Abstract 2035: Imaging mass cytometry identifies structural and cellular composition of the mouse tissue microenvironment
Bibliographic record
Abstract
Abstract Imaging Mass Cytometry™ (IMC™) is a vital tool to deeply characterize the complexity and diversity of any tissue without disrupting spatial context. The Hyperion™ Imaging System utilizes IMC, based on CyTOF® technology, to simultaneously assess up to 40 individual structural and functional markers in tissues, providing unprecedented insight into the organization and function of tissue microenvironment. We have previously demonstrated the application of IMC in combination with Maxpar® panel kits to highlight cellular composition of human tissues. Here, we showcase the recently released Maxpar OnDemand Antibodies for IMC application on mouse tissue. We introduced 11 additional biomarkers to our existing mouse antibody catalog, providing the basis for the use of high-multiplex imaging in preclinical investigations. To demonstrate the IMC workflow on mouse tissue, we analyzed a normal mouse tissue microarray using IMC spatial proteomic analysis. Tissues were stained with a 20-marker panel designed to highlight tissue architecture and major immune lineage markers combined with our IMC Cell Segmentation Kit*. The IMC Cell Segmentation Kit facilitates identification of cellular borders using plasma membrane markers that lead to improved nucleus and plasma membrane demarcation. We generated a detailed spatial map of the heterogeneous tissue architecture and successfully identified immune, epithelial, and stromal cell populations in various mouse tissues. Additionally, we classified the activation state of immune cell populations, adhesion state of epithelial cells, and molecular composition of the extracellular matrix.Overall, this work demonstrates the capability of IMC to identify subcellular localization of cellular and structural markers in the mouse tissue microenvironment. Information gained from IMC studies will enable in-depth high-throughput phenotypic characterization of the tissue microenvironment in various mouse models of development and disease, and thus accelerate preclinical discoveries. *The IMC Cell Segmentation Kit is part of the Innovative Solutions menu of custom-made reagents and workflows developed and tested by Fluidigm scientists to give faster access to new cutting-edge solutions for high-multiplex single-cell analysis. Innovative Solutions are not part of the Maxpar catalog. For Research Use Only. Not for use in diagnostic procedures. Citation Format: Qanber Raza, Michael Cohen, Smriti Kala, Liang Lim, Geneve Awong, Andrew Quong, Christina Loh. Imaging mass cytometry identifies structural and cellular composition of the mouse tissue microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2035.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".