Abstract 483: Unraveling the impact of cancer cell derived membrane and cytosolic proteins using synthetic small extracellular vesicles
Notice bibliographique
Résumé
Abstract Background: Extracellular vesicles (EVs) are couriers in cell-cell communication. Evidence suggests that EV biology, from cargo packing, biodistribution, to cell uptake is a non-random and well-orchestrated process. Substantial efforts have been devoted to studying the pathological roles and therapeutic potential of EVs. It is speculated that surface properties, such as membrane proteins, mediate the interaction between EVs and recipient cells, while the enclosed “messages” exert downstream effects. This concept is exemplified in cancer metastasis, where cancer cell-derived EVs were shown to establish pre-metastatic niches and guide cancer organotropism. We propose selectively loading cancer cell membrane and cytosolic proteins into synthetic vesicles (SVs) like liposomes. This approach allows for the isolated study of individual factors, in contrast to the complexity of naturally occurring EVs. Methods: Cellular membrane and cytosolic proteins were extracted separately from a cancer cell line (MP41) (Mem-PERTM Plus kit). Empty-SV, Mem-SV (with membrane proteins), Cyto-SV (with cytosolic proteins), and Complete-SV (with both) were synthesized in a 3D-printed microfluidic chip and subsequently dialyzed (1000 KDa) overnight. The volume of protein buffer was controlled in all SV syntheses. EVs were isolated from the conditioned medium by ultrafiltration (Amicon) followed by ultracentrifugation. The size (Nanosight), zeta potential (ZetaView), and morphology (Transmission Electron Microscopy) of SVs and EVs were analyzed. Proteins incorporated into SVs were validated by stain-free gel, western blot, and CytoFLEX. SVs and EVs were stained by sp-DiIC18 fluorescent dye. The number of fluorescent particles was quantified (CytoFLEX) and controlled in cell uptake analysis on hepatocytes (IHH) and fibroblasts (BJ) (Incucyte). Results: All SVs were successfully synthesized with a mean size of ~100 nm. The zeta potential of both Mem-SV (-27.03 mV) and Complete-SV (-24.78 mV) is close to MP41 EVs (-26.01 mV) (P > 0.05) and are more negative than Empty-SV (-11.30 mV) and Cargo-SV (-13.38 mV) (P < 0.05). Total protein incorporation efficiency was estimated to be ~30%. The relative level of specific proteins (e.g. integrin av, TSG101) in Mem-SV and Cyto-SV matched the level in the raw membrane and cytosolic proteins by western blot. Integrin avb5 was detected on the surface of Mem-SV. Membrane and cytosolic protein incorporation increased the uptake efficiency of SVs compared to Empty-SVs, and the efficiency varied with cell type and protein content. Conclusion: In this study, we demonstrate that membrane and cytosolic proteins differentially impact the physical (zeta potential) and functional (cellular uptake) properties of SVs. Investigating these distinct roles could further our understanding of cancer EV biology, as well as advance drug delivery systems. Citation Format: Yunxi Chen, Rubén R. López, Thupten Tsering, Chaymaa Zouggari Ben El Khyat, Vahé Nerguizian, Julia V. Burnier. Unraveling the impact of cancer cell derived membrane and cytosolic proteins using synthetic small extracellular vesicles [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 483.
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 ».