Ursolic Acid Inhibits Collective Cell Migration and Promotes JNK-Dependent Lysosomal Associated Cell Death in Glioblastoma Multiforme Cells.
Gillian Eileen ConwayDeimante ZizyteJulie Rose Mae MondalaZhonglei HeLorna LynamMathilde LecourtCarlos BarciaOrla HoweJames Francis CurtinPublished in: Pharmaceuticals (Basel, Switzerland) (2021)
Ursolic acid (UA) is a bioactive compound which has demonstrated therapeutic efficacy in a variety of cancer cell lines. UA activates various signalling pathways in Glioblastoma multiforme (GBM) and offers a promising starting point in drug discovery; however, understanding the relationship between cell death and migration has yet to be elucidated. UA induces a dose dependent cytotoxic response demonstrated by flow cytometry and biochemical cytotoxicity assays. Inhibitor and fluorescent probe studies demonstrate that UA induces a caspase independent, JNK dependent, mechanism of cell death. Migration studies established that UA inhibits GBM collective cell migration in a time dependent manner that is independent of the JNK signalling pathway. Cytotoxicity induced by UA results in the formation of acidic vesicle organelles (AVOs), speculating the activation of autophagy. However, inhibitor and spectrophotometric analysis demonstrated that autophagy was not responsible for the formation of the AVOs. Confocal microscopy and isosurface visualisation determined co-localisation of lysosomes with the previously identified AVOs, thus providing evidence that lysosomes are likely to be playing a role in UA induced cell death. Collectively, our data identify that UA rapidly induces a lysosomal associated mechanism of cell death in addition to UA acting as an inhibitor of GBM collective cell migration.
Keyphrases
- cell death
- cell migration
- cell cycle arrest
- drug discovery
- fluorescent probe
- flow cytometry
- induced apoptosis
- signaling pathway
- machine learning
- squamous cell carcinoma
- high throughput
- endoplasmic reticulum stress
- cell proliferation
- high glucose
- mass spectrometry
- single cell
- deep learning
- big data
- liquid chromatography