Gravity-based microfiltration reveals unexpected prevalence of circulating tumor cell clusters in ovarian and colorectal cancer
Notice bibliographique
Résumé
Circulating tumor cells (CTCs) are rare (a few cells per milliliter of blood) and mostly isolated as single-cell CTCs (scCTCs). CTC clusters (cCTCs), even rarer, are of growing interest, notably because of their higher metastatic potential, but very difficult to isolate. We introduce gravity-based microfiltration (GµF) for facile isolation of cCTCs using in-house fabricated microfilters and 3D printed cartridges. Optimal flow rate and pore size for cCTC isolation are determined by GµF of cultured ovarian single cells and cell clusters spiked in healthy blood. We perform GµF of blood from orthotopic ovarian cancer mouse models and characterize the morphological features of scCTCs and cCTCs, and the expression of molecular markers for aggressiveness. Finally, we analyze blood from 17 epithelial ovarian cancer patients with either localized or metastatic disease, and from 13 colorectal cancer liver metastasis patients. Here, we show that GµF optimized for cell cluster isolation captures cCTCs from blood while minimizing unwanted cluster disaggregation, with ~85% capture efficiency. We detect cCTCs in every patient, with between 2–100+ cells. We find cCTCs represent between 5–30% of all CTC capture events, and 10-80% of the CTCs are clustered; remarkably, in 10 patients, most CTCs are circulating not as scCTCs, but as cCTCs. GµF uncovers the unexpected prevalence and frequency of cCTCs including sometimes very large ones in epithelial ovarian cancer patients, and motivates additional studies to uncover their properties and role in disease progression. Circulating tumor cells (CTCs) are cancer cells that have moved from the cancer tumor itself into the bloodstream. CTCs are considered responsible for cancers spreading from the place they initially start to grow to other parts of the body, a process called metastasis. CTCs can be found as single cells or as clusters of cells, but clusters have remained elusive. We developed a way to capture clusters of CTCs and use it to isolate them from 17 people with ovarian cancer and 13 people with colorectal cancer which had spread to their liver. We find clusters of CTCs in all the cancer patients. Our study highlights the prevalence of these cell clusters, and our isolation method could be used to study them further, as well as potentially diagnose and monitor the impact of therapy in the future. Meunier et al. explore circulating tumor cell (CTC) population identification in ovarian and colorectal cancer. Utilization of optimized gravity-based microfiltration captures both single and clustered CTCs in animal models and patient samples.
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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) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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) | 0,000 | 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 ».