Abstract P5-04-24: Molecular stratification of ER+/HER2- breast cancer cell lines to predict sensitivity to targeted agents
Notice bibliographique
Résumé
Abstract Background: Approximately 70% of all breast cancers are estrogen receptor positive (ER+) at diagnosis and are dependent on estrogen signaling for tumour growth and proliferation. Some ER+ breast cancers can be effectively treated with adjuvant endocrine therapies including tamoxifen, but despite favorable improvements in overall survival, resistance to endocrine therapy is common and has been associated with dysregulation of several signaling pathways. These pathways can be targeted with specific inhibitors, many of which are currently under clinical investigation. However currently there is a lack of predictive biomarkers to identify which patients should receive treatment with targeted therapy. The goal of this study was to determine whether alterations in specific signaling pathways can be identified and used to stratify breast cancer cell lines to the most effective experimental treatments. Methods/Results: Fifteen ER+/HER2- cell lines were characterized using a NanoString PAM50-like assay as well as next generation sequencing and were then stratified according to alterations in three key signaling pathways: CCND/CDK, PI3K/AKT/mTOR and FGFR. High-throughput small-molecule screenings were performed to identify the IC50 values of 24 inhibitors across the strata. Variation in inhibitor sensitivity was observed between cell lines based on molecular alterations. Cell lines with a PIK3CA mutation in combination with a CDK-pathway alteration were more sensitive to CDK inhibitors (50 to 120nM) than cell lines with alterations in the CDK-pathway alone or PIK3CA mutations alone (170nM to >5000nM). In addition, cell lines with the dual alterations demonstrated stronger synergy between CDK and PI3K-pathway inhibitors compared to either alteration alone. Conclusions: The results suggest that stratification according to molecular alterations in specific signaling pathways may predict sensitivity to targeted inhibitors in a panel of ER+/HER2- luminal breast cancer cell lines. Work is ongoing to identify the optimal synergistic inhibitor combinations for each strata. The ultimate goal is to translate this work into a novel personalized medicine approach, using molecular stratification based on a combination of molecular events in a functional pathway as opposed to single genes. Citation Format: Bathurst L, Liao L, Crozier C, Lyttle N, Marcellus R, Bayani J, Al-awar R, Bartlett J, Spears M. Molecular stratification of ER+/HER2- breast cancer cell lines to predict sensitivity to targeted agents [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P5-04-24.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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 tête enseignante, 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 ».