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@ARTICLE{Nuez:212455,
      author       = {N. G. Nuñez and F. Berner and E. Friebel and S. Unger and
                      N. Wyss and J. M. Gomez and M.-T. Purde and R. Niederer and
                      M. Porsch and C. Lichtensteiger and R. Kramer and M. Erdmann
                      and C. Schmitt and L. Heinzerling and M.-T. Abdou and J.
                      Karbach and D. Schadendorf$^*$ and L. Zimmer and S. Ugurel
                      and N. Klümper and M. Hölzel and L. Power and S. Kreutmair
                      and M. Capone and G. Madonna and L. Cevhertas and A. Heider
                      and T. Amaral and O. Hasan Ali and D. Bomze and F. Dimitriou
                      and S. Diem and P. A. Ascierto and R. Dummer and E. Jäger
                      and C. Driessen and M. P. Levesque and W. van de Veen and M.
                      Joerger and M. Früh and B. Becher and L. Flatz},
      title        = {{I}mmune signatures predict development of autoimmune
                      toxicity in patients with cancer treated with immune
                      checkpoint inhibitors.},
      journal      = {Med},
      volume       = {4},
      number       = {2},
      issn         = {2666-6340},
      address      = {Amsterdam},
      publisher    = {Elsevier},
      reportid     = {DKFZ-2023-00172},
      pages        = {113-129.e7},
      year         = {2023},
      note         = {2023 Feb 10;4(2):113-129.e7},
      abstract     = {Immune checkpoint inhibitors (ICIs) are among the most
                      promising treatment options for melanoma and non-small cell
                      lung cancer (NSCLC). While ICIs can induce effective
                      anti-tumor responses, they may also drive serious
                      immune-related adverse events (irAEs). Identifying
                      biomarkers to predict which patients will suffer from irAEs
                      would enable more accurate clinical risk-benefit analysis
                      for ICI treatment and may also shed light on common or
                      distinct mechanisms underpinning treatment success and
                      irAEs.In this prospective multi-center study, we combined a
                      multi-omics approach including unbiased single-cell
                      profiling of over 300 peripheral blood mononuclear cell
                      (PBMC) samples and high-throughput proteomics analysis of
                      over 500 serum samples to characterize the systemic immune
                      compartment of patients with melanoma or NSCLC before and
                      during treatment with ICIs.When we combined the parameters
                      obtained from the multi-omics profiling of patient blood and
                      serum, we identified potential predictive biomarkers for
                      ICI-induced irAEs. Specifically, an early increase in
                      CXCL9/CXCL10/CXCL11 and interferon-γ (IFN-γ) 1 to 2 weeks
                      after the start of therapy are likely indicators of
                      heightened risk of developing irAEs. In addition, an early
                      expansion of Ki-67+ regulatory T cells (Tregs) and Ki-67+
                      CD8+ T cells is also likely to be associated with increased
                      risk of irAEs.We suggest that the combination of these
                      cellular and proteomic biomarkers may help to predict which
                      patients are likely to benefit most from ICI therapy and
                      those requiring intensive monitoring for irAEs.This work was
                      primarily funded by the European Research Council, the Swiss
                      National Science Foundation, the Swiss Cancer League, and
                      the Forschungsförderung of the Kantonsspital St. Gallen.},
      keywords     = {Translation to patients (Other) / biomarkers for
                      immunotherapy (Other) / cancer immunotherapy (Other) /
                      checkpoint blockade (Other) / immune-related adverse events
                      (Other)},
      cin          = {ED01},
      ddc          = {610},
      cid          = {I:(DE-He78)ED01-20160331},
      pnm          = {899 - ohne Topic (POF4-899)},
      pid          = {G:(DE-HGF)POF4-899},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:36693381},
      doi          = {10.1016/j.medj.2022.12.007},
      url          = {https://inrepo02.dkfz.de/record/212455},
}