Yinghui Hao , Fangmei Xie , Jieyi He , Chenqiong Gu , Ying Zhao , Wenfeng Luo , Xiaoyu Song , Jian Shen , Li Yu , Zeping Han , Jinhua He
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引用次数: 0
Abstract
Previous studies have shown that phenyllactic acid (alpha-Hydroxyhydrocinnamic acid, 2-Hydroxy-3-phenylpropionic acid, PLA), a type of organic acid metabolite, has excellent diagnostic efficacy when used to differentiate between prostate cancer, benign prostatic hyperplasia, and prostatitis. This research aims to explore the molecular mechanism by which PLA influences the PANoptosis of prostate cancer (PCa) cell lines. First, we found that PLA was detected in all prostate cancer cell lines (PC-3, PC-3 M, DU145, LNCAP). Further experiments showed that the addition of PLA to prostate cancer cells could promote ATP generation, enhance cysteine desulfurase (NFS1) expression, and reduce tumor necrosis factor alpha (TNF-α) levels, thereby inhibiting apoptosis in prostate cancer cells. Notably, overexpression of NFS1 can inhibit the binding of TNF-α to serpin mRNA binding protein 1 (SERBP1), suggesting that NFS1 competes with TNF-α for binding to SERBP1. Knockdown of SERBP1 significantly reduced the level of small ubiquity-related modifier (SUMO) modification of TNF-α. This suggests that NFS1 reduces the SUMO modification of TNF-α by competing with SERBP1, thereby reducing the expression and stability of TNF-α and ultimately inhibiting apoptosis in prostate cancer cell lines. In conclusion, PLA inhibits TNF-α induced panapoptosis of prostate cancer cells through metabolic reprogramming, providing a new idea for targeted treatment of prostate cancer.
期刊介绍:
IJBCB publishes original research articles, invited reviews and in-focus articles in all areas of cell and molecular biology and biomedical research.
Topics of interest include, but are not limited to:
-Mechanistic studies of cells, cell organelles, sub-cellular molecular pathways and metabolism
-Novel insights into disease pathogenesis
-Nanotechnology with implication to biological and medical processes
-Genomics and bioinformatics