Abstract 5142: 50-parameter flow cytometry by CyTOF empowers comprehensive single-cell immune profiling of pulmonary immunosenescence in aged mice
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".