% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Broche:304252,
      author       = {J. Broche$^*$ and O. Kelemen and A. Sekar and L. Schütz
                      and F. Muyas and A. Forschner and C. Schroeder$^*$ and S.
                      Ossowski$^*$},
      title        = {{G}ene{B}its: ultra-sensitive tumour-informed ct{DNA}
                      monitoring of treatment response and relapse in cancer
                      patients.},
      journal      = {Journal of translational medicine},
      volume       = {23},
      number       = {1},
      issn         = {1479-5876},
      address      = {London},
      publisher    = {BioMed Central},
      reportid     = {DKFZ-2025-01806},
      pages        = {964},
      year         = {2025},
      abstract     = {Circulating tumour DNA (ctDNA) in liquid biopsies has
                      emerged as a powerful biomarker in cancer patients. Its
                      relative abundance in cell-free DNA serves as a proxy for
                      the overall tumour burden. Here we present GeneBits, a
                      method for cancer therapy monitoring and relapse detection.
                      GeneBits employs tumour-informed enrichment panels targeting
                      20-100 somatic single-nucleotide variants (SNVs) in
                      plasma-derived DNA, combined with ultra-deep sequencing and
                      unique molecular barcoding. In conjunction with the newly
                      developed computational method umiVar, GeneBits enables
                      accurate detection of molecular residual disease and early
                      relapse identification.To assess the performance of GeneBits
                      and umiVar, we conducted benchmarking experiments using
                      three different commercial cell-free DNA reference
                      standards. These standards were tested with targeted
                      next-generation sequencing (NGS) workflows from both IDT and
                      Twist, allowing us to evaluate the consistency and accuracy
                      of our approach across different oligo-enrichment
                      strategies. GeneBits achieved comparable depth of coverage
                      across all target sites, demonstrating robust performance
                      independent of the enrichment kit used. For duplex reads
                      with ≥ 4x UMI-family size, umiVar achieved exceptionally
                      low error rates, ranging from 7.4×10-7 to 7.5×10-5. Even
                      when including mixed consensus reads (duplex $\&$ simplex),
                      error rates remained low, between 6.1×10-6 and 9×10-5.
                      Furthermore, umiVar enabled variant detection at a limit of
                      detection as low as $0.0017\%,$ with no false positive calls
                      in mutation-free reference samples. In a reanalysed melanoma
                      cohort, variant allele frequency kinetics closely mirrored
                      imaging results, confirming the clinical relevance of our
                      method.GeneBits and umiVar enable highly accurate therapy
                      and relapse monitoring in plasma as well as identification
                      of molecular residual disease within four weeks of tumour
                      surgery or biopsy. By leveraging small, tumour-informed
                      sequencing panels, GeneBits provides a targeted,
                      cost-effective, and scalable approach for ctDNA-based cancer
                      monitoring. The benchmarking experiments using multiple
                      commercial cell-free DNA reference standards confirmed the
                      high sensitivity and specificity of GeneBits and umiVar,
                      making them valuable tools for precision oncology. UmiVar is
                      available at https://github.com/imgag/umiVar .},
      keywords     = {Humans / Circulating Tumor DNA: genetics / Circulating
                      Tumor DNA: blood / Neoplasms: genetics / Neoplasms: therapy
                      / Neoplasms: blood / High-Throughput Nucleotide Sequencing /
                      Neoplasm Recurrence, Local: genetics / Treatment Outcome /
                      Recurrence / Liquid Biopsy / Polymorphism, Single
                      Nucleotide: genetics / Cell-free DNA (Other) / Circulating
                      tumour DNA (Other) / Liquid biopsy (Other) / Molecular
                      residual disease (Other) / Next-Generation-Sequencing
                      (Other) / Relapse detection (Other) / Treatment monitoring
                      (Other) / Ultra-deep sequencing (Other) / Unique molecular
                      barcode (Other) / Circulating Tumor DNA (NLM Chemicals)},
      cin          = {TU01},
      ddc          = {610},
      cid          = {I:(DE-He78)TU01-20160331},
      pnm          = {899 - ohne Topic (POF4-899)},
      pid          = {G:(DE-HGF)POF4-899},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:40866952},
      doi          = {10.1186/s12967-025-06993-3},
      url          = {https://inrepo02.dkfz.de/record/304252},
}