Howard M. Johnson, Ezra Neptune Noon-Song, Rea Dabelic, Chulbul M. Ahmed
Abstract
The classical model of cytokine signaling dominates our view of specific gene activation by cytokines such as the interferons (IFNs). The importance of the model extends beyond cytokines and applies to hormones such as growth hormone (GH) and insulin, and growth factors such as epidermal growth factor (EGF) and fibroblast growth factor (FGF). According to this model, ligand activates the cell via interaction with the extracellular domain of the receptor. This results in activation of receptor or receptor-associated tyrosine kinases, primarily of the Janus activated kinase (JAK) family, phosphorylation and dimerization of the signal transducer and activator of transcription (STAT) transcription factors, which dissociate from the receptor cytoplasmic domain and translocate to the nucleus. This view ascribes no further role to the ligand, JAK kinase, or receptor in either specific gene activation or the associated epigenetic events. The presence of dimeric STATs in the nucleus essentially explains it all. Our studies have resulted in the development of a non-canonical, more complex model of IFNγ signaling that is akin to that of steroid hormone (SH)/steroid receptor (SR) signaling. We have shown that ligand, receptor, activated JAKs, and STATs are associated with specific gene activation, where the receptor subunit IFNGR1 functions as a co-transcription factor and the JAKs are involved in associated epigenetic events. We found that the type I IFN system functions similarly. The fact that GH receptor, insulin receptor, EGF receptor, and FGF receptor undergo nuclear translocation upon ligand binding suggests that they may also function similarly. The SH/SR nature of type I and II IFN signaling provides insight into the specificity of signaling by members of cytokine families. The non-canonical model could also provide better understanding to more complex cytokine families such as those of IL-2 and IL-12, whose members often use the same JAKs and STATs, but also have different functions and properties.
Pharmacology, Toxicology and Pharmaceutical Science
2
5%
Engineering
2
5%
Other
3
8%
Unknown
4
11%
Attention Score in Context
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 July 2013.
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#19,944,091
of 25,373,627 outputs
Outputs from Frontiers in immunology
#22,573
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#221,304
of 288,991 outputs
Outputs of similar age from Frontiers in immunology
#240
of 503 outputs
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