Abstract 5755: Expansion of the known functional diversity of human T cells achieved due to the unprecedented resolution of intracellular proteins by mass cytometry (CyTOF)
Notice bibliographique
Résumé
Abstract Measuring the functional signatures of immune cells comprehensively, spanning the inflammatory (Th1/Th17) and immunosuppressive (Th2/Treg) lineages, provides key insights into several facets of cancer research and therapy. Single-cell detection of cytokines from diverse functional lineages is required to determine mechanisms underlying success/failure of checkpoint blockade, define immunosuppressive activity of the tumor-resident cell subsets and identify immunological biomarkers that predict clinical outcomes. Powerful cytometric research tools, such as fluorescence cytometry, enable important intracellular measurements of functional potential, such as cytokines, phosphorylation events and transcription factors in single cells. However, expanding the number of targets detected per cell by these methods has limitations in commercial availability of compatible conjugates and the technology’s resolving capacity for rare subsets, specifically due to spectral signal overlap and autofluorescence. Many readouts, including cytokines of the Th2/Treg lineages (IL-5, IL-10 and IL-13), have also been notoriously difficult to reproducibly detect in human cells using fluorescence-based cytometry. We predicted that mass cytometry may overcome such limitations and enable better signal resolution for such applications. We evaluated three small (11-12-plex) panels using a full-spectrum flow cytometer and the CyTOF™ XT mass cytometer to address this. Each panel was comprised of surface and intracellular analytes (cytokines, phospho-epitopes or transcription factors) and designed to minimize potential impact of spectral overlap on the resolution of spectral flow data. PBMC were stimulated, split and stained with either fluorochrome- (Cytek Aurora) or metal-conjugated antibodies (CyTOF). Datasets were analyzed by PhenoGraph clustering and visualized with opt-SNE to determine cellular functional diversity. Overall, data collected on the CyTOF XT system demonstrated superior resolution for many intracellular readouts, including cytokines IL-10 and IL-13, with stimulation-specific events only detected using CyTOF technology. Additionally, improved signal:noise (S/N) provided better resolution of phospho-activation events and transcription factor expression, particularly TOX and Tbet. Further, better S/N with CyTOF technology enabled more accurate population clustering using PhenoGraph, and more distinct functional signatures resulted from mass cytometry datasets compared with fluorescent counterparts. CyTOF XT mass cytometry platform clarifies understanding a sample's immune signatures in unsupervised analysis. Our findings indicate that the CyTOF XT platform could serve as a catalyst for seminal discoveries in immune profiling to drive therapeutic design and advanced disease monitoring in cancer. Citation Format: Laura Polanco, Michael J. Cohen, Erika L. Smith-Mahoney, Ling Wang, David King, Madison Bailey, Christina Loh, Anna C. Belkina, Amedeo J. Cappione, Jennifer E. Snyder-Cappione. Expansion of the known functional diversity of human T cells achieved due to the unprecedented resolution of intracellular proteins by mass cytometry (CyTOF) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5755.
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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,002 |
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 ».