Role of gut microbiota in the pathogenesis of castration-resistant prostate cancer: a comprehensive study using sequencing and animal models.
Guowen LinFeng ZhangXiaoling WengZhe HongDingwei YeGangmin WangPublished in: Oncogene (2024)
CRPC remains a significant challenge in prostate cancer research. We aimed to elucidate the role of gut microbiota and its specific mechanisms in CRPC using a multidisciplinary approach. We analyzed 16S rRNA sequencing data from mouse fecal samples, revealing substantial differences in gut microbiota composition between CRPC and castration-sensitive prostate cancer mice, particularly in Firmicutes and Bacteroidetes. Functional analysis suggested different bacteria may influence CRPC via the α-linolenic acid metabolism pathway. In vivo, experiments utilizing mouse models and fecal microbiota transplantation (FMT) demonstrated that FMT from healthy control mice could decelerate tumor growth in CRPC mice, reduce TNF-α levels, and inhibit the activation of the TLR4/MyD88/NF-κB signaling pathway. Transcriptome sequencing identified crucial genes and pathways, with rescue experiments confirming the gut microbiota's role in modulating CRPC progression through the TLR4/MyD88/NF-κB pathway. The activation of this pathway by TNF-α has been corroborated by in vitro cell experiments, indicating its role in promoting prostate cancer cell proliferation, migration, and invasion while inhibiting apoptosis. Gut microbiota dysbiosis may promote CRPC development through TNF-α activation of the TLR4/MyD88/NF-κB signaling pathway, potentially linked to α-linolenic acid metabolism.
Keyphrases
- signaling pathway
- prostate cancer
- toll like receptor
- pi k akt
- single cell
- nuclear factor
- radical prostatectomy
- inflammatory response
- rheumatoid arthritis
- cell cycle arrest
- induced apoptosis
- cell proliferation
- immune response
- epithelial mesenchymal transition
- high fat diet induced
- lps induced
- oxidative stress
- rna seq
- cell therapy
- genome wide
- endoplasmic reticulum stress
- mouse model
- stem cells
- deep learning
- type diabetes
- metabolic syndrome
- electronic health record
- adipose tissue