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

Cooper, Rachel S.; Kowalczuk, Aleksandra; Wilkie, Gwen; Vickers, Mark A.; Turner, Marc L.; Campbell, John D. M.; Fraser, Alasdair R.

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 good manufacturing practice (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 analysing 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 analysed using a 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 interleukin (IL)‐2, tumour necrosis factor (TNF)‐α and interferon (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.