The adhesion-GPCR ADGRF5 fuels breast cancer progression by suppressing the MMP8-mediated antitumorigenic effects.
Yalan WuHuixia LiuZhe SunJieling LiuKai LiRonghui FanFujun DaiHui TangQi HouJinSong LiXiaolong TangPublished in: Cell death & disease (2024)
ADGRF5 (GPR116) has been identified as a facilitator of breast cancer cell migration and metastasis, yet the underlying mechanisms remain largely elusive. Our current study reveals that the absence of ADGRF5 in breast cancer cells impairs extracellular matrix (ECM)-associated cell motility and impedes in vivo tumor growth. This correlates with heightened expression of matrix metalloproteinase 8 (MMP8), a well-characterized antitumorigenic MMP, and a shift in the polarization of tumor-associated neutrophils (TANs) towards the antitumor N1 phenotype in the tumor microenvironment (TME). Mechanistically, ADGRF5 inhibits ERK1/2 activity by enhancing RhoA activation, leading to decreased phosphorylation of C/EBPβ at Thr235, hindering its nuclear translocation and subsequent activation. Crucially, two C/EBPβ binding motifs essential for MMP8 transcription are identified within its promoter region. Consequently, ADGRF5 silencing fosters MMP8 expression and CXCL8 secretion, attracting increased infiltration of TANs; simultaneously, MMP8 plays a role in decorin cleavage, which leads to trapped-inactivation of TGF-β in the TME, thereby polarizing TANs towards the antitumor N1 neutrophil phenotype and mitigating TGF-β-enhanced cell motility in breast cancer. Our findings reveal a novel connection between ADGRF5, an adhesion G protein-coupled receptor, and the orchestration of the TME, which dictates malignancy progression. Overall, the data underscore ADGRF5 as a promising therapeutic target for breast cancer intervention.
Keyphrases
- cell migration
- extracellular matrix
- single cell
- poor prognosis
- transforming growth factor
- randomized controlled trial
- binding protein
- breast cancer cells
- transcription factor
- gene expression
- dna methylation
- cell proliferation
- stem cells
- electronic health record
- cystic fibrosis
- machine learning
- big data
- epithelial mesenchymal transition
- genome wide
- fatty acid
- artificial intelligence
- deep learning