STAT1 gain-of-function heterozygous cell models reveal diverse interferon-signature gene transcriptional responses
Abstract Signal transducer and activator of transcription 1 (STAT1) gain-of-function (GOF) is an autosomal dominant immune disorder marked by wide infectious predisposition, autoimmunity, vascular disease, and malignancy. Its molecular hallmark, elevated phospho-STAT1 (pSTAT1) following interferon (...
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| Autores principales: | , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/f8847bc7541a4ab68fbd2ae0e0ec203f |
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| Sumario: | Abstract Signal transducer and activator of transcription 1 (STAT1) gain-of-function (GOF) is an autosomal dominant immune disorder marked by wide infectious predisposition, autoimmunity, vascular disease, and malignancy. Its molecular hallmark, elevated phospho-STAT1 (pSTAT1) following interferon (IFN) stimulation, is seen consistently in all patients and may not fully account for the broad phenotypic spectrum associated with this disorder. While over 100 mutations have been implicated in STAT1 GOF, genotype–phenotype correlation remains limited, and current overexpression models may be of limited use in gene expression studies. We generated heterozygous mutants in diploid HAP1 cells using CRISPR/Cas9 base-editing, targeting the endogenous STAT1 gene. Our models recapitulated the molecular phenotype of elevated pSTAT1, and were used to characterize the expression of five IFN-stimulated genes under a number of conditions. At baseline, transcriptional polarization was evident among mutants compared with wild type, and this was maintained following prolonged serum starvation. This suggests a possible role for unphosphorylated STAT1 in the pathogenesis of STAT1 GOF. Following stimulation with IFNα or IFNγ, differential patterns of gene expression emerged among mutants, including both gain and loss of transcriptional function. This work highlights the importance of modeling heterozygous conditions, and in particular transcription factor-related disorders, in a manner which accurately reflects patient genotype and molecular signature. Furthermore, we propose a complex and multifactorial transcriptional profile associated with various STAT1 mutations, adding to global efforts in establishing STAT1 GOF genotype–phenotype correlation and enhancing our understanding of disease pathogenesis. |
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