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A Highly Sensitive Flow Cytometric Approach to Detect Rare Antigen-Specific T Cells: Development and Comparison to Standard Monitoring Tools

  • Tel Aviv Sourasky Medical Center
  • Rabin Medical Center Israel
  • Tel Aviv University
  • Department of Pediatric Hematology-Oncology
  • Sheba Medical Center at Tel Hashomer
  • Department of Biomolecular Sciences
  • Weizmann Institute of Science
  • The Cancer Immunotherapy Laboratory
  • Neurosurgery Department

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Personalized vaccines against patient-unique tumor-associated antigens represent a promising new approach for cancer immunotherapy. Vaccine efficacy is assessed by quantification of changes in the frequency and/or the activity of antigen-specific T cells. Enzyme-linked immunosorbent spot (ELISpot) and flow cytometry (FCM) are methodologies frequently used for assessing vaccine efficacy. We tested these methodologies and found that both ELISpot and standard FCM [monitoring CD3/CD4/CD8/IFNγ/Viability+CD14+CD19 (dump)] demonstrate background IFNγ secretion, which, in many cases, was higher than the antigen-specific signal measured by the respective methodology (frequently ranging around 0.05–0.2%). To detect such weak T-cell responses, we developed an FCM panel that included two early activation markers, 4-1BB (CD137) and CD40L (CD154), in addition to the above-cited markers. These two activation markers have a close to zero background expression and are rapidly upregulated following antigen-specific activation. They enabled the quantification of rare T cells responding to antigens within the assay well. Background IFNγ-positive CD4 T cell frequencies decreased to 0.019% ± 0.028% and CD8 T cells to 0.009% ± 0.013%, which are 19 and 13 times lower, respectively, than without the use of these markers. The presented methodology enables highly sensitive monitoring of T-cell responses to tumor-associated antigens in the very low, but clinically relevant, frequencies.

Original languageEnglish
Article number574
JournalCancers
Volume15
Issue number3
DOIs
StatePublished - Feb 2023

Funding

FundersFunder number
Chaya Charitable Trust
Israel Science Foundation1652/20

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Keywords

    • ELISpot
    • RNA vaccine
    • T cells
    • cancer
    • cancer testis antigens
    • flow cytometry
    • neoantigens
    • peptide vaccine
    • personalized cancer vaccine
    • self-antigens

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