Abstract B49: Using ionizing radiation and primary human esophageal adenocarcinoma xenograft models to interrogate tumor cell characteristics associated with tumor-initiating cells
Notice bibliographique
Résumé
Abstract Radiotherapy is critical to the treatment of esophageal adenocarcinoma (EAC). However, with frequent recurrence and metastasis, five-year survival rates are only 13%. Clinical radioresistance is further evidenced by the fact that escalated doses increase toxicity without improving outcome. The cancer stem cell model may provide insight on the EAC cell of origin and thus, on clinically-observed radioresistance. Recent evidence has demonstrated a differential ability of EAC cells to seed tumors in mice, however a correlation between tumorigenicity and radioresistance in EAC has not been reported. Recently, sequencing and cross-checking of 14 commercially-available EAC cell lines revealed that these cell lines were in fact derived from other cancer types. These findings highlight the need for reliable models of EAC. We have developed mouse xenograft models of primary human EAC that recapitulated the original tumors in cellular differentiation and tumor architecture. Using these models, we compared the in vivo tumorigenicity of irradiated versus non-irradiated (control) tumors. We hypothesized that ionizing radiation would enrich the population of tumor-initiating cells (TIC) in xenograft tumors compared to non-irradiated tumors. Thus far, we are evaluating five primary xenograft models of human EAC that have been established in NODSCID mice. Treatment sensitivity testing has been performed on these five xenograft lines, and limiting dilution assays (LDA) have been performed on the first two. Initial experiments have revealed that xenograft Line 2 is significantly more radioresistant than the other four lines. LDA results on xenograft Line 1 revealed a TIC frequency of 1 in 20,089 in non-irradiated xenograft tumors and 1 in 40,620 in irradiated xenograft tumors. Line 2 revealed a TIC fraction of 1 in 434 non-irradiated tumors and 1 in 31,631 irradiated xenografts. These results suggest two Conclusions: (1) TIC frequency may be associated with relative radioresistance, since the radioresistant Line 2 appeared to be very tumorigenic; and (2) the comparison of TIC fractions in non-irradiated and irradiated xenograft tumors raises concerns that infiltrating mouse cells may dilute the TIC frequency through a radiation-induced inflammatory response. In subsequent LDAs, cells positive for the mouse-specific antigen H2k were depleted from the tumour cell suspension. Results from these LDAs are forthcoming, and will be presented at the meeting. In conclusion, preliminary LDA results have shown that the baseline TIC frequency in EAC xenografts is highly variable and might be related to radiosensitivity; our results suggest that this variability can be several orders of magnitude wider than previously reported. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the Second AACR International Conference on Frontiers in Basic Cancer Research; 2011 Sep 14-18; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2011;71(18 Suppl):Abstract nr B49.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 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 | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 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 ».