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Alloreactive T Cell Clonal Dynamics in Kidney Allograft Rejection Following Anti-PD-1 Therapy

Abstract

Kidney transplant recipients are at particular risk for developing tumors, many of which are now routinely treated with immune checkpoint inhibitors (ICIs); however, ICI therapy can precipitate transplant rejection. Here, we use TCR sequencing to identify and track alloreactive T cells in a patient with melanoma who experienced kidney transplant rejection following PD-1 inhibition. The treatment was associated with a sharp increase in circulating alloreactive CD8+ T cell clones, which display a unique transcriptomic signature and were also detected in the rejected kidney but not at tumor sites. Longitudinal and cross-tissue TCR analyses indicate unintended expansion of alloreactive CD8+ T cells induced by ICI therapy for cancer, coinciding with ICI-associated organ rejection.


Introduction

Immune checkpoint inhibitors (ICIs) have become the standard of care therapy for many cancers1. ICIs block the activation of inhibitory receptors (e.g., CTLA-4, PD-1), driving T cell activation and enhancing anti-tumor immunity2. However, ICI therapy is often complicated by immune-related adverse events (irAEs) that result from loss of T cell tolerance3,4. Kidney transplant recipients have a 3- to 10-fold increased risk of cancer post-transplant, but the use of ICI is challenging due to the high risk of precipitating acute allograft rejection5,6. We hypothesized that ICI-induced allograft rejection might occur due to a vigorous expansion of pre-existing, alloreactive memory T cells. Here we leveraged banked tissue and blood samples from a patient with advanced melanoma who experienced allograft rejection shortly after ICI therapy to identify and track alloreactive T cells longitudinally and across different tissues.


Methods

  • Patient samples

  • Flow cytometry

  • Immunofluorescence

  • Bulk TCR sequencing

  • Mixed-lymphocyte reaction

  • Single-cell RNA and TCR library preparation and sequencing

  • MLR single-cell RNA processing, QC, and clustering

  • Non-naive CD8 single-cell RNA processing, QC, and clustering

  • Gene signature analysis

  • Reference mapping

  • Single-cell TCR processing and QC


Statistics and reproducibility

As this study focuses on the case of a single patient, no statistical method was used to predetermine the sample size. Further, no data were excluded from the analyses, the experiments were not randomized, and the investigators were not blinded to allocation during experiments and outcome assessment.







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