Novel Therapeutic Approaches to Treat Brain Cancer Combining Cold Atmospheric Plasma, Therapeutic Prodrugs and Gold Nanoparticles
Notice bibliographique
Résumé
Glioblastoma Multiforme (GBM) makes up approximately 45% of all primary brain tumours. State of the art treatment at present involves concurrent and adjuvant temozolomide (TMZ) with radical radiotherapy which extends median survival from 12.1 months (radical radiotherapy alone) to 14.6 months according to the study of the European Organization for Research and Treatment of Cancer (EORTC) Brain Tumour and Radiotherapy Groups and the National Cancer Institute of Canada (NCIC) Clinical Trials Group. Meanwhile, National Cancer Registry Ireland presented that GBM represents over 40% of all malignant brain tumours and had the worst five-year net survival (4%) compared to overall malignant brain cancer (five-year net survival, 19%) in Ireland. Long term survival of patients with GBM has not been significantly improved in the last 20 years. GBM tumours also have presented high level of resistance to normal treatments. Therefore, novel therapies to treat GBM are urgently needed. This study aimed to investigate efficient therapeutic methods by combining novel interventions, including cold atmospheric plasma (CAP), gold nanoparticles (AuNPs) and specific chemotherapeutic compounds to overcome the barriers of GBM treatment. Over the past decade CAP has emerged as a novel approach in health care area, especially cancer therapy. CAP generates chemically active species such as reactive oxygen species (ROS) and reactive nitrogen species (RNS) and has been demonstrated to act in synergy with a selection of traditional chemotherapeutic compounds which could reduce the effective concentrations of drugs needed at the tumour and may allow for targeted toxicity at sites exposed to the plasma field. AuNPs, well known as biocompatible drug delivery and diagnosis agents for cancer therapy, have been demonstrated to have synergistic anti cancer effects in combination with CAP treatment. In this project, for the first time, we investigated and described the detailed mechanism iii behind the synergistic anti-cancer effects between AuNPs and CAP treatment. Chapter 2 and Chapter 3 demonstrated that low dose treatment of CAP treatment was capable of promoting the uptake of AuNPs into glioblastoma U373MG cells via stimulated membrane repair clathrin-dependent endocytosis. The intracellular accumulation of AuNPs was tracked using atomic absorbance spectrometry (AAS) and simulated with numerical modelling to identify the enhanced uptake routine. AuNPs were tracked into early endosomes, late endosomes and finally lysosomes using specific fluorescent probes and confocal microscope. The lipid oxidation of cancer cells induced by CAP treatment was confirmed by various methods, including confocal microscopy, Thiobarbituric Acid Reactive Substances (TBARS) assay and flow cytometry. Meanwhile, the related endocytosis pathway was determined to be clathrin dependent using multiple clathrin and caveola specific inhibitors and clathrin siRNA. In Chapter 4, we performed the screening of 47 prodrug candidates for their cytotoxicity against U373MG cells in combination with CAP treatment. The selection of chemotherapeutic compounds provided by collaborators have been tested to determine dose response curves with or without CAP treatment using Alamar Blue assay, thus, to characterise their synergistic potential in combination with CAP. Two leading candidates which showed significant cytotoxicity with CAP, have been identified from 47 compounds. Furthermore, the mechanism behind the synergistic cytotoxicity between one of the leading candidates, JW-04-061, and CAP treatment has been investigated. It has been demonstrated that reactive species, especially short-lived species, generated in culture medium may play a main role in the oxidation and activation of the prodrug during CAP treatment.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».