Abstract B034: The immune checkpoint molecule B7-H3 is a driver of tumor immune exclusion by mediating TGF-β activation
Notice bibliographique
Résumé
Abstract Addressing the limited responsiveness to immune checkpoint blockade (ICB) in human cancers remains a critical challenge. Efforts over the past two decades have primarily focused on enhancing CD8 T cell function and preventing their exhaustion. However, less attention has been given to understanding the molecular mechanisms that contribute to the immunosuppressive tumor microenvironment (TME), which impedes CD8 T cell infiltration and fosters ICB resistance. The TME in ICB-resistant tumors is characterized by Transforming Growth Factor beta (TGF-β) cytokine signaling, leading to a fibrotic extracellular matrix (ECM) and the accumulation of immunosuppressive fibroblasts and myeloid cells. These features hinder CD8 T cell penetration, thereby promoting immune escape. The immune checkpoint molecule B7-H3, overexpressed in ICB-resistant cancers, has been linked to impaired CD8 T cell infiltration and poor prognosis. However, the molecular mechanisms governing B7-H3 function remain poorly understood. We investigated the relationship between B7-H3 gene expression and ICB response using transcriptomic data from two randomized phase 3 trials (IMvigor010 and IMvigor210). Bulk RNAseq data, tissue staining, and spectral flow cytometry were used to characterize the TME composition of B7-H3 high and low tumors. Multi-omic profiling of tumor cell lines with manipulated B7-H3 expression was performed to identify downstream targets of B7-H3. Syngeneic mouse tumor models were used to assess the impact of B7-H3 on tumor growth and antitumor immunity. High B7-H3 expression was associated with shorter overall survival in both IMvigor010 (HR=0.48, 95% CI: 0.33-0.70, p<0.0001) and IMvigor210 trials (HR=0.68, 95% CI: 0.51-0.92, p=0.01). In ICB-refractory cancers, B7-H3 expression correlated with high levels of fibroblasts, collagen deposits, and M2 macrophages. Gene set enrichment analysis revealed a positive association between B7-H3 and TGF-β signaling. Genetic deletion of B7-H3 in tumor cells reduced the surface expression of MMP14, a metalloprotease that activates TGF-β. Pan-cancer analysis identified MMP14 as the gene most correlated with B7-H3 (Pearson r=0.69, p<0.0001). TGF-β activation was reduced by 70% in B7-H3 knockout cells compared to wild-type. Loss of B7-H3 led to MMP14 accumulation in lysosomes, resulting in its degradation. We generated a B7-H3 inhibitor, 5D10, which promotes MMP14 degradation and inhibits TGF-β activation. In humanized B7-H3 mouse models, 5D10 significantly reduced TGF-β activation, enhancing CD8 T cell infiltration and impairing tumor growth. Our research identifies B7-H3 as a driver of immune exclusion and ICB resistance. We describe a novel, receptor-independent mechanism where B7-H3 promotes TGF-β activation via stabilization of MMP14. Targeting B7-H3 represents a strategy to modulate the TME, transforming immune-excluded tumors into immune-inflamed states that may respond better to ICB. Citation Format: Fabrice Lucien, Roxane Lavoie, Jack Korleski, Yohan Kim, Bharath Wootla, Liguo Wang, Ava Farrell, Kelly Harper, Martine Charbonneau, Claire Dubois, Igor Frank, Sounak Gupta, John Cheville, Jacob Orme, Stephen Boorjian, Parash Shah, Eugene Kwon, Sean Park, Haidong Dong. The immune checkpoint molecule B7-H3 is a driver of tumor immune exclusion by mediating TGF-β activation [abstract]. In: Proceedings of the AACR IO Conference: Discovery and Innovation in Cancer Immunology: Revolutionizing Treatment through Immunotherapy; 2025 Feb 23-26; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Immunol Res 2025;13(2 Suppl):Abstract nr B034.
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 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».