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Record W4393075499 · doi:10.1158/1538-7445.am2024-3800

Abstract 3800: Next generation of spatial biology: High-throughput multiplexed Imaging Mass Cytometry™ with whole slide modes

2024· article· en· W4393075499 on OpenAlexaff
Qanber Raza, Thomas D. Pfister, Jyh Yun Chwee, Liang Lim, David Howell, Nikesh Parsotam, David M. King

Bibliographic record

VenueCancer Research · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSingle-cell and spatial transcriptomics
Canadian institutionsIntegrity Testing Laboratory (Canada)
Fundersnot available
KeywordsMass cytometryThroughputMultiplexingCytometryComputer scienceBiologyComputational biologyFlow cytometryMolecular biologyGeneticsTelecommunications

Abstract

fetched live from OpenAlex

Abstract Gaining spatial insights into the cellular composition of tumor tissue has tremendous potential to inform clinical and translational researchers about mechanisms behind spatial predictors of immunotherapy success, disease etiology and progression. Imaging Mass Cytometry™ (IMC™) is a high-plex spatial biology imaging technique that enables deep characterization of the diversity and complexity of the tumor microenvironment (TME). IMC supports detailed assessment of cell phenotype and function using 40-plus metal-tagged antibodies simultaneously on a single slide without issues associated with fluorescence-based spectral overlap, tissue autofluorescence or implementation of multiple washing and acquisition cycles. Currently, IMC enables user-defined regions of interest (ROI) in tissues to evaluate cellular and structural composition. To enhance the IMC user experience, we developed two new whole slide imaging (WSI) modes which enable streamlined workflows using ultrafast preview mode (PM) and high-throughput tissue mode (TM). PM samples the entire tissue at predefined spacing to rapidly capture a low-resolution image of all expressed markers in the antibody panel. PM generates an image in minutes to enable informed ROI placements while leaving the stained tissue intact for higher-resolution imaging. PM and TM are designed so acquisitions can easily occur on the same slide without additional processing steps. TM rapidly acquires images of the whole tissue at lower resolution (7 μm pixel size) at a quality that can be used for quantitative analysis of the tissue spatial biology. Specifically designed for high-throughput applications, TM in combination with a newly available 40-slide loader for the Hyperion XTi™ Imaging System permits automated and continuous imaging of more than 40 large tissue samples (400 mm2 per tissue) per week. We showcase the application of WSI modes using the newly developed Maxpar® Human Immuno-Oncology IMC Panel Kit. The 31-marker panel was combined with catalog antibodies to create a 40-plus-marker panel that expands the ability to conduct comprehensive high-plex tumor and immune cell profiling. Tumor tissue microarrays (TMA) and whole tumor tissue sections were stained with the expanded panel. Single-cell analysis of selected ROIs, on whole tumor sections and TMAs, guided by PM data successfully provided quantitative analyses of spatial biology at single-cell resolution. In parallel, TM on whole tumor sections followed by pixel-based analysis provided a spatially resolved quantitative assessment of specific tumor and immune components of the TME. This work demonstrates the expanded capabilities of IMC and establishes it as a reliable high-plex spatial biology imaging platform with high-throughput imaging capabilities ideally suited for translational and clinical applications. For Research Use Only. Not for use in diagnostic procedures. Citation Format: Qanber Raza, Thomas D. Pfister, Jyh Yun Chwee, Liang Lim, David Howell, Nikesh Parsotam, David King, Christina Loh. Next generation of spatial biology: High-throughput multiplexed Imaging Mass Cytometry™ with whole slide modes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3800.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.506

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.110
GPT teacher head0.372
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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