Abstract 2777: Advantages of patient primary tumor models versus tumor cell lines derived models for testing anticancer therapeutics.
Notice bibliographique
Résumé
Abstract BACKGROUND While the tumor xenograft models derived from human cancer cell lines in immunodeficient mice have been widely used for testing cytotoxic anticancer agents, new drug development has moved from cytotoxic agents to molecular target-directed therapeutics. Consequently, there is a need to identify tumor types and individual patient tumors that express the target that will benefit tumor model selection and be more indicative for clinical trials. Therefore, the tumor models used in preclinical development should be “disease-oriented” and target-directed. Recently, we have developed a large number of patient primary tumor xenograft models by transplanting patients’ fresh tumor tissues into immunodeficient mice, which have been used for testing novel therapeutics. METHODS The fresh tumor samples were collected from local hospitals. The tumor fragments of 1-2 mm were subcutaneously implanted in the flanks of nude mice. The histopathology and genomic mutation status of primary tumor xenografts were analyzed and compared with patients’ original tumors. The tested clinically used drugs included cisplatin, carboplatin, paclitaxel, docetaxel, irinotecan, doxorubicin, 5-FU, gemcitabine, gefitinib, erlotinib, pemetrexed, Erbitux, and Avastin. RESULTS A total of 1,120 patients’ primary tumor tissues have been implanted into immunodeficient mice and 348 patient tumor-derived models have been established. The tumor taking rates of the different tumor types in the first passage were colorectal (52%), ovarian (49%), esophageal (67%), small cell lung cancer (89%), non-small cell lung cancer (45%), gastric (27%), kidney (17%), glioblastoma (21%), breast (11%), liver (12%), pancreatic (50%), lymphoma (33%), and leukemia (23%). The tumor taking rates were higher in the later passages for the various tumor types, ranged from approximately 80-100%. The clinically used drugs produced tumor inhibition rates ranged from 20-90%, which were consistent with their clinical findings. The patient primary tumor xenografts presented a similar histopathological morphology and the same genomic mutation status to their counterparts of the patients’ original tumors. CONCLUSIONS The results suggest that patient primary tumor-derived xenograft model system can provide a larger number of models within the same tumor histological type for models selection based on antitumor mechanism of test agents. They also provide a unique renewable source of tumor material for target identification and biomarker evaluation. The preclinical results obtained from primary tumor models may give a better predictive value than the traditional human tumor xenograft models established by inoculation of in vitro cultured cancer cell lines. Especially, they have advantages for testing target-oriented therapeutics in new drugs development programs. Citation Format: Changnian Liu, Wenwei Li, Wen Zhou, Rong Liu, Rui Zhou, Fang He, Chunping Xu, Chang Bai. Advantages of patient primary tumor models versus tumor cell lines derived models for testing anticancer therapeutics. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2777. doi:10.1158/1538-7445.AM2013-2777
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) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».