A 3D In Vivo Model for Studying Human Renal Cystic Tissue and Mouse Kidney Slices

Cells. 2022 Jul 22;11(15):2269. doi: 10.3390/cells11152269.

Abstract

(1) Background: Autosomal dominant polycystic kidney disease (ADPKD) is a frequent monogenic disorder that leads to progressive renal cyst growth and renal failure. Strategies to inhibit cyst growth in non-human cyst models have often failed in clinical trials. There is a significant need for models that enable studies of human cyst growth and drug trials. (2) Methods: Renal tissue from ADPKD patients who received a nephrectomy as well as adult mouse kidney slices were cultured on a chorioallantoic membrane (CAM) for one week. The cyst volume was monitored by microscopic and CT-based applications. The weight and angiogenesis were quantified. Morphometric and histological analyses were performed after the removal of the tissues from the CAM. (3) Results: The mouse and human renal tissue mostly remained vital for about one week on the CAM. The growth of cystic tissue was evaluated using microscopic and CT-based volume measurements, which correlated with weight and an increase in angiogenesis, and was accompanied by cyst cell proliferation. (4) Conclusions: The CAM model might bridge the gap between animal studies and clinical trials of human cyst growth, and provide a drug-testing platform for the inhibition of cyst enlargement. Real-time analyses of mouse kidney tissue may provide insights into renal physiology and reduce the need for animal experiments.

Keywords: 3D in vivo model; ADPKD; chorioallantoic membrane (CAM) model; human renal cystic tissue; mouse kidney slices; polycystic kidney disease.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Animals
  • Cell Proliferation
  • Cysts* / pathology
  • Humans
  • Kidney / pathology
  • Mice
  • Polycystic Kidney, Autosomal Dominant*

Grants and funding

This research was funded by the Deutsche Forschungsgemeinschaft (DFG), grant number HA 6655/1-3, AU 635/1-1, BU 2918/3-1 and by the DFG, project number 387509280, SFB 1350.