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Enregistrement W6998608459

Antibody and Anticancer Drug Functionalised Gold Nanoparticles as Novel and Potential Immunotherapeutic Agents for Targeted Biological Treatment Against Cancers

2023· dissertation· en· W6998608459 sur OpenAlexaboutno aff

Notice bibliographique

RevueThe Sydney eScholarship Repository (The University of Sydney) · 2023
Typedissertation
Langueen
DomaineMedicine
ThématiqueCancer Research and Treatment
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMonoclonal antibodyDrugDrug deliveryContext (archaeology)Colloidal goldCancerCancer immunotherapyAntibodyAdjuvant
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Biological therapeutic approaches are important in the context of pharmacological development and innovation. As the area of molecular biology keeps expanding rapidly, new methods and approaches are becoming available for the development of novel biopharmaceuticals and the refinement of existing biological therapies. This thesis explores an empirical study of the functionalisation of two different antibodies (nimotuzumab and trastuzumab) (chapter 3 and 4, respectively) and one thiol-containing anticancer drug (mertansine, analogue of maytansine) with dual antibodies onto a gold nanoparticle surface (chapter 5) for addressing the key challenges and potentialities of innovative immunotherapeutics. Massive interest in nanoparticle exploration, particularly concerning its medicinal implications, has been prompted by recent developments in nanotechnology. Numerous nanoparticles in diverse forms, sizes, and composites now show great potential for cancer treatment. Nanoparticles were used in specific target biological drug delivery vehicles and adjuvants for improving the administration of antibodies and thiolate anticancer drugs conjugated antibodies to specific receptors, by accumulating them due to increased permeability and retention effect (EPR) of cancer tissue. Because of their simplicity in synthesis, simple surface functionalisation, adjuvant capabilities, effective bioconjugation, probable non-cytotoxicity, tuneable and improved scattering, and absorption properties, gold nanoparticles (AuNPs) have significant advantages in cancer applications when compared to other nanoparticles. 
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\nWorldwide, cancer is a major incidence of death. United States Food and Drug Administration (US FDA) initially authorised monoclonal antibody (mAb) in 1986 and especially for cancer treatment in 1997. Monoclonal antibodies account for the majority of biological drugs now being researched in clinical studies. Antibody-related drugs (e.g., antibody-drug conjugates, antibody fragments, bispecific antibodies) and full-size therapeutic mAbs have become the most popular agents in the biopharmaceutical sector and are now being researched in clinical studies. At present, U.S. FDA, Swissmedic, Australia TGA, European Medicines Agency (EMA), Health Canada, Japanese, Indian, and Chinese regulatory agencies have approved biosimilar monoclonal antibodies (mAbs) for chronic inflammatory, cancer, vaccine, non-communicable disease, and autoimmune disease treatment. mAbs can bind to antigens precisely and cause cytotoxicity. An antibody is an adaptive and practical approach to detecting and treating malignant tumours by neutralising effects or enhancing innate antibody-dependent cellular cytotoxicity (ADCC), complement-dependent cytotoxicity (CDC), and antibody-dependent cellular phagocytosis (ADCP) pathway. The tyrosine kinase family human epidermal growth factor receptor (HER-2, EGFR, and EGFR/HER-2) expression has been linked to the genesis and proliferation of numerous human cancers. Nimotuzumab (NmAb), a monoclonal antibody against the human epidermal growth factor receptor, and trastuzumab (TmAb), a monoclonal antibody against the human epidermal receptor-2 employed in the management and treatment of EGFR and HER-2 expressed cancers, respectively. TmAb and NmAb are making headway in the treatment of HER-2 and EGFR co-expressed cancers, both individually and in conjunction with AuNPs. The current antibody therapy is not the best receptor-targeted treatment strategy in clinical use due to some issues like antigen mono-specific, unstable in a biological medium, and resistance properties. Thus, a novel therapeutic approach is primarily needed to enhance the efficacy of mAb antibody-based immunotherapeutic agents for the treatment of both resistant and non-resistant cancers. That’s why I have tried to address some of the issues and conjugated antibodies and anticancer drugs with gold nanoparticles to overcome those issues.
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\nTo revolutionise present treatment approaches and strategies, this research designed and addressed three critical steps. Step (1): to rapidly synthesise different sizes (around 10 nm to 30 nm) of homogeneous and spherical AuNPs (being utilised as adjuvants and biological drug nano-carriers) by using citrate-tannate complexes, which is a strong and effective reducing agent, under lower temperatures followed by PEGylation using thiol-PEG compounds. Step (2): to develop antibody-AuNPs and dual antibody-AuNPs-anticancer drug nano complex compounds for improving the biophysical properties and treatment strategies to enhance synergistic capabilities against cancers. Step (3): to deliver customised and uniquely designed AuNPs-based antibodies and anticancer drugs to specific tumour cells to improve cellular uptake and boost cancer treatment specificity against A431, Calu-3, A549, and SKBR-3 cancer cells. Herein, I developed different bio-engineered immunoconjugates by combining therapeutic monoclonal antibodies (nimotuzumab and trastuzumab), and emtansine chemotherapeutic drugs (DM1) with AuNPs for providing precise synergistic targeted therapy against A549 and Calu-3 lung tumour, A431 skin cancer, and SKBR-3 breast cancer cell lines. A variety of physicochemical techniques have been used to describe the AuNPs-NmAb, AuNPs-TmAb, and AuNPs-DM1-TmAb-NmAb nanoconjugates via transmission electron microscopy (TEM), ultraviolet-visible spectrophotometry (UV-Vis), dynamic light scattering (DLS), Fourier-transform infrared spectroscopy (FTIR) and nanoparticle tracking analysis (NTA). We used polyacrylamide gel electrophoresis (SDS-PAGE), NaCl-salt titration, and biological medium tests to conduct the stability and binding activity analyses respectively, of the designed conjugates. Furthermore, the cytotoxicity potency and intracellular absorption of surface-modified AuNPs via cells were also assessed in vitro through MTT and spICP-MS assay, respectively. The survivability of cancerous cells was considerably reduced when AuNPs-NmAb was applied to A549 and A431 cells, AuNPs-TmAb was applied to Calu-3 and A431 cells, and AuNPs-DM1-TmAb-NmAb was applied to SKBR-3 cells compared to alone used of NmAb, TmAb, and DM1. Similar to this, AuNPs significantly boosted cellular absorption after PEGylation and conjugating with antibodies. For the lung and skin cancer cell lines, approximately 80 µg/mL of PEGylated 25–30 nm size, and for the breast cancer cell line, 40 µg/mL of 10 nm of PEGylated AuNPs seemed to be harmless. The results showed that AuNPs-NmAb inhibits the proliferation of EGFR overexpressed cancer cells. Whereas AuNPs-TmAb and AuNPs-DM1-TmAb-NmAb target and inhibit the proliferation of selective HER-2 overexpressed and EGFR/HER-2 co-expressed cancer cells, respectively. Among them, AuNPs-DM1-TmAb-NmAb showed the best immune-therapeutic potential against the EGFR/HER-2 expressed and trastuzumab-resistant breast cancer cell line (SKBR-3) treatment. Overall, this Ph.D. thesis focuses on surface modification and experimental strategies that will assist in the design and manufacturing of AuNPs carrier-based new generation immunotherapeutics for lung, skin, and breast cancer treatment.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,856
Score d'incertitude au seuil0,863

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,030
Tête enseignante GPT0,293
Écart entre enseignants0,262 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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