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Metadata

Name
PAX3-FOXO1 suppresses cellular senescence through RASSF4-mediated restraint of the mammalian Hippo/MST1 pathway
Repository
Gene Expression Omnibus
Identifier
geo.series:GSE40543
Description
Alveolar rhabdomyosarcoma (aRMS) is an aggressive sarcoma of skeletal muscle characterized by expression of the PAX3-FOXO1 fusion gene. Despite its discovery over almost 20 years ago, PAX3-FOXO1 remains an enigmatic tumor driver. Previously, we reported that PAX3-FOXO1 supports aRMS initiation by enabling bypass of cellular senescence. Here, we show that bypass occurs in part by PAX3-FOXO1-mediated upregulation of RASSF4, a Ras-association domain family (RASSF) member, which then suppresses the evolutionarily conserved mammalian Hippo/Mst1 pathway. RASSF4 loss-of-function activates Hippo/Mst1 and inhibits downstream YAP, causing aRMS cell cycle arrest and senescence. This is the first evidence for an oncogenic role for RASSF4, and a novel mechanism for Hippo signaling suppression in human cancer.
Human skeletal muscle myoblasts (HSMMs) were retrovirally transduced with either an empty vector (Vp, pK1) or PAX3-FOXO1 (PFp, pK1-PAX3-FOXO1) and selected on puromycin. Presenescent (presen) cells were harvested before the senescence checkpoint. Since cells expressing PAX3-FOXO1 can bypass the senescence checkpoint, postsenescent (postsen) cells expressing PAX3-FOXO1 were also harvested.
Data or Study Types
Expression profiling by array
Source Organization
National Center for Biotechnology Information
Access Conditions
available
Year
2014
Access Hyperlink
http://www.ncbi.nlm.nih.gov/sites/GDSbrowser?acc=GSE40543

Distributions

  • Encoding Format: Bioproject ; URL: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA174363
  • Encoding Format: TXT ; URL: ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE1nnn/GSE40543/matrix/
  • Encoding Format: MINiML ; URL: ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE1nnn/GSE40543/miniml/
  • Encoding Format: SOFT ; URL: ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE1nnn/GSE40543/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.