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Recognition of unusual histological features can augment and hasten a diagnosis but also stimulate ideas about physiological and pathological cellular interactions. Osteoclasts resorb mineralised tissue and therefore can be found at sites of heterotopic bone formation. However, multinucleated giant cells with morphological features of osteoclasts, so called ‘osteoclast-like cells’ can also be encountered in a variety of soft tissue tumours unrelated to ossification and calcification. Prompted by the presence of osteoclast-like cells in undifferentiated pleomorphic sarcoma while undertaking our Artificial Intelligence project for classifying sarcoma, we reviewed the English literature for these cells in soft tissue tumours and we found that this was poorly documented, and much was published before the release of the WHO essential diagnostic criteria in 2020. There were numerous single case reports and small series of a broad range of soft tissue tumours with osteoclast-like cells but only a limited number of diagnoses in which these cells were reported recurrently. We provide a comprehensive update of osteoclast-like cells and mineralisation in soft tissue tumours from the literature. We also present real-world incidence of osteoclast-like cells from selected tumour types in our Whole Slide Image (WSI) library of soft tissue tumours. Assessment of WSI from 1100 different patients showed that osteoclast-like cells were relatively common and under-recognised in nodular fasciitis (18.5 of 200), angiomatoid fibrous histiocytoma (17.5% of 40), undifferentiated pleomorphic sarcoma (15% of 261) and epithelioid sarcoma (9% of 68) while they were never encountered in myxofibrosarcoma (0/250) and clear cell sarcoma of soft tissue (0/80). Awareness of this phenomenon not only helps shape the differential diagnosis but also can be used to stimulate pathobiological questions and to enhance the performance of AI models for classifying disease.

Breast cancer is the leading cause of cancer-related death in women, and despite advances in preventive screening as well as in molecular classification, many patients still do not benefit from existing therapies, highlighting the importance of identifying new molecular determinants of treatment resistance. The Paired-box (PAX) family of developmental transcription factors are central regulators of tissue morphogenesis and lineage specification, yet their reactivation in tumors and contribution to breast cancer progression remain only partially defined. Here, a multi-level analysis integrating RNA sequencing and protein profiling in twenty-one primary breast carcinomas shows that distinct PAX members are directly correlated to distinct fundamental cancer hallmarks, including proliferation, cell death, epithelial–mesenchymal transition, immune evasion, and genomic instability. Specifically, PAX1 and PAX9 correlates with both cell death and proliferative markers, indicating dual roles in the regulation of cell fate. PAX1 and PAX9 correlate with both proliferative and apoptotic markers, indicating dual roles in cell fate regulation. PAX3, PAX5, and PAX8 are mainly associated with immune checkpoint expression, including PD-L1 and TIGIT, while PAX6 is linked to microsatellite instability and tumor mutational burden, implicating it in genomic dysregulation. Therefore, PAX-based molecular signatures identify that accurately predict lymph node metastasis at transcriptomic (PAX2–PAX7) levels. These findings establish PAX transcription factors as key modulators of breast cancer biology and support their potential as clinically relevant biomarkers for prognostic refinement and therapeutic stratification.