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@ARTICLE{Alhalabi:169758,
      author       = {O. Alhalabi$^*$ and M. N. C. Fletcher$^*$ and T.
                      Hielscher$^*$ and T. Kessler$^*$ and T. Lokumcu$^*$ and U.
                      Baumgartner and E. Wittmann$^*$ and S. Schlue$^*$ and M.
                      Göttmann$^*$ and S. Rahman$^*$ and L. Hai$^*$ and L.
                      Hansen-Palmus$^*$ and L. Puccio$^*$ and I. Nakano and C.
                      Herold-Mende and B. W. Day and W. Wick$^*$ and F. Sahm and
                      E. Phillips$^*$ and V. Goidts$^*$},
      title        = {{A} novel patient stratification strategy to enhance the
                      therapeutic efficacy of dasatinib in glioblastoma.},
      journal      = {Neuro-Oncology},
      volume       = {24},
      number       = {1},
      issn         = {1523-5866},
      address      = {Oxford},
      publisher    = {Oxford Univ. Press},
      reportid     = {DKFZ-2021-01541},
      pages        = {39-51},
      year         = {2022},
      note         = {B067#LA:B067# / 2022 Jan 5;24(1):39-51 / Junior Research
                      Group Bioinformatics and Omics Data Analytics},
      abstract     = {Glioblastoma is the most common primary malignancy of the
                      central nervous system with dismal prognosis. Genomic
                      signatures classify isocitrate dehydrogenase 1
                      (IDH)-wildtype glioblastoma into three subtypes: proneural,
                      mesenchymal and classical. Dasatinib, an inhibitor of
                      proto-oncogene kinase Src (SRC), is one of many therapeutics
                      which, despite promising preclinical results, has failed to
                      improve overall survival in glioblastoma patients in
                      clinical trials. We examined whether glioblastoma subtypes
                      differ in their response to dasatinib and could hence be
                      evaluated for patient enrichment strategies in clinical
                      trials.We carried out in silico analyses on glioblastoma
                      gene expression (TCGA) and single-cell RNA-Seq data. In
                      addition, in vitro experiments using glioblastoma stem-like
                      cells (GSCs) derived from primary patient tumors were
                      performed, with complementary gene expression profiling and
                      immunohistochemistry analysis of tumor samples.Patients with
                      the mesenchymal subtype of glioblastoma showed higher SRC
                      pathway activation based on gene expression profiling.
                      Accordingly, mesenchymal GSCs were more sensitive to SRC
                      inhibition by dasatinib compared to proneural and classical
                      GSCs. Notably, SRC phosphorylation status did not predict
                      response to dasatinib treatment. Furthermore, serpin
                      peptidase inhibitor clade H member 1 (SERPINH1), a collagen
                      related heat-shock protein associated with cancer
                      progression, was shown to correlate with dasatinib response
                      and with the mesenchymal subtype.This work highlights
                      further molecular-based patient selection strategies in
                      clinical trials and suggests the mesenchymal subtype as well
                      as SERPINH1 to be associated with response to dasatinib. Our
                      findings indicate that stratification based on gene
                      expression subtyping should be considered in future
                      dasatinib trials.},
      keywords     = {Dasatinib (Other) / Glioblastoma (Other) / Glioblastoma
                      stem-like cells (Other) / SERPINH1 (Other) / SRC (Other)},
      cin          = {B067 / B060 / C060 / B320},
      ddc          = {610},
      cid          = {I:(DE-He78)B067-20160331 / I:(DE-He78)B060-20160331 /
                      I:(DE-He78)C060-20160331 / I:(DE-He78)B320-20160331},
      pnm          = {312 - Funktionelle und strukturelle Genomforschung
                      (POF4-312)},
      pid          = {G:(DE-HGF)POF4-312},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:34232320},
      doi          = {10.1093/neuonc/noab158},
      url          = {https://inrepo02.dkfz.de/record/169758},
}