Poster Presentation NSW State Cancer Conference 2023

Unravelling Immunotherapy Toxicity at Single Cell Resolution (#241)

Jennifer W Lim 1 2 3 , Venessa T Chin 1 3 4 , Patricia Keith 1 5 , Rachael Zekanovic 1 , Drew Neavin 1 3 6 , Karena Pryce 1 , Dominik Kaczorowski 1 , Chia-Ling Chan 1 , Ellie Spenceley 1 , Himanshi Arora 1 , Anthony Joshua 1 3 4 , Joseph Powell 1 3
  1. The Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
  2. Medical Oncology, St George Hospital, Kogarah, NSW, Australia
  3. University of New South Wales, Sydney, NSW, Australia
  4. The Kinghorn Cancer Centre, St Vincent's Hospital, Darlinghurst, NSW, Australia
  5. University of Technology, Sydney, NSW, Australia
  6. University of Queensland, Brisbane, QLD, Australia

Background

Immune checkpoint inhibitors are widely used in oncology. However, immune-related adverse events (IRAEs) are idiosyncratic events that can be very severe. The overall incidence is around 27%, with severe IRAEs occurring in 6% of patients1. We hypothesised that difference in gene expression within peripheral immune cells can predict and mediate immune-related toxicity from checkpoint inhibitor immunotherapy based on previously published research2,3. Single-cell RNA sequencing (scRNA-seq) is a powerful modality that enables study of the gene expression of thousands of individual cells4.

Aims

We aimed to analyse single-cell RNA data generated from peripheral blood mononuclear cells (PBMCs) collected from patients who experienced a severe checkpoint inhibitor therapy IRAE.

Methods

We identified a cohort of 8 patients who developed grade 3 or above toxicity due to immune checkpoint inhibitors and 8 age-matched controls who received similar treatment but without severe toxicity. Peripheral blood samples were collected prospectively at baseline and at two subsequent timepoints with PBMCs isolated and cryopreserved. Cells were captured on the 10x Chromium platform and sequenced on Illumina. Samples were demultiplexed according to previously published methods5 and the bioinformatic data analysed with the Seurat package on R statistical software.

Results

After quality control filtering, we identified 36 288 cells from 16 individuals and 24 samples. Preliminary analysis indicates a significant difference in cell proportions at baseline, with increased numbers of B intermediate cells (9.93% vs 0.97% in the control group, p <0.01 ) and reduced CD8 T effector memory cells in the cohort group (9.29% vs 17.37% in the control group, p <0.01) . Furthermore, we observed an early drop in B intermediate cells and a sharp rise in CD8 T effector memory cells between cycle 1 and cycle 2 associated with development of severe immune-related toxicity. Gene expression analysis is currently in progress.

  1. Kumar V, Chaudhary N, Garg M, Floudas CS, Soni P, Chandra AB. Current Diagnosis and Management of Immune Related Adverse Events (irAEs) Induced by Immune Checkpoint Inhibitor Therapy. Frontiers in Pharmacology. 2017;8.
  2. Lozano AX, Chaudhuri AA, Nene A, et al. T cell characteristics associated with toxicity to immune checkpoint blockade in patients with melanoma. Nature Medicine. 2022;28(2):353-362.
  3. Das R, Bar N, Ferreira M, et al. Early B cell changes predict autoimmunity following combination immune checkpoint blockade. J Clin Invest. 2018;128(2):715-720.
  4. Lim, J., Chin, V., Fairfax, K. et al. Transitioning single-cell genomics into the clinic. Nat Rev Genet (2023). https://doi.org/10.1038/s41576-023-00613-w
  5. Neavin, D, Senabouth A, Lee J, Ripoll A,, sc-eQTLGen Consortium, Franke L, Prabhakar S, Ye CJ, Davis J. McCarthy, Melé M, Hemberg, M, Powell, J. Demuxafy: Improvement in droplet assignment by integrating multiple single-cell demultiplexing and doublet detection methods. bioRxiv 2022.03.07.483367; doi: https://doi.org/10.1101/2022.03.07.483367