E-cadherin expression pattern (membranous/loss/aberrant): (1) ductal/membranous, (2) lobular/loss, (3) lobular/aberrant, (4) mixed, (5) ductal/loss or aberrant, and (6) lobular/membranous.
Results: In 211 cases (43.8%), an E-cadherin pattern indicating ILC (loss and aberrant) was observed alongside lobular morphology, representing 5.52% of all breast cancer biopsies during the relevant period. Moreover, 181 cases (37.6%) showed a membranous pattern with ductal morphology, 4 (0.8%) were mixed IBC-NST and ILC, and 85 (17.7%) exhibited discordance between morphology and E-cadherin expression. Notably, only 25.9% (15/58) of cases in group 3, characterized by aberrant E-cadherin patterns, were initially diagnosed as ILC, highlighting a significant diagnostic discrepancy. In group 6, where membranous E-cadherin pattern was present with lobular morphology, only 3.4% (2/58) were diagnosed as ILC in the original reports, indicating diagnostic challenges in morphology and immunohistochemistry discordance. Similarly, in group 5, which had ductal morphology with loss or aberrant E-cadherin expression, the initial diagnosis rate of IBC-NST was 33.3% (9/27), reflecting the complexities in interpreting discordant cases.
Conclusions: In real-world practice, diagnosing ILC often heavily depends on E-cadherin results. This study emphasizes the need for diagnostic clarification in cases with discordance between morphology and E-cadherin patterns.
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http://dx.doi.org/10.1007/s12282-024-01649-4 | 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.