Design, optimisation and standardisation of a high-dimensional spectral flow cytometry workflow assessing T-cell immunophenotype in patients with melanoma

Jack M Edwards; Miles C Andrews; Hayley Burridge; Robin Smith; Carole Owens; Mark Edinger; Katherine Pilkington; Juliette Desfrancois; Mark Shackleton; Sashendra Senthi; Menno C van Zelm

doi:10.1002/cti2.1466

Design, optimisation and standardisation of a high-dimensional spectral flow cytometry workflow assessing T-cell immunophenotype in patients with melanoma

Clin Transl Immunology. 2023 Sep 7;12(9):e1466. doi: 10.1002/cti2.1466. eCollection 2023.

Authors

Jack M Edwards^{1

2}, Miles C Andrews^{3

4}, Hayley Burridge⁴, Robin Smith¹, Carole Owens¹, Mark Edinger⁵, Katherine Pilkington⁵, Juliette Desfrancois⁵, Mark Shackleton^{3

4}, Sashendra Senthi¹, Menno C van Zelm²

Affiliations

¹ Alfred Health Radiation Oncology The Alfred Hospital Melbourne VIC Australia.
² Department of Immunology, Central Clinical School Monash University and Alfred Hospital Melbourne VIC Australia.
³ Department of Medicine, Central Clinical School Monash University Melbourne VIC Australia.
⁴ Department of Medical Oncology The Alfred Hospital Melbourne VIC Australia.
⁵ Cytek Biosciences Fremont CA USA.

Abstract

Objectives: Despite the success of immune checkpoint blockade, most metastatic melanoma patients fail to respond to therapy or experience severe toxicity. Assessment of biomarkers and immunophenotypes before or early into treatment will help to understand favourable responses and improve therapeutic outcomes.

Methods: We present a high-dimensional approach for blood T-cell profiling using three multi-parameter cytometry panels: (1) a TruCount panel for absolute cell counts, (2) a 27-colour spectral panel assessing T-cell markers and (3) a 20-colour spectral panel evaluating intracellular cytokine expression. Pre-treatment blood mononuclear cells from patients and healthy controls were cryopreserved before staining across 11 batches. Batch effects were tracked using a single-donor control and the suitability of normalisation was assessed. The data were analysed using manual gating and high-dimensional strategies.

Results: Batch-to-batch variation was minimal, as demonstrated by the dimensionality reduction of batch-control samples, and normalisation did not improve manual or high-dimensional analysis. Application of the workflow demonstrated the capacity of the panels and showed that patients had fewer lymphocytes than controls (P = 0.0027), due to lower naive CD4⁺ (P = 0.015) and CD8⁺ (P = 0.011) T cells and follicular helper T cells (P = 0.00076). Patients showed trends for higher proportions of Ki67 and IL-2-expressing cells within CD4⁺ and CD8⁺ memory subsets, and increased CD57 and EOMES expression within TCRγδ⁺ T cells.

Conclusion: Our optimised high-parameter spectral cytometry approach provided in-depth profiling of blood T cells and found differences in patient immunophenotype at baseline. The robustness of our workflow, as demonstrated by minimal batch effects, makes this approach highly suitable for the longitudinal evaluation of immunotherapy effects.

Keywords: T cells; immune checkpoint blockade; immunotherapy; melanoma; spectral flow cytometry.