Breast cancer is the leading cause of cancer-related death in women worldwide ¹ . Here, in the Breast Cancer-Anti-Progestin Prevention Study 1 (BC-APPS1; NCT02408770 ), we assessed whether progesterone receptor antagonism with ulipristal acetate for 12 weeks reduces surrogate markers of breast cancer risk in 24 premenopausal women. We used multilayered OMICs and live-cell approaches as readouts for molecular features alongside clinical imaging and tissue micromechanics correlates. Ulipristal acetate reduced epithelial proliferation (Ki67) and the proportion, proliferation and colony formation capacity of luminal progenitor cells, the putative cell of origin of aggressive breast cancers ² . MRI scans showed reduction in fibroglandular volume with treatment, whereas single-cell RNA sequencing, proteomics, histology and atomic force microscopy identified extracellular matrix remodelling with reduced collagen organization and tissue stiffness. Collagen VI was the most significantly downregulated protein after ulipristal acetate treatment, and we uncovered an unanticipated spatial association between collagen VI and SOX9 ^high luminal progenitor cell localization, establishing a link between collagen organization and luminal progenitor activity. Culture of primary human breast epithelial cells in a stiff environment increased luminal progenitor activity, which was antagonized by anti-progestin therapy, strengthening this mechanistic link. This study offers a template for biologically informed early-phase therapeutic cancer prevention trials and demonstrates the potential for premenopausal breast cancer prevention with progesterone receptor antagonists through stromal remodelling and luminal progenitor suppression.

CD19-targeted therapies, including monoclonal antibodies, antibody–drug conjugates, and chimeric antigen receptor (CAR) T-cell products, have significantly improved outcomes in relapsed/refractory diffuse large B-cell lymphoma (R/R DLBCL). Despite their clinical efficacy, resistance and antigen modulation pose substantial challenges, especially in patients requiring sequential therapy. This review provides a comprehensive overview of CD19 biology and its relevance as a therapeutic target. We examine mechanisms of resistance such as antigen loss, epitope masking, and T-cell exhaustion, as well as the implications of tumor microenvironmental immunosuppression. Future efforts should prioritize the integration of real-time diagnostics, such as flow cytometry, immunohistochemistry, and transcriptomic profiling, and AI-assisted predictive models to optimize therapeutic sequencing and expand access to personalized immunotherapy.

Despite major advances in high-throughput genomics, proteomics, and multimodal imaging, a substantial gap persists between molecular tumor characterization and clinically actionable therapeutic decision-making, partly due to the limitations of conventional preclinical models in capturing tumor heterogeneity and predicting patient-specific drug response. Patient-derived organoids (PDO) have emerged as a promising platform to bridge this gap by enabling functional interrogation of individual tumors in a physiologically relevant three-dimensional context. PDO retain the genomic, transcriptomic, and histopathological features of their parental tumors while supporting long-term expansion, biobanking, and high-throughput pharmacological testing. In this review, we provide a clinically oriented overview of PDO technology as a key tool in functional precision oncology, summarizing current methodologies for tissue processing, organoid derivation, and quality control. We examine applications across multiple cancer types, including drug screening, radiotherapy response modeling, immuno-oncology co-culture systems, and CRISPR-based functional genomics, highlighting their role in directly measuring therapeutic vulnerability. We also integrate tumor-specific evidence across major malignancies, including colorectal, pancreatic, and breast cancers, where PDO-based pharmacotyping shows strong concordance with clinical outcomes and is increasingly incorporated into prospective trials. Finally, we discuss the integration of PDO with emerging technologies, including organoid-on-chip systems, artificial intelligence-driven analytics, and hospital-integrated workflows, as a critical innovation layer that is redefining their clinical applicability. These integrative approaches move PDO beyond static ex vivo models toward dynamic, and decision-support systems, with the potential to substantially enhance predictive accuracy and real-time therapeutic stratification. Collectively, these advances position PDOs as a promising component in next-generation precision oncology, supporting a transition from static genomics-based stratification toward dynamic, functionally guided therapeutic decision-making.

Obesity is increasingly recognized as a systemic immunometabolic disorder that influences lymphoma risk, tumor biology, treatment response, and survivorshi

The development of patient-derived organoids (PDOs) has substantially advanced the study of gastrointestinal diseases by providing three-dimensional human models that faithfully recapitulate the structural, molecular, and functional characteristics of native tissues. Unlike conventional two-dimensional cultures and animal models, intestinal organoids preserve epithelial architecture, cellular heterogeneity, and patient-specific genetic features, enabling more physiologically relevant investigations of gastrointestinal physiology and disease. Recent technological advances, including co-culture systems, organoid-derived monolayers, and organ-on-chip platforms, have further expanded their ability to model epithelial interactions with immune cells, stromal components, and the gut microbiota. These developments have facilitated mechanistic studies of epithelial barrier function, host–microbiota communication, microbial metabolites, and endocrine signaling, while also supporting translational applications in inflammatory bowel disease, infectious disorders, inherited gastrointestinal diseases, and gastrointestinal cancers. Moreover, patient-derived organoids have emerged as promising platforms for drug screening, biomarker discovery, precision medicine, and regenerative therapies. Despite these advances, several challenges remain, including limited representation of the native tissue microenvironment, lack of standardized culture protocols, scalability, and regulatory issues that currently restrict routine clinical implementation. This review summarizes recent progress in gastrointestinal organoid technology, highlighting current applications, emerging experimental platforms, and future perspectives for integrating organoid-based models into translational research and personalized medicine.