Disruption of RING and PHD Domains of TRIM28 Evokes Differentiation in Human iPSCs.
Sylwia MazurekUrszula OleksiewiczPatrycja CzerwinskaJoanna Patrycja WróblewskaMarta KlimczakMaciej WiznerowiczPublished in: Cells (2021)
TRIM28, a multi-domain protein, is crucial in the development of mouse embryos and the maintenance of embryonic stem cells' (ESC) self-renewal potential. As the epigenetic factor modulating chromatin structure, TRIM28 regulates the expression of numerous genes and is associated with progression and poor prognosis in many types of cancer. Because of many similarities between highly dedifferentiated cancer cells and normal pluripotent stem cells, we applied human induced pluripotent stem cells (hiPSC) as a model for stemness studies. For the first time in hiPSC, we analyzed the function of individual TRIM28 domains. Here we demonstrate the essential role of a really interesting new gene (RING) domain and plant homeodomain (PHD) in regulating pluripotency maintenance and self-renewal capacity of hiPSC. Our data indicate that mutation within the RING or PHD domain leads to the loss of stem cell phenotypes and downregulation of the FGF signaling. Moreover, impairment of RING or PHD domain results in decreased proliferation and impedes embryoid body formation. In opposition to previous data indicating the impact of phosphorylation on TRIM28 function, our data suggest that TRIM28 phosphorylation does not significantly affect the pluripotency and self-renewal maintenance of hiPSC. Of note, iPSC with disrupted RING and PHD functions display downregulation of genes associated with tumor metastasis, which are considered important targets in cancer treatment. Our data suggest the potential use of RING and PHD domains of TRIM28 as targets in cancer therapy.
Keyphrases
- induced pluripotent stem cells
- poor prognosis
- pluripotent stem cells
- embryonic stem cells
- stem cells
- electronic health record
- signaling pathway
- endothelial cells
- cancer therapy
- big data
- long non coding rna
- gene expression
- genome wide
- cell proliferation
- dna methylation
- machine learning
- bone marrow
- data analysis
- young adults
- squamous cell carcinoma
- oxidative stress
- artificial intelligence
- case control
- protein kinase
- deep learning
- lymph node metastasis