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@ARTICLE{Wurm:283153,
      author       = {A. A. Wurm$^*$ and S. Brilloff and S. Kolovich and S.
                      Schäfer and E. Rahimian and V. Kufrin and M. Bill$^*$ and
                      Z. Carrero$^*$ and S. Drukewitz$^*$ and A. Krüger$^*$ and
                      M. Hüther and S. Uhrig and S. Oster$^*$ and D. Westphal and
                      F. Meier and K. Pfütze$^*$ and D. Hübschmann$^*$ and P.
                      Horak$^*$ and S. Kreutzfeldt$^*$ and D. Richter$^*$ and E.
                      Schröck$^*$ and G. Baretton$^*$ and C. Heining$^*$ and L.
                      Möhrmann$^*$ and S. Fröhling$^*$ and C. Ball$^*$ and H.
                      Glimm$^*$},
      title        = {{S}ignaling-induced systematic repression of mi{RNA}s
                      uncovers cancer vulnerabilities and targeted therapy
                      sensitivity.},
      journal      = {Cell reports / Medicine},
      volume       = {4},
      number       = {10},
      issn         = {2666-3791},
      address      = {Maryland Heights, MO},
      publisher    = {Elsevier},
      reportid     = {DKFZ-2023-01939},
      pages        = {101200},
      year         = {2023},
      note         = {#LA:B280# / 2023 Oct 17;4(10):101200},
      abstract     = {Targeted therapies are effective in treating cancer, but
                      success depends on identifying cancer vulnerabilities. In
                      our study, we utilize small RNA sequencing to examine the
                      impact of pathway activation on microRNA (miRNA) expression
                      patterns. Interestingly, we discover that miRNAs capable of
                      inhibiting key members of activated pathways are frequently
                      diminished. Building on this observation, we develop an
                      approach that integrates a low-miRNA-expression signature to
                      identify druggable target genes in cancer. We train and
                      validate our approach in colorectal cancer cells and extend
                      it to diverse cancer models using patient-derived in vitro
                      and in vivo systems. Finally, we demonstrate its additional
                      value to support genomic and transcriptomic-based drug
                      prediction strategies in a pan-cancer patient cohort from
                      the National Center for Tumor Diseases (NCT)/German Cancer
                      Consortium (DKTK) Molecularly Aided Stratification for Tumor
                      Eradication (MASTER) precision oncology trial. In
                      conclusion, our strategy can predict cancer vulnerabilities
                      with high sensitivity and accuracy and might be suitable for
                      future therapy recommendations in a variety of cancer
                      subtypes.},
      keywords     = {cancer driver (Other) / drug response (Other) / miRNA
                      signatures (Other) / organoids (Other) / precision oncology
                      (Other) / spheroids (Other) / target prediction (Other)},
      cin          = {DD01 / HD01 / B340 / B280},
      ddc          = {610},
      cid          = {I:(DE-He78)DD01-20160331 / I:(DE-He78)HD01-20160331 /
                      I:(DE-He78)B340-20160331 / I:(DE-He78)B280-20160331},
      pnm          = {312 - Funktionelle und strukturelle Genomforschung
                      (POF4-312)},
      pid          = {G:(DE-HGF)POF4-312},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:37734378},
      doi          = {10.1016/j.xcrm.2023.101200},
      url          = {https://inrepo02.dkfz.de/record/283153},
}