Differential Antiproliferative Effects Of Cannabidiol (Cbd) In The Core And Infiltrative Boundary Of Human Glioblastoma Cells
Abassi-Rana, G.; Calle, Y.; Molina-Holgado, F.
Show abstract
BackgroundWe have previously reported that the brain cannabinoid signalling pathways regulates in the isocitrade dehydrogenase-1 wild-type glioblastoma (GBM) core and infiltrative boundary tumor cell proliferation. To uncover the mechanism behind these effects we have investigated the possible antitumoral actions of cannabidiol (CBD) in the tumour core cells (U87) and the Glioma Invasive Margin cells (GIN-8), the latter representing a better proxy of post-surgical residual disease. MethodsMonolayer of GBM cells cultures were treated with increasing concentrations of CBD, Temozolomide (TMZ), Carmustine (BCUN), Fluoxetine, Doxorubicine (DOX) or vehicle. After treatment, cell viability was assessed using an MTT kit assay to evaluate mitochondrial activity/cell proliferation, cytotoxicity was evaluated by LDH release. In addition, we have investigated the effects of the CBD alone or in combination with the above drugs on the autophagic cell death, unfold protein response (UPR) mitochondrial response and release of proinflammatory cytokines. SummaryThis study highlights the potential therapeutic relevance of CBD in combination with other FDA-approved drugs against glioblastoma. We observed strong synergism between CBD and TMZ, FX, and DOXO in reducing U87-MG cell viability in vitro, with even stronger synergy between CBD and TMZ in GIN-8 cells. Our preliminary data identify CBD as a potential anti-neoplastic drug in both core and invasive margin cells. Given the heterogeneity of glioblastoma, further studies will elucidate the molecular mechanisms underlying CBD observed anti-tumoral actions and determine whether it can potentially be used in the future as an addition to current therapies.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Preclinical assessment of MAGMAS inhibitor as a potential therapy for pediatric medulloblastoma 95%
- Changes in the tumor microenvironment and treatment outcome in glioblastoma: A pilot study 95%
- The biotoxin BMAA promotes dysfunction via distinct mechanisms in neuroblastoma and glioblastoma cells 95%
Similar papers in this journal
- Novel kinome profiling technology reveals drug treatment is patient and 2D/3D model dependent in GBM 94%
- Augmentation of extracellular ATP synergizes with chemotherapy in triple negative breast cancer 94%
- A pro-oxidant combination of resveratrol and copper down-regulates hallmarks of cancer and immune checkpoints in patients with advanced oral cancer: Results of an exploratory study (RESCU 004) 94%
Similar papers in this journal
- Thermal cycling-hyperthermia attenuates rotenone-induced cell injury in SH-SY5Y cells through heat-activated mechanisms 94%
- Protein profiling of WERI RB1 and etoposide resistant WERI ETOR reveals new insights into topoisomerase inhibitor resistance in retinoblastoma 93%
- NDR2 Kinase Regulate Microglial Metabolic Adaptation and Inflammatory Response: Critical Role in Glucose-Dependent Functional Plasticity 93%
Similar papers in this journal
- Ursolic acid inhibits cell migration and promotes JNK-dependent lysosomal associated cell death in Glioblastoma multiforme cells 98%
- Augmented efficacy of uttroside B over sorafenib in a murine model of human hepatocellular carcinoma 93%
- MiR-182-5p regulates Nogo-A expression and promotes neurite outgrowth of hippocampal neurons in vitro 93%
Similar papers in this journal
- Elevated intracellular cAMP concentration mediates growth suppression in glioma cells 92%
- Transcriptional activation of cyclin D1 via HER2/HER3 contributes to cell survival and EGFR tyrosine kinase inhibitor resistance in non-small cell lung carcinoma 92%
- Ribosomal protein L5 (RPL5/uL18) I60V mutation is associated to increased translation and modulates drug sensitivity in T-cell acute lymphoblastic leukemia cells 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.