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@ARTICLE{Jahn:282341,
      author       = {E. Jahn and M. Saadati and P. Fenaux and M. Gobbi and G. J.
                      Roboz and L. Bullinger and P. Lutsik and A. Riedel$^*$ and
                      C. Plass$^*$ and N. Jahn and C. Walter and K. Holzmann and
                      Y. Hao and S. Naim and N. Schreck$^*$ and J. Krzykalla$^*$
                      and A. Benner$^*$ and H. N. Keer and M. Azab and K. Döhner
                      and H. Döhner},
      title        = {{C}linical impact of the genomic landscape and leukemogenic
                      trajectories in non-intensively treated elderly acute
                      myeloid leukemia patients.},
      journal      = {Leukemia},
      volume       = {37},
      number       = {11},
      issn         = {0887-6924},
      address      = {London},
      publisher    = {Springer Nature},
      reportid     = {DKFZ-2023-01725},
      pages        = {2187-2196},
      year         = {2023},
      note         = {2023 Nov;37(11):2187-2196},
      abstract     = {To characterize the genomic landscape and leukemogenic
                      pathways of older, newly diagnosed, non-intensively treated
                      patients with AML and to study the clinical implications,
                      comprehensive genetics analyses were performed including
                      targeted DNA sequencing of 263 genes in 604 patients treated
                      in a prospective Phase III clinical trial. Leukemic
                      trajectories were delineated using oncogenetic tree modeling
                      and hierarchical clustering, and prognostic groups were
                      derived from multivariable Cox regression models. Clonal
                      hematopoiesis-related genes (ASXL1, TET2, SRSF2, DNMT3A)
                      were most frequently mutated. The oncogenetic modeling
                      algorithm produced a tree with five branches with ASXL1,
                      DDX41, DNMT3A, TET2, and TP53 emanating from the root
                      suggesting leukemia-initiating events which gave rise to
                      further subbranches with distinct subclones. Unsupervised
                      clustering mirrored the genetic groups identified by the
                      tree model. Multivariable analysis identified FLT3 internal
                      tandem duplications (ITD), SRSF2, and TP53 mutations as poor
                      prognostic factors, while DDX41 mutations exerted an
                      exceptionally favorable effect. Subsequent backwards
                      elimination based on the Akaike information criterion
                      delineated three genetic risk groups: DDX41 mutations
                      (favorable-risk), DDX41wildtype/FLT3-ITDneg/TP53wildtype
                      (intermediate-risk), and FLT3-ITD or TP53 mutations
                      (high-risk). Our data identified distinct trajectories of
                      leukemia development in older AML patients and provide a
                      basis for a clinically meaningful genetic outcome
                      stratification for patients receiving less intensive
                      therapies.},
      cin          = {B370 / C060},
      ddc          = {610},
      cid          = {I:(DE-He78)B370-20160331 / I:(DE-He78)C060-20160331},
      pnm          = {312 - Funktionelle und strukturelle Genomforschung
                      (POF4-312)},
      pid          = {G:(DE-HGF)POF4-312},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:37591941},
      doi          = {10.1038/s41375-023-01999-6},
      url          = {https://inrepo02.dkfz.de/record/282341},
}