Recapitulating primary immunodeficiencies with expanded potential stem cells: Proof of concept with STAT1 gain of function

Background: Inborn errors of immunity (IEI) often lack specific disease models and personalized management. Signal transducer and activator of transcription (STAT)-1 gain of function (GoF) is such example of an IEI with diverse clinical phenotype with unclear pathomechanisms and unpredictable response to therapy. Limitations in obtaining fresh samples for functional testing and research further highlights the need for patient-specific ex vivo platforms.

Objective: Using STAT1-GoF as an example IEI, we investigated the potential of patient-derived expanded potential stem cells (EPSC) as an ex vivo platform for disease modeling and personalized treatment.

Methods: We generated EPSC derived from individual STAT1-GoF patients. STAT1 mutations were confirmed with Sanger sequencing. Functional testing including STAT1 phosphorylation/dephosphorylation and gene expression with or without Janus activating kinase inhibitors were performed. Functional tests were repeated on EPSC lines with GoF mutations repaired by CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9) editing.

Results: EPSC were successfully reprogrammed from STAT1-GoF patients and expressed the same pluripotent makers as controls, with distinct morphologic differences. Patient-derived EPSC recapitulated the functional abnormalities of index STAT1-GoF patients with STAT1 hyperphosphorylation and increased expression of STAT1 and its downstream genes (IRF1, APOL6, and OAS1) after IFN-γ stimulation. Addition of ruxolitinib and baricitinib inhibited STAT1 hyperactivation in STAT1-GoF EPSC in a dose-dependent manner, which was not observed with tofacitinib. Corrected STAT1 phosphorylation and downstream gene expression were observed among repaired STAT1-GoF EPSC cell lines.

Conclusion: This proof-of-concept study demonstrates the potential of our patient-derived EPSC platform to model STAT1-GoF. We propose this platform when researching, recapitulating, and repairing other IEI in the future.