Abstract PO-076: Adrenergic regulation of the anti-tumor immune response in <i>p53</i>-deficient tumors
Notice bibliographique
Résumé
Abstract Several previous studies have shown that β2-adrenergic signaling pathway promotes tumor progression, whereas others have shown the opposite effect. The role of β2-adrenergic activation in oral squamous cell carcinoma (OSCC) remains largely unknown. Our previous study showed that the loss of p53 leads to increased adrenergic tumor innervation in OSCC, resulting in transcriptional programs that establish new neuronal identity. We hypothesized that tumor immunity in OSCC is regulated by adrenergic signaling. The aim of the present study was to determine the influences of adrenergic signaling in immune microenvironment of OSCC. We first performed multiplex immunofluorescence to analyze the immune cell infiltration and adrenergic nerve density in OSCC; and analyzed the Cancer Genome Atlas (TCGA) datasets to establish correlations between immune-related and adrenergic pathway genes. Subsequently, we performed T cell killing assay with p53 knockout (KO) and p53 wild-type (WT) using antigen-specific HLA-matched patient-derived T-cells with adrenergic agonists or antagonists. To confirm p53-dependent adrenergic signaling in OSCC, a genetically engineered p53MDM2 overexpression (OE) cell line was generated and treated with adrenergic agonists or antagonists. To test our hypothesis that p53 regulates adrenergic-dependent paracrine signaling between cancer and T cells we performed a Luminex assay on the conditioned medium from p53 KO and p53 WT coculture system. Finally, in vivo, adrenergic ablation (TH flox/flox ) and novel murine models of OSCC were used to investigate the effect of adrenergic nerve signaling on immune infiltration and responses to immunotherapy. Our data showed that the increase in adrenergic nerve density was inversely proportional to the infiltration of exhausted T cells. Analysis of the TCGA data revealed that ADRB2 strongly correlated with tumor immune infiltrate genes. Adrenergic agonists treatment induced significantly more apoptosis in the p53 KO but not in the p53 WT cells; and overexpression of MDM2 rescued the resistance to apoptosis. Conditioned media experiments showed that the coculture of tumor cells with T cells acts through paracrine signaling and that the secreted factor is CXCL10. We then knocked out CXCL10 and ADRB2 in p53KO cells and confirmed that apoptosis was significantly reduced in the absence of CXCL10 or ADRB2. Genetic ablation of adrenergic signaling in vivo undermined response to anti-programmed cell death protein 1 (anti-PD1) compared to controls. Finally, our mouse model of OSCC showed that isoprenaline (β-adrenergic agonist) treatment in combination with PD-1 therapy significantly enhanced response to immunotherapy and improved survival. Our study provides new evidence that adrenergic signaling induces immune-mediated apoptosis and response to immunotherapy. Further studies are needed to assess the role of isoprenaline combined with anti-PD-1 therapy as a novel therapeutic regimen for patients with p53-deficient OSCC tumors. Citation Format: Deborah A. Silverman, Shamima Akhter, Tongxin Xie, Shajedul Islam, Simone Anfossi, Jennifer D. Covello, Frederico O. Gleber-Netto, Elien Doorduijn, Yunfei Wang, Emily L. Ashkin, Jeffrey N. Myers, George A. Calin, Patrick Hwu, Moran Amit. Adrenergic regulation of the anti-tumor immune response in p53-deficient tumors [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Innovating through Basic, Clinical, and Translational Research; 2023 Jul 7-8; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2023;29(18_Suppl):Abstract nr PO-076.
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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 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 ».