Patient-Derived Organoids Can Guide Personalized-Therapies for Patients with Advanced Breast Cancer.

Most breast cancers at an advanced stage exhibit an aggressive nature, and there is a lack of effective anticancer options. Herein, the development of patient-derived organoids (PDOs) is described as a real-time platform to explore the feasibility of tailored treatment for refractory breast cancers. PDOs are successfully generated from breast cancer tissues, including heavily treated specimens. The microtubule-targeting drug-sensitive response signatures of PDOs predict improved distant relapse-free survival for invasive breast cancers treated with adjuvant chemotherapy. It is further demonstrated that PDO pharmaco-phenotyping reflects the previous treatment responses of the corresponding patients. Finally, as clinical case studies, all patients who receive at least one drug predicate to be sensitive by PDOs achieve good responses. Altogether, the PDO model is developed as an effective platform for evaluating patient-specific drug sensitivity in vitro, which can guide personal treatment decisions for breast cancer patients at terminal stage.

Accelerating precision anti-cancer therapy by time-lapse and label-free 3D tumor slice culture platform.

The feasibility of personalized medicine for cancer treatment is largely hampered by costly, labor-intensive and time-consuming models for drug discovery. Herein, establishing new pre-clinical models to tackle these issues for personalized medicine is urgently demanded. Methods: We established a three-dimensional tumor slice culture (3D-TSC) platform incorporating label-free techniques for time-course experiments to predict anti-cancer drug efficacy and validated the 3D-TSC model by multiphoton fluorescence microscopy, RNA sequence analysis, histochemical and histological analysis. Results: Using time-lapse imaging of the apoptotic reporter sensor C3 (C3), we performed cell-based high-throughput drug screening and shortlisted high-efficacy drugs to screen murine and human 3D-TSCs, which validate effective candidates within 7 days of surgery. Histological and RNA sequence analyses demonstrated that 3D-TSCs accurately preserved immune components of the original tumor, which enables the successful achievement of immune checkpoint blockade assays with antibodies against PD-1 and/or PD-L1. Label-free multiphoton fluorescence imaging revealed that 3D-TSCs exhibit lipofuscin autofluorescence features in the time-course monitoring of drug response and efficacy. Conclusion: This technology accelerates precision anti-cancer therapy by providing a cheap, fast, and easy platform for anti-cancer drug discovery.

Molecular landscape and subtype-specific therapeutic response of nasopharyngeal carcinoma revealed by integrative pharmacogenomics.

Nasopharyngeal carcinoma (NPC) is a malignant head and neck cancer type with high morbidity in Southeast Asia, however the pathogenic mechanism of this disease is poorly understood. Using integrative pharmacogenomics, we find that NPC subtypes maintain distinct molecular features, drug responsiveness, and graded radiation sensitivity. The epithelial carcinoma (EC) subtype is characterized by activations of microtubule polymerization and defective mitotic spindle checkpoint related genes, whereas sarcomatoid carcinoma (SC) and mixed sarcomatoid-epithelial carcinoma (MSEC) subtypes exhibit enriched epithelial-mesenchymal transition (EMT) and invasion promoting genes, which are well correlated with their morphological features. Furthermore, patient-derived organoid (PDO)-based drug test identifies potential subtype-specific treatment regimens, in that SC and MSEC subtypes are sensitive to microtubule inhibitors, whereas EC subtype is more responsive to EGFR inhibitors, which is synergistically enhanced by combining with radiotherapy. Through combinational chemoradiotherapy (CRT) screening, effective CRT regimens are also suggested for patients showing less sensitivity to radiation. Altogether, our study provides an example of applying integrative pharmacogenomics to establish a personalized precision oncology for NPC subtype-guided therapies.