Gravity microfiltration for enriching circulating tumour cells and clusters
Notice bibliographique
Résumé
Cancer is a leading cause of death worldwide, and metastatic lesions the primary mortal complication in solid tumour cancers. Tumour characterization by tissue biopsy is an invasive process that fails to fully account for widely prevalent spatiotemporal heterogeneity due to being assessed on a limited fraction of tissue taken at a single site and timepoint. Biopsy is often taken only during surgical resection, this can deny patients improved treatment informed by understanding tumour phenotype or worse, subject patients to costly and even harmful unnecessary treatment. This is true of colorectal cancer liver metastasis (CRCLM) in Canada, where patients receive pre-operative bevacizumab, which worsens outcome in a histological growth pattern (HGP) that is only diagnosed after the surgery.Circulating tumour cells (CTCs) in blood have a demonstrated clinical significance and are used for prognosis and monitoring in a wide range of cancers. They are much more rarely found as clusters (cCTCs), which have increased metastatic potential and may contain tumour-associated stromal and immune cells. However, most of the commonly used CTC isolation technologies are designed for isolating single cells and do not capture many cCTCs. The Juncker Lab has developed a gravity-driven microfiltration (GµF) platform suitable for the enrichment of single cell CTCs (scCTCs) and CTC clusters from blood samples on the basis of their size and mechanical properties. The platform has demonstrated excellent capture efficiency with spiked cells and has lead to exciting findings of cCTCs in ovarian cancer patients. However, bottlenecks in sample and analysis throughput need to be overcome to take advantage of the platform's strengths in large-scale studies. This works goes towards increasing the scalability of the GµF platform. First, high open-ratio membranes are designed and their fabrication optimized. These membranes allow for a five-fold increase in flow rate while maintaining the same shear-stress conditions. Next, a programmable confocal microscope routine is implemented to facilitate scalable data acquisition. Finally, we demonstrated the applicability of the improved platform in isolating CTCs from CRCLM patients. scCTCs and cCTCs were found in 13/13 patients. To the best of our knowledge, this is an unprecedented cCTC-positive rate (100%) in a set of CRCLM samples. This finding suggests that cCTC counts might be under-reported in literature due to the common use of CTC enrichment technologies that are incompatible with cCTC isolation or have low cCTC sensitivity. The outcome of this work improves the throughput of the GµF platform, which will facilitate its use in the pursuit of clinical translation research. Future studies are likely to investigate the particular role of cCTCs in the metastatic cascade, and assess their value as liquid analytes for cancer diagnosis, prognosis, and monitoring
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».