Currently, the only treatment for end stage renal disease is dialysis or kidney transplantation. These methods contain obvious limitations such as the palliative nature of dialysis treatment and the lack of available organs for transplantation. As a result, there is a dire unmet need for alternative options. Regenerative therapies that focus on stimulating the regrowth of injured tissue can be a promising alternative. A critical step in the development of such therapeutic remedies is obtaining robust models that mimic the complex nature of the human kidney. The proximal tubules are a particular region of interest due to their important role in reabsorption and secretion of the glomerular filtrate and the blood, making them particularly susceptible to nephrotoxicity and renal pathologies. For this reason, the goal of this thesis was to engineer a 3D model of human proximal tubulogenesis that would allow for both developmental and regenerative studies. The ideal assay would mimic the human 3D structure and function of proximal tubules in a tunable, robust matrix that can be easily analyzed in throughput screenings for regenerative medicine and toxicity applications.
In this thesis, we show the development, characterization, and application of an in vitro human renal tubulogenesis model using a modular and tunable biohybrid starPEG-heparin hydrogel platform. A range of hydrogel mechanics and compositions were systematically tested to determine the optimal conditions for renal tubulogenesis. The results revealed that only soft hydrogels based on heparin and matrix metalloproteinase (MMP) enzymatically cleavable crosslinkers led to the generation of polarized tubule structures. The generated tubules display polarization markers, extracellular matrix components, and organic anion transport functions which mimic the human renal proximal tubule. To the best of our knowledge, this is the first system where human renal tubulogenesis can be monitored ex vivo from single cells to physiologically sized tubule structures in a 3D tunable matrix. Moreover, it was found that heparin played a role in the polarization of proximal tubule cells in the hydrogel culture.
The established starPEG-MMP-heparin based hydrogel model was then tested for its application as a renal tubulogenesis model by the addition of pro and anti-tubulogenic factors. It was found that the addition of growth factors and MMP inhibitors could promote and inhibit tubulogenesis, respectively. This model can be used to modulate tubulogenesis by adjusting the mechanical properties of the hydrogel, growth factor signaling, and the presence of insoluble cues (such as adhesion peptides), potentially providing new insights for regenerative therapy.
To examine if the established hydrogel-based renal tubulogenesis model could be applied as a drug toxicity platform, the nephrotoxic, chemotherapeutic drug, cisplatin was incubated with the renal tubule model. The tubular structures showed a dose-dependent drug response resembling the human clinical renal pathology. The injured tubular structures also expressed the early in vivo proximal tubule injury biomarker, kidney injury molecule-1 (KIM-1).
In conclusion, a hydrogel-based renal tubulogenesis model was successfully developed, characterized, and applied as a nephrotoxicity assay. Our findings suggest that the established hydrogel-based model can additionally be used for personalized medicine, where a patient’s predisposition to drug-induced renal injury or specific renal regenerative medicine treatments could be examined. This platform provides a novel approach to study human nephrotoxicity and renal regenerative medicine ex vivo, limiting the need for animal models, and potentially paving the way for more reliable preclinical trials.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:30305 |
| Date | 06 March 2017 |
| Creators | Weber, Heather |
| Contributors | Werner, Carsten, Murray, Patricia, Technische Universität Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
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