Abstract P014: Driving immune-dependent metabolic vulnerabilities in the breast tumor microenvironment
Notice bibliographique
Résumé
Abstract The tumor microenvironment (TME) is a complex arms race composed of host stroma and rapidly adapting cancer cells. This symbiosis is further complicated when dissecting the influence of inflammation, due to its multifaceted function within the TME as a driver of both pro- and anti-tumor responses. Comprising a major component of the TME, targeting or exploiting tumor-associated inflammation has long been sought for therapeutic purposes. However, the optimal amount and composition of inflammation for such purposes remains elusive. We have recently identified an interferon (IFN)-dependent transcriptional response in breast cancer cells that renders a unique sensitivity to oxidative stress produced by the biguanide-class complex I inhibitor, phenformin. Using syngeneic murine models representing luminal B (PyMT) and basal (4T1) breast cancer, we identified a modest sensitivity to phenformin administration in vivo. However, phenformin effectiveness is dramatically enhanced when used in combination with the toll-like receptor 3 (TLR3) agonist, polyinosinic:polycytidylic acid (poly (I:C)). Critically, the effectiveness of this combination treatment was lost when performed in immune-deficient mice (SCID-beige), indicating that an immune component was essential. These findings highlight a novel role for inflammation and the immune system to promote sensitivity to oxidative stress in the TME. By identifying cell types responsible for cultivating a microenvironment conducive to biguanide sensitivity in breast cancer, we can identify a novel immune-biomarker of complex I sensitivity. Therefore, using high-parameter flow cytometry, we are analyzing systemic and tumor-infiltrating leukocyte diversity and enumeration in both our genetically and phenotypically distinct breast cancer models. Combination-therapy-induced immune populations will be further characterized in their molecular and cellular response to TLR agonism and complex I inhibition. Functional responses such as inflammatory-mediator production, immunomodulatory activity, and direct and indirect tumor cytotoxicity will be assessed, ex vivo. Furthermore, monoclonal antibody-mediated depletion of candidate cell types will be used to validate their requirement and contribution to the observed synergy to the combination therapy. Examples of tumoricidal synergy between biguanides and the inflammatory TLR agonists have not yet been described, establishing these findings as novel additions to the field of tumor biology. Furthermore, identifying how sensitivity to oxidative stress can become situationally immune-dependent can greatly advance our understanding of how inflammation and metabolism intersect within the TME. Citation Format: John Heath, Stephanie Totten, Young Kyuen Im, Valerie Sabourin, Kathryn Hunt, Josie Ursini-Siegel. Driving immune-dependent metabolic vulnerabilities in the breast tumor microenvironment [abstract]. In: Abstracts: AACR Virtual Special Conference: Tumor Immunology and Immunotherapy; 2021 Oct 5-6. Philadelphia (PA): AACR; Cancer Immunol Res 2022;10(1 Suppl):Abstract nr P014.
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 | 0,005 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,018 | 0,001 |
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 ».