CCL5, abbreviated from C-C motif chemokine ligand 5, exerts diverse regulatory effects on both the initiation and progression of breast cancer (BC), making it a focal point of extensive research within the field. By enhancing the growth, invasive ability, and metastatic potential of BC cells, simultaneously recruiting and polarizing immunosuppressive cell populations, CCL5 actively reshapes the tumor immune microenvironment. Furthermore, elevated CCL5 levels are strongly linked to particular clinicopathological parameters, worse clinical outcomes, and a higher likelihood of recurrence in BC, suggesting its value in early diagnosis and prognosis. Current preclinical studies targeting the CCL5/CCR5 axis have demonstrated notable efficacy in inhibiting the progression of BC. This article explores how CCL5 contributes to BC progression and elucidates its regulatory mechanisms, providing theoretical support and potential targets for innovative therapeutic approaches.

Breast density is one of the strongest risk factors for breast cancer and a key determinant of mammographic sensitivity, yet fundamental questions remain regarding its measurement, biology, and role in individualized risk management. The International Breast Density Workshop (IBDW) has convened biennially since 2002 to advance this field. The 11th IBDW was held in Līhue, Kaua'i, Hawai'i in June 2025, bringing together 85 unique abstracts from researchers, clinicians, and advocates representing 14 countries. The workshop was organized around five thematic sessions covering: the state of the art in risk assessment and imaging biomarkers; biological and environmental modulators of breast density; innovative technology and methods for imaging-based risk assessment; frontiers in integrating clinical, omic, and imaging biomarkers; and community engagement and health equity in screening strategies. An innovative Breast Cancer Risk Board, modeled on the clinical tumor board format, provided a forum for real-time audience engagement on individualized risk management cases. Across sessions, recurring themes included the rapid maturation of AI-based imaging biomarkers, the critical need for validation in racially and ethnically diverse populations, and the importance of standardized density measures for equitable screening recommendations. The 12th IBDW will be held in Maui, Hawai'i, June 2-4, 2027.

Accurate determination of human epidermal growth factor receptor 2 (HER2) gene amplification is a cornerstone of precision oncology in breast cancer and an expanding range of solid tumors. While immunohistochemistry (IHC) remains the first-line screening modality, in situ hybridization (ISH) techniques are essential for resolving equivocal cases and providing quantitative assessment of HER2 gene status. Among ISH methods, silver-enhanced in situ hybridization (SISH) has emerged as a clinically relevant bright-field alternative to fluorescence in situ hybridization (FISH), offering permanent staining, high concordance, and compatibility with routine histopathology workflows. Despite these advantages, SISH interpretation remains labor-intensive and subject to interobserver variability, particularly in borderline and heterogeneous tumors. The rise of digital pathology and artificial intelligence (AI) has enabled automated analysis of whole-slide images (WSIs), supporting tasks such as nuclei segmentation, signal detection, HER2 copy-number estimation, and HER2/CEP17 ratio computation. However, current evidence remains heterogeneous, with limitations including small datasets, limited external validation, and insufficient methodological transparency. This systematic review synthesizes current literature on AI-assisted HER2 assessment with a specific focus on SISH and related bright-field ISH modalities. We examine computational workflows, validation strategies, performance benchmarks, and translational readiness while critically appraising limitations in the evidence base. The analysis demonstrates that AI can support reproducible and scalable HER2 assessment when aligned with clinical guidelines, but emphasizes that clinical deployment requires rigorous validation, uncertainty-aware design, and integration with expert pathology workflows.