Evidence map›Paper›PMID 30468565›Full record

ArticleCytometry. Part A : the journal of the International Society for Analytical Cytology2019

Immune Cell and Cell Cluster Phenotyping, Quantitation, and Visualization Using In Silico Multiplexed Images and Tissue Cytometry.

Kim R M Blenman, Marcus W Bosenberg

Abstract readValidation Study
In one paragraph

Article in Cytometry. Part A : the journal of the International Society for Analytical Cytology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. A comprehensive profile of TCF1International journal of oral science · 2022
    Article
  4. Article
  5. Review
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Kim R M BlenmanDepartment of Dermatology, Yale University School of Medicine, New Haven, Connecticut, USA.ORCID 0000-0001-6070-0728
Marcus W BosenbergDepartment of Dermatology, Yale University School of Medicine, New Haven, Connecticut, USA.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Yale SPORE in Skin CancerP50CA121974 · NCI · YALE UNIVERSITY · PI DAVID F STERN · 2006 to 2026
$43.9M
Tumor Assessment CoreP01CA128814 · NCI · SANFORD BURNHAM PREBYS MEDICAL DISCOVERY INSTITUTE · PI SMITH, JEFFREY W · 2009 to 2020
$19.1M
Congenic Mouse Medels of Melanoma for the Characterization of Tumor Immune ResponsesR01CA196660 · NCI · YALE UNIVERSITY · PI BOSENBERG, MARCUS W · 2016 to 2018
$1.7M
NCATS NIH HHS UL1 TR001863NCI NIH HHS P01 CA128814NCI NIH HHS P50 CA121974NCI NIH HHS R01 CA196660
6 · The paper itself

Abstract

Phenotyping immune cells and cell clusters in situ, including their activation state and function, can aid in interpretation of spatial relationships within the tissue microenvironment. Immune cell phenotypes require multiple biomarkers. However, conventional microscopy setups can only image up to four biomarkers at one time. In this report, we describe and give an example of a workflow to phenotype, quantitate, and visualize greater than four biomarkers in silico utilizing multiplexed fluorescence histology and the TissueFAXS quantitative imaging system with a conventional microscopy setup. Biomarkers were conjugated to Cy3 or Cy5. Multiplexed staining was performed on formalin-fixed paraffin-embedded tissue sections. We imaged the slides, inactivated the dyes, and repeated the process until all biomarkers were stained. Phenotype profiles were built based on in silico combinations of the biomarkers. We used algorithms that aligned all images to create a composite image, isolated each cell in the image, and identified biomarker positive cells in the image. The in silico phenotypes were quantitated and displayed through flow cytometry-like histograms and dot scatterplots in addition to backgating into the tissue images. The advantage of our workflow is that it provides visual verification of cell isolation and identification as well as highlight characteristics of cells and cell clusters. © 2018 International Society for Advancement of Cytometry.

Indexed as

Computer SimulationAnimalsCell CountCell Line, TumorFlow CytometryImage CytometryImage Processing, Computer-AssistedImmunophenotypingLymphocytesMiceMice, Inbred C57BLMicroscopy, FluorescenceSpheroids, CellularStaining and LabelingTissue Fixationcell clustersFFPEimmune cellsin silico analysismultiplexed histologyquantitative imagingtissue cytometryTissueFAXS

Identifiers

PMID30468565
PMCPMC6500592

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.