SRBD1 Regulates the Cell Cycle, Apoptosis, and M2 Macrophage Polarization via the RPL11-MDM2-p53 Pathway in Glioma.
Hongfu ChenShuping GaoPeng WangManyi XieHui ZhangYuechao FanEr NieQing LanPublished in: Environmental toxicology (2024)
Low expression of certain ribosomal proteins leads to the inactivation of p53, which is mediated mainly by RPL5 or RPL11 (ribosomal protein L11). It is also unknown what mechanisms drive aberrant ribosomal proteins expression in tumor. SRBD1 (S1 RNA-binding domain 1), as a highly conserved RNA-binding protein, is lowly expressed in glioma tissues and correlated with glioma prognosis. In this study, we observed that SRBD1 was closely related to p53 signaling. The upregulation of SRBD1 elevated p53 levels, thereby activating the p53 signaling pathway. As an RNA bind protein, SRBD1 could bind to the 5'-UTR of target genes and regulate RNA translation. We further conducted RNA immunoprecipitation using anti-SRDB1 antibody and noticed 29 hub RNA, including RPL11. RPL11 could inhibit MDM2-mediated p53 ubiquitination. SRBD1 upregulation promoted RPL11 binding to MDM2 via elevating RPL11 protein levels, which in turn activated the p53 signaling. Disrupting the p53 signaling blocked SRBD1-induced glioma suppression. In mouse xenograft model, SRBD1 ectopic expression was effective in reducing the total M2 tumor-associated macrophages (TAMs) density and suppressed glioma tumor growth. In summary, these data show that SRBD1 has a critical role in inhibition of glioma tumor growth and M2 macrophage polarization, and targeting RPL11-MDM2-p53 signaling may be an effective strategy to improve therapy and survival for glioma patients.
Keyphrases
- binding protein
- poor prognosis
- signaling pathway
- cell cycle
- cell proliferation
- nucleic acid
- end stage renal disease
- chronic kidney disease
- protein protein
- small molecule
- gene expression
- stem cells
- genome wide
- amino acid
- mesenchymal stem cells
- endoplasmic reticulum stress
- cell death
- pi k akt
- drug induced
- induced apoptosis
- cancer therapy
- sensitive detection
- deep learning
- living cells
- free survival
- fluorescent probe