Abstract 1802: CD39 inhibition shapes the transcriptional landscape of myeloid cells and induces proinflammatory states in the CT26 syngeneic tumor model
Notice bibliographique
Résumé
Abstract Extracellular adenosine triphosphate (ATP) generated by tissue damage or immunogenic cell death initiates proinflammatory responses that are potently restricted by adenosine produced through ATP hydrolysis. The ectonucleotidases CD39 and CD73 limit immune responses by sequentially converting ATP to adenosine monophosphate (AMP) and adenosine, respectively. Increased activity of CD39, the rate-limiting enzyme in ATP hydrolysis in tumor microenvironments (TME), results in significant reductions in extracellular ATP. The subsequent accumulation of adenosine contributes to tumor immune escape, induction of angiogenesis, and metastatic progression. Although pharmacological targeting of CD39 has antitumor effects in preclinical models, the immunological mechanisms of therapeutic CD39 blockade have not been finely parsed. In this study, the immunological effects of CD39 inhibition on tumor infiltrating lymphocytes (TILs) were examined by single-cell transcriptome analysis. Mice bearing syngeneic CT26 tumors were treated with an anti-murine CD39 antibody that blocks the conversion of ATP to AMP. After 3 doses, tumors were harvested on Day 15 post-implant, dissociated, and enriched for CD45+ cells. Isolated TILs were captured in droplets, and single-cell sequencing libraries were generated through standard 10× Genomics protocols. Raw reads were pre-processed through the CellRanger pipeline. Data quality, normalization, integration, and clustering were performed with Seurat. Cell type annotation and differential expression was performed with SingleR and EdgeR, respectively. Several defined immunocyte populations identified in the CT26 TME were conserved across all conditions tested. These cell clusters segregated along the lymphoid/myeloid axis, with many sub-clusters identified for each major lineage. Data for each cell were aggregated in a pseudo-bulk RNA-seq analysis to define broad effects of CD39 blockade, which revealed major changes to immunocyte transcriptional landscapes. Notably, CD39 blockade upregulated several proinflammatory genes, including Gzmf, Gzmg, Cxcl9, and Csf3. Mapping of these changes to single-cell clusters revealed that CD39 blockade predominantly altered the transcriptional profiles of myeloid cell subsets, generally inducing proinflammatory gene modules. This analysis also demonstrated a significant effect of CD39 inhibition on plasmacytoid dendritic cells, inducing Cxcl2, Il1b, Gadd45g, and Fabp4 expression. Interestingly, CD39 blockade repressed Klk1, a kallikrein previously implicated in tumorigenesis. In summary, single-cell RNA-seq of the CT26 syngeneic tumor model suggests that CD39 inhibition predominantly shaped the transcriptional landscape of myeloid cells and generally induced proinflammatory conditions. Citation Format: Devapregasan Moodley, Mayra Carneiro, Sonia D. Gas, Austin Dulak, Ricard Masia, Secil Koseoglu, Matthew Rausch, Marisella Panduro, Michael C. Warren, John Stagg, Benjamin Lee, Pamela M. Holland, Vito J. Palombella, Andrew C. Lake. CD39 inhibition shapes the transcriptional landscape of myeloid cells and induces proinflammatory states in the CT26 syngeneic tumor model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1802.
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 ».