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@ARTICLE{Gellrich:309604,
      author       = {F. F. Gellrich$^*$ and C. Hufnagel$^*$ and A. M. Funk and
                      S. Jonas and H. Altmann$^*$ and S. Hobelsberger$^*$ and J.
                      Steininger$^*$ and C. Feige and A. Tasdogan$^*$ and T.
                      Chavakis and S. Beissert and F. Meier$^*$ and P. Mirtschink
                      and G. Steiner},
      title        = {¹{H}-{NMR} serum metabolomic profiling from clinical
                      routine identifies signatures of progressive melanoma
                      metastasis.},
      journal      = {Scientific reports},
      volume       = {nn},
      issn         = {2045-2322},
      address      = {[London]},
      publisher    = {Springer Nature},
      reportid     = {DKFZ-2026-00254},
      pages        = {nn},
      year         = {2026},
      note         = {#DKTKZFB9# / #NCTZFB9# / epub},
      abstract     = {Early detection of active melanoma metastasis is crucial.
                      Serum metabolomics may offer non-invasive biomarkers, but
                      real-world applicability needs validation. This study aimed
                      to identify ¹H-NMR-based serum metabolic signatures for
                      active metastasis in a large clinical cohort. Serum from 963
                      melanoma patients (1698 samples) underwent ¹H-NMR
                      spectroscopy. Patients were classified by active metastasis
                      status. OPLS-DA and RFE followed by logistic regression
                      models were developed on a patient-level training/test
                      split. Subgroup analyses assessed signatures related to
                      Immune Checkpoint Inhibitor (ICI) therapy, brain metastases,
                      and BRAF status. Models for active metastasis showed
                      moderate test set discrimination (Area Under the Curve
                      [AUCs]: OPLS-DA 0.609, RFE 0.630). The RFE-model highlighted
                      seven significant metabolites: increased pyruvate,
                      phenylalanine, acetoacetate, glutamate, glucose, and
                      decreased histidine and citrate were associated with active
                      metastasis. OPLS-DA yielded concordant metabolites. Subgroup
                      analyses revealed distinct metabolic associations, e.g., for
                      ICI therapy (citrate, RFE AUC 0.721) and BRAF status
                      (acetate, RFE AUC 0.655), but limited performance for brain
                      metastases (RFE AUC 0.553). ¹H-NMR serum metabolomics
                      detects systemic metabolic alterations of active melanoma
                      metastasis with moderate accuracy in a real-world setting.
                      Identified disruptions in energy and amino acid metabolism
                      offer pathobiological insights and warrant investigation for
                      multimodal biomarker panels.},
      keywords     = {Biomarkers (Other) / Melanoma (Other) / Metabolic profiling
                      (Other) / Predictive model (Other) / Tumor metabolism
                      (Other)},
      cin          = {ED01 / DD04 / WT01},
      ddc          = {600},
      cid          = {I:(DE-He78)ED01-20160331 / I:(DE-He78)DD04-20160331 /
                      I:(DE-He78)WT01-20160331},
      pnm          = {899 - ohne Topic (POF4-899)},
      pid          = {G:(DE-HGF)POF4-899},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:41617901},
      doi          = {10.1038/s41598-026-37118-5},
      url          = {https://inrepo02.dkfz.de/record/309604},
}