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@ARTICLE{Hertel:305685,
      author       = {A. Hertel and A. Streuer and S. Diehl and T. Boch$^*$ and
                      D. Nörenberg and A. Strittmatter and F. G. Zöllner and S.
                      O. Schoenberg and W.-K. Hofmann and S. Loges$^*$ and D.
                      Nowak and M. F. Froelich},
      title        = {{T}argeting tumoral heterogeneity in lung cancer: a novel,
                      {CT}-texture-guided targeted biopsy approach with exome
                      sequencing.},
      journal      = {npj precision oncology},
      volume       = {9},
      number       = {1},
      issn         = {2397-768X},
      address      = {[London]},
      publisher    = {Springer Nature},
      reportid     = {DKFZ-2025-02308},
      pages        = {342},
      year         = {2025},
      abstract     = {Solid tumors like lung cancer show significant mutational
                      heterogeneity. A biopsy captures only focal aspects,
                      limiting conclusions about overall tumor biology. This
                      prospective study correlated CT-based radiomics features
                      with genomic profiles to optimize biopsy site selection.
                      Lung cancer patients underwent CT imaging, radiomics
                      analysis, targeted biopsies, and whole-exome sequencing.
                      Twelve non-redundant features were extracted, with
                      JointEntropy guiding biopsy targeting. In 7 of 12 patients,
                      over $10\%$ of mutations were exclusive to one biopsy.
                      Clonal reconstruction showed heterogeneous profiles with
                      over two subclonal processes in $67\%$ of cases.
                      Unsupervised clustering of radiomics features revealed two
                      distinct groups separated by entropy features, of which the
                      entropy-rich cluster was associated with STK11 mutations.
                      Our study demonstrates that integrating radiomics with
                      localized genomic analysis enhances the understanding of
                      tumoral heterogeneity and may improve the targeting of
                      advanced tumor regions for diagnostic sampling.},
      cin          = {A420},
      ddc          = {610},
      cid          = {I:(DE-He78)A420-20160331},
      pnm          = {311 - Zellbiologie und Tumorbiologie (POF4-311)},
      pid          = {G:(DE-HGF)POF4-311},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:41203783},
      pmc          = {pmc:PMC12594912},
      doi          = {10.1038/s41698-025-01148-5},
      url          = {https://inrepo02.dkfz.de/record/305685},
}