Abstract 1741: Cancer cell-derived extracellular vesicle mimicking: A parametric study of the physicochemical characteristics of EVs and their influence on cellular uptake in metastasis
Notice bibliographique
Résumé
Abstract Introduction: Extracellular vesicles (EVs) play a crucial role in disseminating cancer to distant organs, communicating with the tumor microenvironment to prepare the metastatic niche, and through horizontal transfer of oncogenic traits to recipient cells. EV parameters influencing cellular uptake include surface proteins, lipid profile, and physicochemical properties such as size and zeta potential. EVs isolated from cells are heterogeneous populations, which hinder the study of single EV variables and their influence on cellular uptake. Moreover, EV isolation is a lengthy and laborious process with an extremely low yield. Liposomes are synthetic vesicles that share properties with EVs, such as the lipid bilayer and the capability to encapsulate relevant biomolecules. In this study, we used a uveal melanoma (UM) model, a highly liver metastatic tumor, to characterize naturally occurring EVs and model them using liposomes. Methods: We utilized liposomes as a model of EVs to study how the size and zeta potential influence cellular internalization. EVs were isolated from primary UM cells (MP41) using ultracentrifugation (UC) and characterized using dynamic light scattering, nanoparticle tracking analysis, as well as electrophoretic mobility for hydrodynamic size, concentration, and zeta potential, respectively. Liposomes mimicking EVs were produced using the periodic disturbance mixer (nanoprecipitation). The lipid composition was DMPC: CHOL: DHP at different ratios and 0.2% molar concentration of SP-DiIC18(3) as labeling reagent. Liposomes were then dialyzed overnight using a membrane size of 12kDa. Cellular uptake was assessed in immortalized human hepatocytes, representing the liver microenvironment. Results: Using surface response methodology (SRM), we created a model to predict size and zeta potential depending on liposome manufacturing conditions. We produced anionic and neutral liposomes with zeta potential ~-30 mV and 0mV, respectively, and with a size of ~150 nm, similar to EVs derived from MP41 cells in order to evaluate the influence of zeta potential in cellular uptake. Our results showed no significant differences at 0 and 6 hours between anionic and neutral EV-like liposomes. By contrast, the uptake of the anionic liposomes was significantly higher at 24 h compared to neutral ones. Moreover, EV-like liposomes were produced 1000x more concentrated than naturally occurring EVs isolated using UC. Conclusion: In this study, we describe a novel approach using synthetic biology to produce EV-like liposomes as a model to study EV cellular uptake and its role in metastasis. Our data demonstrate that liposomes are a feasible tool to study EV variables individually, thereby addressing the high heterogeneity of biological samples, and producing high liposome yield, thereby helping to accelerate research Citation Format: Rubén Rodrigo López Salazar, Chaymaa Zouggari, Thupten Tsering, Prisca Bustamante Alvarez, Ion Stiharu, Catherine Mounier, Vahe Nerguizian, Julia V. Burnier. Cancer cell-derived extracellular vesicle mimicking: A parametric study of the physicochemical characteristics of EVs and their influence on cellular uptake in metastasis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1741.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».