Abstract

Animal models are a valuable tool in preclinical research. However, limited predictivity of human biological responses in the conventional models has stimulated the search for reliable preclinical tools that show translational robustness. Here, we used precision-cut kidney slices (PCKS) as a model of renal fibrosis and investigated its predictive capacity for screening the effects of anti-fibrotics. Murine and human PCKS were exposed to TGFβ or PDGF pathway inhibitors with established anti-fibrotic efficacy. For each treatment modality, we evaluated whether it affected: (1) culture-induced collagen type I gene expression and interstitial accumulation; (2) expression of markers of TGFβ and PDGF signaling; and (3) expression of inflammatory markers. We summarized the outcomes of published in vivo animal and human studies testing the three inhibitors in renal fibrosis, and drew a parallel to the PCKS data. We showed that the responses of murine PCKS to anti-fibrotics highly corresponded with the known in vivo responses observed in various animal models of renal fibrosis. Moreover, our results suggested that human PCKS can be used to predict drug efficacy in clinical trials. In conclusion, our study demonstrated that the PCKS model is a powerful predictive tool for ex vivo screening of putative drugs for renal fibrosis.

Highlights

  • Animal models are powerful tools in the study of disease mechanisms and preclinical development of therapeutics

  • We showed that the anti-fibrotic activity of pirfenidone, galunisertib, and imatinib tested in a 2D system of primary human renal fibroblasts was largely reflected in human precision-cut kidney slices (PCKS), a 3D ex vivo model

  • We showed that injury inflicted by slice preparation and sustained by culturing for 48 h affects the transcriptional program of PCKS, dictating faster changes in gene regulation in murine PCKS compared to human PCKS

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Summary

Introduction

Animal models are powerful tools in the study of disease mechanisms and preclinical development of therapeutics. Modeling human disease, such as chronic kidney disease (CKD), is a very challenging task [1]. CKD is a major global health concern characterized by the progressive loss of renal function [2]. Irrespective of etiology, renal fibrosis is a driving force in the progression of CKD and it is often regarded as the most damaging process in kidney disease [3,4]. Treatment options for CKD are limited to blood pressure regulation by renin angiotensin-aldosterone-system (RAAS) blockade, which only delay the decline in renal function [5]. No pharmacological intervention is currently available that effectively halts the progression of renal fibrosis in CKD patients

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