henhaobio
Sign in

bioRxivImmunology

High-throughput Screening with Pluripotent Stem Cells Identifies CUDC-907 as an Effective Compound for Restoring the Proinflammatory Phenotype of Nakajo-Nishimura Syndrome

N. Kase, M. Terashima, A. Ohta, A. Niwa, F. Honda-Ozaki, Y. Kawasaki, T. Nakahata, N. Kanazawa, M. Saito

PDFDOIPreprint

Abstract

Nakajo-Nishimura syndrome (NNS) is an autoinflammatory disorder caused by a homozygous mutations in PSMB8 gene. The administration of systemic corticosteroids is partially effective, but continuous treatment causes severe side effects. We previously established a pluripotent stem cell (PSC)-derived NNS disease model that reproduces several inflammatory phenotypes including the overproduction of monocyte chemoattractant protein-1 (MCP-1) and interferon gamma-induced protein-10 (IP-10). Here we performed high-throughput compound screening (HTS) using this PSC-derived NNS model to find potential therapeutic candidates and identified CUDC-907 as an effective inhibitor of the release of MCP-1 and IP-10. CUDC-907 did not induce cell death within therapeutic concentrations and was also effective on primary patient cells. Further analysis indicated that the inhibitory effect was post-transcriptional. These findings suggest that HTS with PSC-derived disease models is useful for finding drug candidates for autoinflammatory diseases. Significance statementIn this study, we identified a histone deacetylase inhibitor CUDC-907 as a potential effective compound for ameliorating overproduction of inflammatory chemokines in an autoinflammatory disease named Nakajo-Nishimura syndrome. We performed high-throughput screening using pluripotent stem cell-derived monocytic cell lines. Our data prove the validity of screening system as a versatile platform for seeking candidate compounds for the treatment of congenital immunological disorders associated with monocytic lineage cells.

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISToldo '26Kaur '26Low '24Schlotfeldt '26Li '25Kinder '20
56% semantic matchSystems Biology
Stefano A Toldo, Dror Luger, Aimee E. Vozenilek+12 more·bioRxiv·Mar 31, 2026