Classification of anticancer drugs based on tissue penetration using a novel in vitro screening assay
Notice bibliographique
Résumé
A213 Background: The failure of many anticancer drugs to control the growth of solid cancers may stem in part from inadequate delivery to tumor regions distant from vasculature. However, gaining an understanding of diffusion limitations of existing drugs and developing new drugs with improved tumor penetration is often limited by a lack of techniques with which to evaluate drugs. In this study we employ multilayered cell culture (MCC) in combination with a biological endpoint to assess the tissue penetration of a panel of 18 commonly used anti-cancer drugs. MCC is a planar analogue of spheroidal cell culture, in which tumor cells are instead grown into discs of tissue. Due to their 3-D conformation they model many characteristics of the tumor extravascular compartment. A unique property of MCC is that it possesses two populations of rapidly proliferating cells, one on each side of the culture, that are separated by a known thickness of tissue. In tumors and spheroids proliferation status falls off with distance from the vasculature (tumors) or tissue edge (spheroids), which in turn modifies cellular response to drugs. Hence, visualizing the distribution of a drug’s effect within these tissues cannot be used to directly determine actual drug distribution. Method: In this study, we exploit the symmetrical growth that occurs within MCCs by exposing them to drugs from one side and then comparing drug effect on the exposed side versus the far side of the cultures. This approach circumvents issues that normally arise from the biochemical gradients that occur with distance into tissue (e.g. changing intrinsic sensitivity of cells to drugs with depth into tissue) and in effect uses the cells themselves as the drug detection endpoint. Using this technique we examined the tissue penetration of representative anti-cancer drugs from a selection of classes, including anthracyclines, microtubule agents, anti-metabolites, platinum based agents and others. The distribution of drug activity within HCT-116 MCCs was assessed 1 to 3 days after a 1-h drug exposure via immunodetection of S-phase cells using bromodeoxyuridine. Using an automated computer analysis routine, the effect of the drugs in the first 30 µm of tissue located on either edge of the cultures relative to controls was assessed. Results: Penetration of the agents through HCT-116 MCCs was grouped into four classes: near uniform tissue distribution (cisplatin, 5-FU and vinorelbine), 1-5 fold decrease in drug exposure to cells on the far side versus the exposed side of the cultures (vincristine, vinblastine, paclitaxel, mitomycin C and etoposide), ~10-fold difference (doxorubicin, epirubicin, docetaxel and gemcitabine) and greater than 10-fold (daunorubicin and mitoxantrone). In the case of the anthracyclines and taxanes, the MCC-based assay was validated by comparing the predicted drug distributions with direct visualization of the drugs themselves. Conclusion: This model could be applied as a screening system for the discovery of biologically active drugs which exhibit desirable penetration properties. This research was supported by the National Cancer Institute of Canada with funds from the Canadian Cancer Society, the Michael Smith Foundation For Health Research and the Canadian Institutes for Health Research.
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 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 | 0,001 | 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 ».