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2017 ; 22
(8
): 974-984
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English Wikipedia
High-Throughput Phenotypic Screening of Kinase Inhibitors to Identify Drug
Targets for Polycystic Kidney Disease
#MMPMID28644734
Booij TH
; Bange H
; Leonhard WN
; Yan K
; Fokkelman M
; Kunnen SJ
; Dauwerse JG
; Qin Y
; van de Water B
; van Westen GJP
; Peters DJM
; Price LS
SLAS Discov
2017[Sep]; 22
(8
): 974-984
PMID28644734
show ga
Polycystic kidney disease (PKD) is a prevalent disorder characterized by renal
cysts that lead to kidney failure. Various signaling pathways have been targeted
to stop disease progression, but most interventions still focus on alleviating
PKD-associated symptoms. The mechanistic complexity of the disease, as well as
the lack of functional in vitro assays for compound testing, has made drug
discovery for PKD challenging. To identify modulators of PKD, Pkd1(-/-) kidney
tubule epithelial cells were applied to a scalable and automated 3D cyst culture
model for compound screening, followed by phenotypic profiling to determine
compound efficacy. We used this screening platform to screen a library of 273
kinase inhibitors to probe various signaling pathways involved in cyst growth. We
show that inhibition of several targets, including aurora kinase, CDK, Chk,
IGF-1R, Syk, and mTOR, but, surprisingly, not PI3K, prevented forskolin-induced
cyst swelling. Additionally, we show that multiparametric phenotypic
classification discriminated potentially undesirable (i.e., cytotoxic) compounds
from molecules inducing the desired phenotypic change, greatly facilitating hit
selection and validation. Our findings show that a pathophysiologically relevant
3D cyst culture model of PKD coupled to phenotypic profiling can be used to
identify potentially therapeutic compounds and predict and validate molecular
targets for PKD.