Sema4C/PlexinB2 signaling controls breast cancer cell growth, hormonal dependence and tumorigenic potential.
Sreeharsha GurrapuEmanuela PupoGiulia FranzolinLetizia LanzettiLuca TamagnonePublished in: Cell death and differentiation (2018)
Semaphorin 4C (Sema4C) expression in human breast cancers correlates with poor disease outcome. Surprisingly, upon knock-down of Sema4C or its receptor PlexinB2 in diverse mammary carcinoma cells (but not their normal counterparts), we observed dramatic growth inhibition associated with impairment of G2/M phase transition, cytokinesis defects and the onset of cell senescence. Mechanistically, we demonstrated a Sema4C/PlexinB2/LARG-dependent signaling cascade that is required to maintain critical RhoA-GTP levels in cancer cells. Interestingly, we also found that Sema4C upregulation in luminal-type breast cancer cells drives a dramatic phenotypic change, with disassembly of polarity complexes, mitotic spindle misorientation, cell-cell dissociation and increased migration and invasiveness. We found that this signaling cascade is dependent on the PlexinB2 effectors ErbB2 and RhoA-dependent kinases. Moreover, Sema4C-overexpressing luminal breast cancer cells upregulated the transcription factors Snail, Slug and SOX-2, and formed estrogen-independent metastatic tumors in mice. In sum, our data indicate that Sema4C/PlexinB2 signaling is essential for the growth of breast carcinoma cells, featuring a novel potential therapeutic target. In addition, elevated Sema4C expression enables indolent luminal-type tumors to become resistant to estrogen deprivation, invasive and metastatic in vivo, which could account for its association with a subset of human breast cancers with poor prognosis.
Keyphrases
- poor prognosis
- long non coding rna
- breast cancer cells
- endothelial cells
- single cell
- transcription factor
- squamous cell carcinoma
- cell therapy
- small cell lung cancer
- epithelial mesenchymal transition
- stem cells
- cell proliferation
- binding protein
- induced pluripotent stem cells
- tyrosine kinase
- risk assessment
- adipose tissue
- cell cycle
- pluripotent stem cells
- artificial intelligence
- mesenchymal stem cells
- skeletal muscle
- human health
- big data
- machine learning
- high fat diet induced
- climate change
- insulin resistance
- estrogen receptor
- oxidative stress
- polycystic ovary syndrome
- hodgkin lymphoma