Abstract 5142: 50-parameter flow cytometry by CyTOF empowers comprehensive single-cell immune profiling of pulmonary immunosenescence in aged mice
Notice bibliographique
Résumé
Abstract High-parameter flow cytometry is essential for human and mouse studies to discover novel immunological mechanisms of cancer, infections, and immunosenescence. It plays an increasingly important role in cancer research to ensure clinical therapeutic success but is limited by the large amount of cell samples needed for staining controls. CyTOF® technology has transformed flow cytometry by enabling 50-plus-marker analysis per tube of sample, with easy panel design and no need for single-stained or autofluorescence controls. Flow cytometry by CyTOF provides an efficient and unbiased approach to discovering novel subsets and unique functional states of immune cells, maximizing insights from precious samples. Immunosenescence perturbs lung cancer onset and development, yet the mechanisms remain largely unknown. To study the pulmonary immune populations in aged (75 weeks old) and young adult (6-8 weeks old) mice, we built a 50-parameter panel (2 for single live-cell identification, 6 for live-cell sample barcoding, and 42 for immune profiling). A core panel of 32 antibodies was selected from Standard BioTools™ catalogs to detect key cell lineage and functional surface markers. A complementary panel with 10 Maxpar® antibodies was added to further study functional cell states. Maxpar Pathsetter™ software was used to create an automated analytical model for high-dimensional analysis. The 50-parameter panel successfully identified over 30 lymphoid and myeloid cell subsets including but not limited to T cells, B cells, NK cells, alveolar macrophages (AMs), dendritic cells, and neutrophils. The panel enabled high-fidelity detection of over 15 functional markers mediating proliferation, activation, inhibition, migration, tissue residence, and cellular metabolism. Automated in-depth analysis by Maxpar Pathsetter efficiently identified many aging-associated alterations in cell frequencies and functional states such as the enrichment of PD-1+ T cells and CD27- γδ T cells that could potentially perturb anti-tumor immunity. Moreover, CyTOF technology is uniquely advanced in characterizing autofluorescent cells such as AMs. A pro-inflammatory state (higher expression of MHC-II, CD80, and PD-L1) was specifically defined for AMs in aged lungs. This study demonstrates comprehensive single-cell immune profiling of mouse tissues with the products and solutions provided by Standard BioTools. Both the 50-parameter panel and Maxpar Pathsetter analytical model can be customized for deep characterization of specific immune populations according to the requirements of various cancer studies in mice. By utilizing end-to-end solutions offered by Standard BioTools, flow cytometry by CyTOF can significantly facilitate the mechanistic studies of mouse models to expand the understanding of human cancers and accelerate therapeutic development. Citation Format: Wenxi Xu, Stephen Li, Alexandre Bouzekri, Lauren Tracey, Christina Loh. 50-parameter flow cytometry by CyTOF empowers comprehensive single-cell immune profiling of pulmonary immunosenescence in aged mice. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5142.
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 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| 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 ».