Organoids as a new model for improving regenerative medicine and cancer personalized therapy in renal diseases.

The pressure towards innovation and creation of new model systems in regenerative medicine and cancer research has fostered the development of novel potential therapeutic applications. Kidney injuries provoke a high request of organ transplants making it the most demanding system in the field of regenerative medicine. Furthermore, renal cancer frequently threaten patients' life and aggressive forms still remain difficult to treat. Ethical issues related to the use of embryonic stem cells, has fueled research on adult, patient-specific pluripotent stem cells as a model for discovery and therapeutic development, but to date, normal and cancerous renal experimental models are lacking. Several research groups are focusing on the development of organoid cultures. Since organoids mimic the original tissue architecture in vitro, they represent an excellent model for tissue engineering studies and cancer therapy testing. We established normal and tumor renal cell carcinoma organoids previously maintained in a heterogeneous multi-clone stem cell-like enriching medium. Starting from adult normal kidney specimens, we were able to isolate and propagate organoid 3D-structures composed of both differentiated and undifferentiated cells while expressing nephron specific markers. Furthermore, we were capable to establish organoids derived from cancer tissues although with a success rate inferior to that of their normal counterpart. Cancer cultures displayed epithelial and mesenchymal phenotype while retaining tumor specific markers. Of note, tumor organoids recapitulated neoplastic masses when orthotopically injected into immunocompromised mice. Our data suggest an innovative approach of long-term establishment of normal- and cancer-derived renal organoids obtained from cultures of fleshly dissociated adult tissues. Our results pave the way to organ replacement pioneering strategies as well as to new models for studying drug-induced nephrotoxicity and renal diseases. Along similar lines, deriving organoids from renal cancer patients opens unprecedented opportunities for generation of preclinical models aimed at improving therapeutic treatments.

Renal cancer: new models and approach for personalizing therapy.

BACKGROUND: Clear cell RCC (ccRCC) accounts for approximately 75% of the renal cancer cases. Surgery treatment seems to be the best efficacious approach for the majority of patients. However, a consistent fraction (30%) of cases progress after surgery with curative intent. It is currently largely debated the use of adjuvant therapy for high-risk patients and the clinical and molecular parameters for stratifying beneficiary categories. In addition, the treatment of advanced forms lacks reliable driver biomarkers for the appropriated therapeutic choice. Thus, renal cancer patient management urges predictive molecular indicators and models for therapy-decision making. METHODS: Here, we developed and optimized new models and tools for ameliorating renal cancer patient management. We isolated from fresh tumor specimens heterogeneous multi-clonal populations showing epithelial and mesenchymal characteristics coupled to stem cell phenotype. These cells retained long lasting-tumor-propagating capacity provided a therapy monitoring approach in vitro and in vivo while being able to form parental tumors when orthotopically injected and serially transplanted in immunocompromised murine hosts. RESULTS: In line with recent evidence of multiclonal cancer composition, we optimized in vitro cultures enriched of multiple tumor-propagating populations. Orthotopic xenograft masses recapitulated morphology, grading and malignancy of parental cancers. High-grade but not the low-grade neoplasias, resulted in efficient serial transplantation in mice. Engraftment capacity paralleled grading and recurrence frequency advocating for a prognostic value of our developed model system. Therefore, in search of novel molecular indicators for therapy decision-making, we used Reverse-Phase Protein Arrays (RPPA) to analyze a panel of total and phosphorylated proteins in the isolated populations. Tumor-propagating cells showed several deregulated kinase cascades associated with grading, including angiogenesis and m-TOR pathways. CONCLUSIONS: In the era of personalized therapy, the analysis of tumor propagating cells may help improve prediction of disease progression and therapy assignment. The possibility to test pharmacological response of ccRCC stem-like cells in vitro and in orthotopic models may help define a pharmacological profiling for future development of more effective therapies. Likewise, RPPA screening on patient-derived populations offers innovative approach for possible prediction of therapy response.