Abstract 1254: Mechanistic interrogation of pre-treatment low dose aspirin effects in HER 2 positive breast cancer
Notice bibliographique
Résumé
Abstract Background: Prior data (Barron et al. Cancer Res. 2014 74:4065-77) suggests that pre-diagnostic exposure to aspirin can have significant effects on breast tumor biology and patient outcome. It has been proposed that aspirin inhibition of COX-2 may suppress lymphangiogenesis and metastasis (Karnezis et al Cancer Cell. 2014. 21:181-95). Here, we sought to recapitulate pre-diagnostic aspirin exposure in rodent models of Her2+ breast cancer and elucidate mechanisms of action. We also determined the effect of aspirin on tumor stroma, using a co-culture system of human tumor and mesenchymal stem cells (MSC). Methods: NOD/SCID mice were orthotopically implanted with Her2+ MDA-MB-231 or HCC1954 cells. 48hr later, animals began a daily low dose [30mg/kg or 120mg/kg] of aspirin, until tumors reached 250mm3. They were then resected. 3 weeks later, HCC1954 implanted animals were treated with trastuzumab (15mg/kg) and paclitaxel (5mg/kg) for 6 weeks. Primary tissues were analysed by immunohistochemistry to assess VEGF-C, -D, COX-2, LYVE1 and CD31. RNAseq was performed on tumours to identify aspirin perturbed molecular pathways. To determine the stromal response to aspirin, patient derived MSCs were cultured either alone or with HCC1954 cells and exposed to aspirin (2.5 or 7.5mM). Secreted VEGF-C was quantified. A tubule formation assay was performed to determine the impact of aspirin on angiogenesis. Pro-angiogenic protein expression was investigated using a human angiogenesis array platform. Results: A significant delay in tumor growth was observed in both tumor models following aspirin treatment (p<.01). Assessment of metastatic progression revealed that 120 mg/kg aspirin significantly (p<.05) increased time to metastasis and reduced primary regrowth in the MDA MB 231 model (p<.01). Immunohistochemical analysis of VEGF C, D and LYVE1 showed a significant dose dependant reduction (p<.01) in both models. RNAseq pathway analysis revealed a significant over-representation of mitochondrial electron transport chain genes. Downstream factors of AMPK showed significant (p<.01) upregulation suggesting alterations in metabolism. Aspirin (7.5mM) exposure resulted in loss of VEGF-C secretion from co-cultured tumor / MSC cell populations. Conditioned media harvested following aspirin treatment limited support tubule formation. Expression of pro-angiogenic factors in HCC1954 cells showed alterations following treatment, with the greatest decrease seen in Urokinase Plasminogen Activator (-42%) and its inhibitor Serpine1 (+55%). Conclusion: We have successfully recapitulated pre-treatment aspirin response in surgical resection models of Her2+ breast cancer, with IHC analysis confirming the impact of treatment on angiogenic and lymphangiogenic factors. RNAseq analysis implicates aspirin mediated alterations in cellular metabolism. Our data further reveals increased response to aspirin in stromal cell populations. Citation Format: Ian S. Miller, Sonja Khan, Liam P. Shiels, Sudipto Das, Bruce Moran, Finbarr P. Leacy, Paul M. Loadman, Robert S. Kerbel, Darran O' Connor, Kathleen Bennett, Róisín M. Dwyer, Annette T. Byrne. Mechanistic interrogation of pre-treatment low dose aspirin effects in HER 2 positive 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 1254. doi:10.1158/1538-7445.AM2017-1254
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) | 0,004 | 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 ».