Abstract

Background: Proliferating alloreactive T cells have a central role in the induction of acute GVHD (aGVHD) making them a promising target in preventing alloreactivity. T cell depleting regimens such as anti-T-lymphocyte globulin (ATG) or post-transplant cyclophosphamide (PTCy) effectively eliminate these cells and reduce aGVHD after hematopoietic cell transplantation (HCT) with marginal differences in clinical outcome. Comparative immune reconstitution analyses could contribute to answer the question, which agent would be most appropriate for an individual patient. However, not only effects relating to the different T cell depleting regimens, i.e. ATG or PTCy may be relevant but the general heterogeneity of T cell reconstitution. Aims: Here, we aimed at dissecting this heterogeneity with an approach called time-series clustering to better understand the impact of both regimens in individual patients and to consequently identify distinct patient subsets which benefit the most from each protocol. Methods: We retrospectively compared immune reconstitution data of 339 recipients of matched-unrelated donor (MUD) HCT with either ATG (n=304) or PTCy (n=35) as T cell depletion via conventional analysis on the cohort level and for its individual heterogeneity via time-series clustering. This analysis leveraged the approach of dynamic time warping (DTW) to determine the distance measure later used for the partitional clustering of individual patient time-series data. The performance of this methods was evaluated by the silhouette coefficient (Sil) which indicates a separation of clusters with values between 0 (overlapping clusters) and +1 (best separation); A 10-fold resampling was used to assess model robustness. Cluster information were used for subsequent analysis of clinical outcomes. All analysis were performed using R packages R stats, dtwclust, survival, survminer and cmprsk. Results: Comparative analysis of cellular reconstitution revealed distinct prominent T cell population after each protocol. While patients receiving PTCy as GVHD prophylaxis presented with higher levels of regulatory T cells, ATG patients had higher levels of γδ T- or NK-T cells. Time-series clustering of T cell subpopulations that associate with GVHD successfully dissected each population’s heterogeneity. For ATG patients the clustering revealed two distinct clusters with its optimal model configuration showing a good and robust silhouette coefficient (7_1: Sil=0.524) and a balanced patient distribution (Fig. 1A). In this model, clustering of ATG patients was driven by αβ- and activated T cells as those revealed higher absolute counts and a greater difference in shape over time as compared to regulatory- and γδ T cells. Patients in ATG cluster 1, showing higher absolute counts of αβ- and activated T cells compared to cluster 2 were associated to a significantly higher 1-year OS (98% vs. 79%, p=0.0023) due to lower NRM (p=0.032) and relapse (p=0.01). The clustering of PTCy patients distinguished two clusters with lower silhouette coefficients had a strong impact of αβ- and activated T cells (Fig.1B). Comparing the overall survival probability of both ATG clusters with the PTCy cohort revealed a significant difference driven by the ATG clusters (Fig 1C). Image:Summary/Conclusion: Beyond a differential impact of ATG and PTCy on immune reconstitution our analysis identified phenotypes that reproducibly associated with impaired clinical outcomes within the same T cell depletion platform. This provides guidance for individually choosing the most appropriate agent in the MUD setting.

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