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@ARTICLE{Sigaud:277810,
      author       = {R. Sigaud$^*$ and T. K. Albert and C. Hess$^*$ and T.
                      Hielscher$^*$ and N. Winkler$^*$ and D. Kocher$^*$ and C.
                      Walter and D. Münter and F. Selt$^*$ and D. Usta$^*$ and J.
                      Ecker$^*$ and A. Brentrup and M. Hasselblatt and C. Thomas
                      and J. Varghese and D. Capper and U. W. Thomale and P.
                      Hernáiz Driever and M. Simon and S. Horn and N. A. Herz and
                      A. Koch and F. Sahm$^*$ and S. Hamelmann$^*$ and A.
                      Faria-Andrade and N. Jabado and M. U. Schuhmann and A. Y. N.
                      Schouten-van Meeteren and E. Hoving and T. Brummer$^*$ and
                      C. M. van Tilburg$^*$ and S. M. Pfister$^*$ and O. Witt$^*$
                      and D. Jones$^*$ and K. Kerl and T. Milde$^*$},
      title        = {{MAPK} inhibitor sensitivity scores predict sensitivity
                      driven by the immune infiltration in pediatric low-grade
                      gliomas.},
      journal      = {Nature Communications},
      volume       = {14},
      number       = {1},
      issn         = {2041-1723},
      address      = {[London]},
      publisher    = {Nature Publishing Group UK},
      reportid     = {DKFZ-2023-01521},
      pages        = {4533},
      year         = {2023},
      note         = {#EA:B310#LA:B310#},
      abstract     = {Pediatric low-grade gliomas (pLGG) show heterogeneous
                      responses to MAPK inhibitors (MAPKi) in clinical trials.
                      Thus, more complex stratification biomarkers are needed to
                      identify patients likely to benefit from MAPKi therapy.
                      Here, we identify MAPK-related genes enriched in
                      MAPKi-sensitive cell lines using the GDSC dataset and apply
                      them to calculate class-specific MAPKi sensitivity scores
                      (MSSs) via single-sample gene set enrichment analysis. The
                      MSSs discriminate MAPKi-sensitive and non-sensitive cells in
                      the GDSC dataset and significantly correlate with response
                      to MAPKi in an independent PDX dataset. The MSSs discern
                      gliomas with varying MAPK alterations and are higher in pLGG
                      compared to other pediatric CNS tumors. Heterogenous MSSs
                      within pLGGs with the same MAPK alteration identify
                      proportions of potentially sensitive patients. The MEKi MSS
                      predicts treatment response in a small set of pLGG patients
                      treated with trametinib. High MSSs correlate with a higher
                      immune cell infiltration, with high expression in the
                      microglia compartment in single-cell RNA sequencing data,
                      while low MSSs correlate with low immune infiltration and
                      increased neuronal score. The MSSs represent predictive
                      tools for the stratification of pLGG patients and should be
                      prospectively validated in clinical trials. Our data
                      supports a role for microglia in the response to MAPKi.},
      cin          = {B310 / HD01 / C060 / B300 / FR01 / B062 / B360},
      ddc          = {500},
      cid          = {I:(DE-He78)B310-20160331 / I:(DE-He78)HD01-20160331 /
                      I:(DE-He78)C060-20160331 / I:(DE-He78)B300-20160331 /
                      I:(DE-He78)FR01-20160331 / I:(DE-He78)B062-20160331 /
                      I:(DE-He78)B360-20160331},
      pnm          = {312 - Funktionelle und strukturelle Genomforschung
                      (POF4-312)},
      pid          = {G:(DE-HGF)POF4-312},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:37500667},
      doi          = {10.1038/s41467-023-40235-8},
      url          = {https://inrepo02.dkfz.de/record/277810},
}