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Using Visualization of t-Distributed Stochastic Neighbor Embedding To Identify Immune Cell Subsets in Mouse Tumors

Nicole V. Acuff and Joel Linden
J Immunol June 1, 2017, 198 (11) 4539-4546; DOI: https://doi.org/10.4049/jimmunol.1602077
Nicole V. Acuff
*Division of Developmental Immunology, La Jolla Institute for Allergy and Immunology, San Diego, CA 92117; and
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Joel Linden
*Division of Developmental Immunology, La Jolla Institute for Allergy and Immunology, San Diego, CA 92117; and
†Department of Pharmacology, University of California, San Diego, La Jolla, CA 92093
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Abstract

High-dimensional flow cytometry is proving to be valuable for the study of subtle changes in tumor-associated immune cells. As flow panels become more complex, detection of minor immune cell populations by traditional gating using biaxial plots, or identification of populations that display small changes in multiple markers, may be overlooked. Visualization of t-distributed stochastic neighbor embedding (viSNE) is an unsupervised analytical tool designed to aid the analysis of high-dimensional cytometry data. In this study we use viSNE to analyze the simultaneous binding of 15 fluorophore-conjugated Abs and one cell viability probe to immune cells isolated from syngeneic mouse MB49 bladder tumors, spleens, and tumor-draining lymph nodes to identify patterns of anti-tumor immune responses. viSNE maps identified populations in multidimensional space of known immune cells, including T cells, B cells, eosinophils, neutrophils, dendritic cells, and NK cells. Based on the expression of CD86 and programmed cell death protein 1, CD8+ T cells were divided into distinct populations. Additionally, both CD8+ T cells and CD8+ dendritic cells were identified in the tumor microenvironment. Apparent differences between splenic and tumor polymorphonuclear cells/granulocytic myeloid-derived suppressor cells are due to the loss of CD44 upon enzymatic digestion of tumors. In conclusion, viSNE is a valuable tool for high-dimensional analysis of immune cells in tumor-bearing mice, which eliminates gating biases and identifies immune cell subsets that may be missed by traditional gating.

Footnotes

  • The online version of this article contains supplemental material.

  • Abbreviations used in this article:

    DC
    dendritic cell
    dLN
    draining lymph node
    gMDSC
    granulocytic myeloid-derived suppressor cell
    MFI
    median fluorescent intensity
    MHC II
    MHC class II
    PD-1
    programmed cell death protein 1
    PMN
    polymorphonuclear cell
    SSC
    side scatter
    tSNE
    t-distributed stochastic neighbor embedding
    viSNE
    visualization of t-distributed stochastic neighbor embedding.

  • Received December 9, 2016.
  • Accepted April 4, 2017.
  • Copyright © 2017 by The American Association of Immunologists, Inc.
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The Journal of Immunology: 198 (11)
The Journal of Immunology
Vol. 198, Issue 11
1 Jun 2017
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Using Visualization of t-Distributed Stochastic Neighbor Embedding To Identify Immune Cell Subsets in Mouse Tumors
Nicole V. Acuff, Joel Linden
The Journal of Immunology June 1, 2017, 198 (11) 4539-4546; DOI: 10.4049/jimmunol.1602077

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Using Visualization of t-Distributed Stochastic Neighbor Embedding To Identify Immune Cell Subsets in Mouse Tumors
Nicole V. Acuff, Joel Linden
The Journal of Immunology June 1, 2017, 198 (11) 4539-4546; DOI: 10.4049/jimmunol.1602077
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