Abstract 5146: EGFL7 is a potent endogenous inhibitor of tumor angiogenesis
Notice bibliographique
Résumé
Abstract Background: Tumor growth depends on establishment of new blood vessels through de novo angiogenesis, and blocking angiogenesis has proven to be an effective anti-cancer strategy. Epidermal growth factor-like 7 (EGFL7) is an endothelial-specific protein that is required for vascular tubulogenesis. Importantly, EGFL7 expression is increased during tumor growth, and recent evidence suggests that this may be due in part to the expression of EGFL7 by tumor cells. The precise function of EGFL7 in the endothelium and in the tumor microenvironment remains elusive, but we hypothesized that EGFL7 promotes the metastasis of HT1080 cells by modulating angiogenesis. To this end, EGFL7 was over-expressed in human fibrosarcoma HT1080 cells and its effect on angiogenesis, tumor growth and progression was assessed. Methods: Human fibrosarcoma HT1080 tumor cells were stably transfected with empty vector, EGFL7-GFP or EGFL7-myc. Cell proliferation was assessed by MTT assay. The effect of EGFL7 on tumor angiogenesis was assessed using HUVEC co-culture morphogenesis assays and a highly modified in vivo CAM angiogenesis assay. The effect of EGFL7 over-expression on tumor growth and metastasis was assessed using an avian embryo xenograft model system, whereby tumors were grown in the chorioallantoic membrane of shell-less chicken embryos. Metastasis was quantified using real-time PCR analysis to detect human alu sequences in distant organs including the brain, liver and lungs. Tumor vessel ultrastructure was examined by transmission electron microscopy and tumor vessel function was assessed using a real time vascular leak assay. Results: EGFL7 over-expression in HT1080 tumor cells did not affect their proliferation. HUVEC co-culture experiments demonstrated a significant decrease in branching morphogenesis (p<0.01). In vivo, EGFL7 over-expression significantly inhibited de novo angiogenesis in the CAM angiogenesis assay. Tumors over-expressing EGFL7 were significantly (p<0.01) smaller than controls. Additionally, we demonstrated that EGFL7 over-expression decreases spontaneous metastasis by more than 80% (p < 0.001). Transmission electron micrographs of the vasculature in EGFL7 over-expressing tumors revealed a disorganized endothelium with multiple layers of endothelial cells and compromised tight junctions. Vascular permeability assays indicated that this vasculature was significantly more permeable than controls, while structural integrity was maintained. Conclusion: Over-expression of EGFL7 in a metastatic fibrosarcoma reduced tumor growth and metastasis via a potent inhibition of angiogenesis. This was caused by a significant defect in the spatial organization of endothelium, which increased vascular permeability without affecting structural integrity. Our results identify EGFL7 as a potent endogenous inhibitor of angiogenesis, which may have implications for future therapeutic approaches. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 5146. doi:10.1158/1538-7445.AM2011-5146
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 | 0,000 |
| 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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».