Abstract 1562: Clusters of circulating tumor cells were selectively isolated in the blood of 12/12 epithelial ovarian cancer patients using facile gravity-flow-based filtration method adapted to clinical use
Notice bibliographique
Résumé
Abstract Background The presence of circulating tumor cells (CTCs) in blood is correlated with disease progression in many cancers. Their prognosis value in ovarian cancer is still under debate.1 CTCs are heterogeneous in size and marker expression, and sub-populations with various metastatic potentials have been identified. CTC clusters, although rare and difficult to isolate, have emerged as a possible driver of metastasis owing to ~50-time higher metastatic potential than single CTCs.2 Only few methods have emerged to capture clusters, and are often complex and cumbersome, limiting our understanding of the role of clusters in metastasis. Here, we present a new filtration method for the selective capture of CTC clusters from blood and found clusters in 12/12 epithelial ovarian cancer (EOC) patients. Method Cluster capture was performed by filtration using a 3D printed cartridge3 and filters4 with pore diameters of 8, 10, 12, 15, 20 or 28 μm. We developed a gravity-driven process, generating reduced shear stress, and optimized capture using blood (1:6, v/v, in PBS) spiked with OV-90 and OVCAR-3 ovarian cancer single cells and clusters. Blood samples from 12 EOC patients were filtered. Clusters can be stained and imaged on the filter, or released for downstream analysis. Results Using the gravity-setup, we were able to selectively capture clusters with good integrity and with a rate that outperforms other technologies to the best of our knowledge. Viable CTC clusters, with 2 to >100 cells, were captured from 12/12 EOC patients. Their size distribution was surprisingly similar between patients. Small clusters (2-3 cells) were the most frequent, and this frequency decreased as their size increased. The molecular characterization of the captured clusters revealed a low and localized, heterogeneous expression of EpCAM (epithelial cell adhesion molecule), in combination with a widespread expression of c-MET (hepatocyte growth factor receptor) in all patients, suggesting a mesenchymal-like profile. Conclusion Using the gravity-filtration setup, CTC clusters were captured from the blood of all patients tested, suggesting that clusters are much more widespread than anticipated, and are in fact the norm rather than the exception. The cluster size distribution was conserved between patients with small clusters dominating, and some rare, very large clusters. Cluster staining revealed a mesenchymal profile, in agreement with a higher metastatic potential. Together, these results suggest that clusters should significantly contribute to disease progression, a hypothesis, which may be explored using our facile and selective method. References 1. Y. Zhou, et al. PLoS ONE 2015, 10, e0130873. 2. N. Aceto, et al. Cell 2014, 158, 1110. 3. A. Meunier, et al. Anal. Chem. 2016, 88, 8510. 4. J. A. Hernandez-Castro, et al. LOC 2017, 17, 1960 Citation Format: Anne Meunier, Sara Kheireddine, J. Alejandro Hernández-Castro, Benjamin Péant, Diane Provencher, Anne-Marie Mes-Masson, Teodor Veres, David Juncker. Clusters of circulating tumor cells were selectively isolated in the blood of 12/12 epithelial ovarian cancer patients using facile gravity-flow-based filtration method adapted to clinical use [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1562.
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) | 0,002 | 0,001 |
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 ».