Abstract PO-065: Utilization of optimized extracellular matrix substratum for inclusive capture of circulating tumor cells in stage IV colorectal cancer
Notice bibliographique
Résumé
Abstract Current methods to recover circulating tumour cells (CTCs) from the peripheral blood circulation of carcinoma patients rely principally on the expression of epithelial markers such as EpCAM, physical characteristics, and the absence of hematopoietic biomarkers. However, this strategy favours recovery of a homogeneous cell population with primarily differentiated epithelial characteristics. It fails to fully include those subpopulations that do not fit predictions and in particular does not properly capture cells that have stem-like characteristics or have undergone epithelial-mesenchymal transition (EMT). Yet these are often the cells that are most likely to give rise to successful metastasis and contribute to disease progression. We favour an approach that anticipates cellular heterogeneity, includes cells that have poor expression of differentiated characteristics, and relies on the very functional properties that are involved in successful negotiation of the route that culminates in metastasis. We therefore use a ‘tuned ECM’ (tECM) approach in which a complex ECM substratum is designed to extract and recover heterogeneous CTCs from the blood of patients with the cancer of interest, allowing subsequent single-cell analysis of cell behaviours to inform on features that have been shown to predict disease progression and metastasis. In the work described here we first used model colorectal cancer (CRC) cell lines, including those made resistant to drugs used in CRC regimens, to establish the best composition of ECM and full procedure to maximally capture cells for functional evaluation. For CRC we identified a defined mixture of collagen I and human plasma fibronectin as optimal for cell capture, providing a total recovery equivalent to complex ECM derived from tumor sources. In addition, this mixture accentuated the recovery of CRC cells made resistant to SN-38, the active metabolite of irinotecan. We then applied this approach to the recovery of CTCs from the blood from patients with stage IV CRC, using density centrifugation for prefractionation of nucleated blood cells followed by incubation on the tECM substratum. The captured cells could be immunostained in situ for both cytoplasmic and cell-surface markers and showed suitability for future assessment of cell behaviours in unfixed preparations. Optimisation of the capture-surface coating concentrations and subsequent fixation approach led to a 128-fold improvement in the CTC capture and identification from CRC patient blood. This optimised tECM approach offers promise for future inclusive recovery of heterogeneous CTC samples based on functional behaviours that relate to the metastastic process of the particular carcinoma, permitting further analyses including of chemokine pathways that are believed to be important in CRC metastasis. Citation Format: Deep Patel, Mala Bahl, Mario Valdes, Jonathan Blay. Utilization of optimized extracellular matrix substratum for inclusive capture of circulating tumor cells in stage IV colorectal cancer [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-065.
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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 ».