Abstract 5881: Identification of resistance mechanisms to IGF-IR targeting in triple negative breast cancer
Notice bibliographique
Résumé
Abstract The triple negative subtypes of breast cancer (TNBC) are associated with poor prognosis. Unlike HER2+ and hormone receptor-positive BC, TNBC do not respond to targeted therapy and chemotherapy remains the primary treatment option. There is therefore an unmet need to develop effective therapy for TNBC. The insulin-like growth factor 1 (IGF-I) axis plays a critical role in BC progression by conveying survival and growth signals. Our laboratory reported on the production of a soluble fusion protein comprised of the extracellular domain of human IGF-IR fused to the Fc portion of human IgG (the IGF-Trap). The IGF-Trap reduces the bioavailability of circulating and locally produced IGF-I, thereby limiting tumor growth. When human TNBC MDA-MB-231 cells were xenotransplanted into nude mice and treated with the IGF-Trap, we observed variability in the response as it ranged from complete tumor regression to disease stabilization and tumor progression in some mice. This suggested that MDA-MB-231 cells are heterogeneous in respect to their sensitivity to IGF-IR signaling blockade. The aim of the present study was to identify resistance mechanisms that allow the cells to progress in the face of IGF-IR signaling blockade by the IGF-Trap. We first analyzed the tyrosine kinase receptor profile of these cells and confirmed by PCR that in addition to IGF-IR, they express epidermal growth factor receptor (EGFR), c-Met, and fibroblast growth factor receptor 1 (FGFR1). They also produce IGF-I, EGF and relatively high level of FGF1 that could provide potential autocrine signaling to compensate for IGF signaling blockade. Using limiting dilution cloning, we isolated MDA-MB-231 cells with a range of IGF-IR expression levels, as confirmed by qPCR and Western blotting. We found that clones with higher basal IGF-IR activation levels, independently of expression levels had increased sensitivity to IGF-Trap treatment in the presence of serum, identifying them as IGF-addicted clonal subpopulations. Furthermore, an IGF-Trap resistant population selected from MDA-MB-231 cells by prolonged exposure to the IGF-Trap had an increased proliferation rate in the presence of the IGF-Trap as compared to unselected cells, as assessed by MTT and showed higher p-EGFR and p-ERK levels, suggesting that prolonged IGF-Trap treatment enriched an IGF-I-independent population with increased aggressiveness. Collectively these results showed that MDA-MB-231 cells are heterogeneous in respect to IGF-IR expression levels and that IGF-Trap sensitivity correlated with constitutive IGF-IR activation levels. Moreover, IGF-Trap resistance in these cells was associated with increased EGFR signaling and proliferation. Further interrogation of the gene expression profile of these cells will define a “resistance signature” with potential relevance to personalized treatment with IGF-targeting drugs. Supported by the CIHR and Mitacs. Citation Format: Jennifer Tsui, George Vaniotis, Maria Celia Fernandez, Pnina Brodt. Identification of resistance mechanisms to IGF-IR targeting in triple negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5881. doi:10.1158/1538-7445.AM2017-5881
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) | 0,002 | 0,000 |
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 ».