% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Leserer:275345,
      author       = {S. Leserer and T. Graf and M. Franke and R. Bogdanov and E.
                      Arrieta-Bolaños$^*$ and U. Buttkereit and N. Leimkühler
                      and K. Fleischhauer$^*$ and H. C. Reinhardt and D. W. Beelen
                      and A. T. Turki},
      title        = {{T}ime series clustering of {T} cell subsets dissects
                      heterogeneity in immune reconstitution and clinical outcomes
                      among {MUD}-{HCT} patients receiving {ATG} or {PTC}y.},
      journal      = {Frontiers in immunology},
      volume       = {14},
      issn         = {1664-3224},
      address      = {Lausanne},
      publisher    = {Frontiers Media},
      reportid     = {DKFZ-2023-00714},
      pages        = {1082727},
      year         = {2023},
      abstract     = {Anti-T-lymphocyte globulin (ATG) or post-transplant
                      cyclophosphamide (PTCy) prevent graft-versus-host disease
                      (GVHD) after hematopoietic cell transplantation (HCT), yet
                      individual patients benefit differentially.Given the sparse
                      comparative data on the impact of cellular immune
                      reconstitution in this setting, we studied flow cytometry
                      and clinical outcomes in 339 recipients of 10/10
                      matched-unrelated donor (MUD) HCT using either ATG (n=304)
                      or PTCy (n=35) for in vivo T cell manipulation along with a
                      haploidentical PTCy control cohort (n=45). Longitudinal
                      cellular immune reconstitution data were analyzed
                      conventionally and with a data science approach using
                      clustering with dynamic time warping to determine the
                      similarity between time-series of T cell subsets.Consistent
                      with published studies, no significant differences in
                      clinical outcomes were observed at the cohort level between
                      MUD-ATG and MUD-PTCy. However, cellular reconstitution
                      revealed preferences for distinct T cell subpopulations
                      associating with GVHD protection in each setting. Starting
                      early after HCT, MUD-PTCy patients had higher regulatory T
                      cell levels after HCT (p <0.0001), while MUD-ATG patients
                      presented with higher levels of γδ T- or NKT cells (both p
                      <0.0001). Time-series clustering further dissected the
                      patient population's heterogeneity revealing distinct immune
                      reconstitution clusters. Importantly, it identified
                      phenotypes that reproducibly associated with impaired
                      clinical outcomes within the same in vivo T cell
                      manipulation platform. Exemplarily, patients with lower
                      activated- and αβ T cell counts had significantly higher
                      NRM (p=0.032) and relapse rates (p =0.01).The improved
                      understanding of the heterogeneity of cellular
                      reconstitution in MUD patients with T cell manipulation both
                      at the cohort and individual level may support clinicians in
                      managing HCT complications.},
      keywords     = {Humans / Time Factors / Immune Reconstitution /
                      Antilymphocyte Serum / Hematopoietic Stem Cell
                      Transplantation: adverse effects / Cyclophosphamide / Graft
                      vs Host Disease / T-Lymphocyte Subsets / GVHD prophylaxis
                      (Other) / anti-T-lymphocyte globulin (Other) /
                      anti-thymocyte globulin (ATG) (Other) / dynamic time warping
                      (DTW) (Other) / matched unrelated donor allogeneic
                      hematopoietic stem cell transplantation (Other) /
                      post-transplant cyclophosphamide (Other) / time-series (TS)
                      model (Other) / unsupervised learning (Other) /
                      Antilymphocyte Serum (NLM Chemicals) / Cyclophosphamide (NLM
                      Chemicals)},
      cin          = {ED01},
      ddc          = {610},
      cid          = {I:(DE-He78)ED01-20160331},
      pnm          = {899 - ohne Topic (POF4-899)},
      pid          = {G:(DE-HGF)POF4-899},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:37020562},
      pmc          = {pmc:PMC10067907},
      doi          = {10.3389/fimmu.2023.1082727},
      url          = {https://inrepo02.dkfz.de/record/275345},
}