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Metadata

Name
Hippo kinases Mst1 and Mst2 sense and amplify IL-2R?STAT5 signaling in Treg cells to establish stable regulatory activity
Repository
Gene Expression Omnibus
Identifier
geo.series:GSE120711
Description
Interleukin-2 (IL-2) and downstream transcription factor STAT5 are important for maintaining regulatory T (Treg) cell homeostasis and function. Tregs can respond to low levels of IL-2, but the mechanisms by which STAT5 is activated during partial IL-2 deficiency remain uncertain. We identified the serine-threonine kinase Mst1 as a signal-dependent amplifier of IL-2?STAT5 activity in Tregs. Tregs had high Mst1 and Mst2 (Mst1?Mst2) activity that was crucial to prevent tumor resistance and autoimmunity. Mechanistically, Mst1?Mst2 sensed IL-2 signals to promote the STAT5 activation necessary for Treg cell homeostasis and lineage stability, and maintain the highly suppressive phophorylated-STAT5+ Treg cell subpopulation. Unbiased quantitative proteomics revealed an association of Mst1 with the cytoskeletal DOCK8?LRCHs module that shaped activity Rho-family GTPase Rac activity, which in turn mediated STAT5 activation in Tregs. Collectively, IL-2?STAT5 signaling critically depends upon Mst1?Mst2 functions to maintain a stable Treg cell pool and immune tolerance.
We used microarrays to compare the global transcription profiles of WT and Mst1/Mst2-null Treg cell populations
Data or Study Types
Expression profiling by array
Source Organization
National Center for Biotechnology Information
Access Conditions
available
Year
2018
Access Hyperlink
http://www.ncbi.nlm.nih.gov/sites/GDSbrowser?acc=GSE120711

Distributions

  • Encoding Format: Bioproject ; URL: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA494226
  • Encoding Format: TXT ; URL: ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE1nnn/GSE120711/matrix/
  • Encoding Format: MINiML ; URL: ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE1nnn/GSE120711/miniml/
  • Encoding Format: SOFT ; URL: ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE1nnn/GSE120711/soft/
This project was funded in part by grant U24AI117966 from the NIH National Institute of Allergy and Infectious Diseases as part of the Big Data to Knowledge program. We thank all members of the bioCADDIE community for their valuable input on the overall project.