Reduced Graphene Oxide Modulates the FAK-Dependent Signaling Pathway in Glioblastoma Multiforme Cells In Vitro.
Jaroslaw SzczepaniakMalwina SosnowskaMateusz WierzbickiOlga Witkowska-PiłaszewiczBarbara StrojnyJoanna JagielloWiktoria FraczekMarcin KusmierzMarta GrodzikPublished in: Materials (Basel, Switzerland) (2022)
Aggressive invasiveness is a common feature of malignant gliomas, despite their high level of tumor heterogeneity and possible diverse cell origins. Therefore, it is important to explore new therapeutic methods. In this study, we evaluated and compared the effects of graphene (GN) and reduced graphene oxides (rGOs) on a highly invasive and neoplastic cell line, U87. The surface functional groups of the GN and rGO flakes were characterized by X-ray photoelectron spectroscopy. The antitumor activity of these flakes was obtained by using the neutral red assay and their anti-migratory activity was determined using the wound healing assay. Further, we investigated the mRNA and protein expression levels of important cell adhesion molecules involved in migration and invasiveness. The rGO flakes, particularly rGO/ATS and rGO/TUD, were found highly toxic. The migration potential of both U87 and Hs5 cells decreased, especially after rGO/TUD treatment. A post-treatment decrease in mobility and FAK expression was observed in U87 cells treated with rGO/ATS and rGO/TUD flakes. The rGO/TUD treatment also reduced β-catenin expression in U87 cells. Our results suggest that rGO flakes reduce the migration and invasiveness of U87 tumor cells and can, thus, be used as potential antitumor agents.
Keyphrases
- reduced graphene oxide
- induced apoptosis
- gold nanoparticles
- signaling pathway
- cell cycle arrest
- endoplasmic reticulum stress
- poor prognosis
- single cell
- high resolution
- magnetic resonance imaging
- machine learning
- pi k akt
- computed tomography
- combination therapy
- epithelial mesenchymal transition
- wound healing
- magnetic resonance
- mesenchymal stem cells
- high grade
- ionic liquid
- mass spectrometry
- neural network
- walled carbon nanotubes
- atomic force microscopy