High-Level Secretion of Pregnancy Zone Protein Is a Novel Biomarker of DNA Damage-Induced Senescence and Promotes Spontaneous Senescence.
Ziqi HuMingzhu ZhangJiankun FanJiandong HuGuochao LinShengwen PiaoPeng LiuJichao LiuSongbin FuWenjing SunSteven P GygiJinwei ZhangChunshui ZhouPublished in: Journal of proteome research (2023)
Identification of unique and specific biomarkers to better detect and quantify senescent cells remains challenging. By a global proteomic profiling of senescent human skin BJ fibroblasts induced by ionizing radiation (IR), the cellular level of pregnancy zone protein (PZP), a presumable pan-protease inhibitor never been linked to cellular senescence before, was found to be decreased by more than 10-fold, while the level of PZP in the conditioned medium was increased concomitantly. This observation was confirmed in a variety of senescent cells induced by IR or DNA-damaging drugs, indicating that high-level secretion of PZP is a novel senescence-associated secretory phenotype. RT-PCR examination verified that the transcription of the PZP gene is enhanced in various cells at senescence or upregulated following DNA damage treatment in a p53-independent manner. Moreover, pretreatment with late pregnancy serum containing a high level of PZP led to inhibition of doxorubicin-induced senescence in A549 cells, and depletion of PZP in the pregnancy serum could enhance such inhibition. Finally, the addition of immuno-precipitated PZP complexes into tissue culture attenuated the growth of A549 cells and promoted the spontaneous senescence. Therefore, we revealed that high-level secretion of PZP is a novel and unique feature associated with DNA damage-induced senescence, and secreted PZP is a positive regulator of cellular senescence, particularly during the late stage of gestation.
Keyphrases
- dna damage
- induced apoptosis
- endothelial cells
- oxidative stress
- cell cycle arrest
- dna repair
- stress induced
- high glucose
- preterm birth
- gene expression
- pregnancy outcomes
- preterm infants
- drug delivery
- transcription factor
- deep learning
- copy number
- machine learning
- smoking cessation
- single molecule
- circulating tumor cells
- combination therapy