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@ARTICLE{Milenkovic:295827,
      author       = {I. Milenkovic and S. Cruciani and L. Llovera and M. C.
                      Lucas and R. Medina and C. Pauli$^*$ and D. Heid$^*$ and T.
                      Muley and M. A. Schneider and L. V. Klotz and M. Allgäuer
                      and R. Lattuca and D. L. J. Lafontaine and C. Müller-Tidow
                      and E. M. Novoa},
      title        = {{E}pitranscriptomic r{RNA} fingerprinting reveals
                      tissue-of-origin and tumor-specific signatures.},
      journal      = {Molecular cell},
      volume       = {85},
      number       = {1},
      issn         = {1097-2765},
      address      = {New York, NY},
      publisher    = {Elsevier},
      reportid     = {DKFZ-2024-02647},
      pages        = {177–190.e7},
      year         = {2025},
      note         = {Molecular Cell, 85(1), pp. 177–190.e7, 2025},
      abstract     = {Mammalian ribosomal RNA (rRNA) molecules are highly
                      abundant RNAs, decorated with over 220 rRNA modifications.
                      Previous works have shown that some rRNA modification types
                      can be dynamically regulated; however, how and when the
                      mammalian rRNA modification landscape is remodeled remains
                      largely unexplored. Here, we employ direct RNA sequencing to
                      chart the human and mouse rRNA epitranscriptome across
                      tissues, developmental stages, cell types, and disease. Our
                      analyses reveal multiple rRNA sites that are differentially
                      modified in a tissue- and/or developmental stage-specific
                      manner, including previously unannotated modified sites. We
                      demonstrate that rRNA modification patterns can be used for
                      tissue and cell-type identification, which we hereby term
                      'epitranscriptomic fingerprinting.' We then explore rRNA
                      modification patterns in normal-tumor matched samples from
                      lung cancer patients, finding that epitranscriptomic
                      fingerprinting accurately classifies clinical samples into
                      normal and tumor groups from only 250 reads per sample,
                      demonstrating the potential of rRNA modifications as
                      diagnostic biomarkers.},
      keywords     = {RNA modifications (Other) / cancer (Other) / classification
                      (Other) / direct RNA sequencing (Other) / epitranscriptome
                      (Other) / fingerprinting (Other) / nanopore (Other) /
                      pseudouridine (Other) / rRNA (Other)},
      cin          = {A350},
      ddc          = {610},
      cid          = {I:(DE-He78)A350-20160331},
      pnm          = {311 - Zellbiologie und Tumorbiologie (POF4-311)},
      pid          = {G:(DE-HGF)POF4-311},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:39662470},
      doi          = {10.1016/j.molcel.2024.11.014},
      url          = {https://inrepo02.dkfz.de/record/295827},
}