UDP-glucose dehydrogenase expression is upregulated following EMT and differentially affects intracellular glycerophosphocholine and acetylaspartate levels in breast mesenchymal cell lines.
Qiong WangSigurdur Trausti KarvelssonFreyr JohannssonArnar Ingi VilhjalmssonLars HagenDavi de Miranda FonsecaAnimesh SharmaGeir SlupphaugÓttar RolfssonPublished in: Molecular oncology (2022)
Metabolic rewiring is one of the indispensable drivers of epithelial-mesenchymal transition (EMT) involved in breast cancer metastasis. In this study, we explored the metabolic changes during spontaneous EMT in three separately established breast EMT cell models using a proteomic approach supported by metabolomic analysis. We identified common proteomic changes, including the expression of CDH1, CDH2, VIM, LGALS1, SERPINE1, PKP3, ATP2A2, JUP, MTCH2, RPL26L1 and PLOD2. Consistently altered metabolic enzymes included the following: FDFT1, SORD, TSTA3 and UDP-glucose dehydrogenase (UGDH). Of these, UGDH was most prominently altered and has previously been associated with breast cancer patient survival. siRNA-mediated knock-down of UGDH resulted in delayed cell proliferation and dampened invasive potential of mesenchymal cells and downregulated expression of the EMT transcription factor SNAI1. Metabolomic analysis revealed that siRNA-mediated knock-down of UGDH decreased intracellular glycerophosphocholine (GPC), whereas levels of acetylaspartate (NAA) increased. Finally, our data suggested that platelet-derived growth factor receptor beta (PDGFRB) signalling was activated in mesenchymal cells. siRNA-mediated knock-down of PDGFRB downregulated UGDH expression, potentially via NFkB-p65. Our results support an unexplored relationship between UGDH and GPC, both of which have previously been independently associated with breast cancer progression.
Keyphrases
- epithelial mesenchymal transition
- poor prognosis
- growth factor
- stem cells
- induced apoptosis
- cell proliferation
- bone marrow
- transforming growth factor
- transcription factor
- binding protein
- cell cycle arrest
- single cell
- cancer therapy
- long non coding rna
- endoplasmic reticulum stress
- cell death
- big data
- hyaluronic acid
- young adults
- oxidative stress
- deep learning
- electronic health record
- cell cycle
- human health
- artificial intelligence