Abstract A19: Establishment of patient primary tumor-derived xenograft models for testing anticancer agents.
Notice bibliographique
Résumé
Abstract Background: While the human tumor xenograft models established by inoculation of human cancer cell lines into immunodeficient mice have been widely used for test of novel cytotoxic anticancer agents, new drug development has moved from general cytotoxic agents to molecular target-directed therapeutics. Consequently, there is a need to identify tumor types and individual patient tumors that express the target and could benefit from more selective therapies in clinical trials. Therefore, the in vivo models used in preclinical development should be “disease-oriented” and target-directed. Recently, we developed xenograft tumor models by transplanting human fresh tumor fragments into nude mice, which have been used for test of clinically used and novel anticancer drugs. Methods: The fresh tumor samples were collected from local hospitals. The tumor fragments of 1–2 mm were subcutaneously implanted in the flanks of the Balb/c nude mice. In the first passage, tumors derived from male patients were implanted into male mice, and tumors from women were inoculated into female mice. The histology and genomic mutation status were compared between original patients' tumors and the genografts. All therapeutic efficacy experiments, with the exception of prostate cancer, used female mice. The positive control drugs tested included cisplatin, paclitaxel, docetaxel, irinotecan, doxorubicin, 5-FU, gemcitabine, and erlotinib. Results: A total of 537 human tumor samples have been implanted into nude mice, 221 patient tumor-derived models have been established. The tumor taking rates of the first passage were colorectal (69%), ovarian (64%), esophagel (63%), small cell lung cancer (60%), non-small cell lung cancer (54%), gastric (25%), kidney (17%), glioblastoma (16%), breast (12%), liver (12%), and acute lymphocytic leukemia (25%). The tumor taking rates were higher in the later passages for the various tumor types, ranged from approximately 50–100%. The test anticancer drugs produced tumor inhibition rates ranged from 20–90%, which were consistent with their clinical findings. The patient-tumor xenografts from all five generations presented the same histopathological morphology and genomic mutation status to their counterparts of the human primary tumors. Conclusions: These results suggest that patient-tumor derived xenograft tumor models provide a unique renewable source of tumor material for test of novel anticancer agents and may give a better predictive value than the traditional human tumor xenograft models established by inoculation of cancer cell lines. Especially, they have advantages for test of target-oriented therapeutics in new drugs development programs. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2011 Nov 12-16; San Francisco, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2011;10(11 Suppl):Abstract nr A19.
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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,004 |
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 ».