Cytometric analysis of T cell phenotype using cytokine profiling for improved manufacturing of an EBV-specific T cell therapy

Rachel Cooper, Aleksandra Kowalczuk, Gwen Wilkie, Mark Vickers, Marc Turner, John Campbell, Alasdair Fraser* (Corresponding Author)

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Adoptive immunotherapy using Epstein-Barr Virus (EBV)-specific T cells is a potentially curative treatment for patients with EBV-related malignancies where other clinical options have proved ineffective. We describe improved GMP-compliant culture and analysis processes for conventional lymphoblastoid cell line (LCL)-driven EBV-specific T cell manufacture, and describe an improved phenotyping approach for analyzing T cell products. We optimized the current LCL-mediated clinical manufacture of EBV-specific T cells to establish an improved process using xenoprotein-free GMP-compliant reagents throughout, and compared resulting products with our previous banked T cell clinical therapy. We assessed effects of changes to LCL: T cell ratio in T cell expansion, and developed a robust flow cytometric marker panel covering T cell memory, activation, differentiation and intracellular cytokine release to characterize T cells more effectively. These data were analyzed using t-Stochastic Neighbour Embedding (t-SNE) algorithm. The optimized GMP-compliant process resulted in reduced cell processing time and improved retention and expansion of central memory T cells. Multi-parameter flow cytometry determined the optimal protocol for LCL stimulation and expansion of T cells and demonstrated that cytokine profiling using IL-2, TNF-α and IFN-γ was able to determine the differentiation status of T cells throughout culture and in the final product. We show that fully GMP-compliant closed-process culture of LCL-mediated EBV-specific T cells is feasible and profiling of T cells through cytokine expression gives improved characterization of start material, in-process culture conditions and final product. Visualization of the complex multi-parameter flow cytometric data can be simplified using t-SNE analysis.
Original languageEnglish
Article number68-81
Number of pages14
JournalClinical and Experimental Immunology
Issue number1
Early online date14 Jul 2021
Publication statusPublished - 31 Oct 2021


  • cancer
  • cell differentiation
  • cytotoxic T-cells
  • T-cells
  • viral


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