Abstract 4303: Definitive identification and characterization of ovarian cancer-initiating cells
Notice bibliographique
Résumé
Abstract Serous ovarian cancer (SOC) typically presents with advanced disease. Current therapy significantly increases survival, yet nearly all patients recur within five years and die of their disease. The cancer-initiating cell (CIC) hypothesis holds that only a subset of cells have the potential to extensively self-renew and give rise to other tumor cells. As their properties may differ from bulk tumor cells, CIC may be spared by available therapies. Identification and characterization of CIC may lead to more effective therapeutic strategies. Previous reports suggested the presence of ovarian CIC, but these findings require validation in primary human samples. Primary SOC were dissociated and depleted of CD45+ cells. Cell surface (CD133/CD44/CD117/CDCP1/MUC-1/VEGFR2) and functional (ALDH1) markers were examined by flow cytometry (n=105). All markers demonstrated intra-/inter-tumor heterogeneity; however only CD133, VEGFR2 and ALDH marked minority populations in all samples. In contrast to a report that CD44+/CD117+ cells identify ovarian CIC, CD117 was present on only half of SOC samples examined (N=75) and only one quarter had a CD44+/CD117+ population. Limiting dilution analysis of primary SOC injected in the mammary fat pad of NOD/SCID mice (95% take at 106 cells) revealed the CIC frequency in primary tumors (n=13) and metastases (n=6 +5 matched) to be ∼1/40000 (n=13). The CIC frequency was significantly higher (∼1/9000) in primary and recurrent ascites (n=16, p=0.002). Xenografts could be passaged at least 3 times, providing evidence of self-renewal. The CIC frequency remained constant in nearly all xenografts from primary tumors, but increased substantially with passage of recurrences, suggesting greater genetic instability. CD133+ cells from primary tumors (n=2), matched metastases (n=2), ascites (n=6) and passage 1 xenografts (n=6) were enriched for CIC (1/300-1/4000), and all (or the vast majority) of CIC activity resided within the CD133+ fraction. Xenografts from CD133+ cells gave rise to CD133+ and CD133- cells and could be serially passaged at least 1-3x. VEGFR2+ and ALDH1+ cells also were enriched for CIC, to a lower extent than CD133. In contrast, after sorting for CD117/CD44 (n=3), tumors arose from all fractions but CD117+/CD44+ cells. Our data are consistent with a hierarchical model of SOC and indicate that CD133 is a marker for ovarian CIC. Current work is devoted to profiling the CD133+ population and identifying additional markers, using high throughput flow cytometry and a panel of 234 antigens and other methods. Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4303.
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) | 0,000 | 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) | 0,005 | 0,002 |
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 ».