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@ARTICLE{Aybey:302809,
      author       = {B. Aybey and B. Brors$^*$ and E. Staub},
      title        = {{E}xpression signatures with specificity for type {I} and
                      {II} {IFN} response and relevance for autoimmune diseases
                      and cancer.},
      journal      = {Journal of translational medicine},
      volume       = {23},
      number       = {1},
      issn         = {1479-5876},
      address      = {London},
      publisher    = {BioMed Central},
      reportid     = {DKFZ-2025-01349},
      pages        = {740},
      year         = {2025},
      abstract     = {Aberrant interferon signaling is a key element of various
                      diseases, but resolving gene expression signatures that stem
                      from different types of IFNs in tissue samples is still a
                      challenge. Most published IFN signatures comprise genes that
                      are activated by different IFNs: they cannot discriminate
                      type-I (IFN-I) and type-II (IFN-II) IFN stimulation. Most
                      often such signatures were obtained from a single expression
                      dataset that had been obtained in a specific cellular
                      context, and their translatability to other experimental
                      contexts has not been demonstrated.We leveraged multiple
                      RNA-seq datasets of IFN stimulation in a network
                      meta-analysis workflow to obtain IFN gene signatures
                      separating IFN-I and IFN-II. We validated our signatures in
                      bulk and single cell RNA-seq datasets of various cellular
                      contexts demonstrating similar or higher coherence than
                      previously published signatures. Our IFN-II signature is
                      broader applicable than other published signatures as it
                      demonstrates strong performance in detecting IFN-II response
                      in more cell types. In three SLE microarray datasets our
                      IFN-I signature was highly coherent and correlated with
                      disease severity better than most published signatures. In
                      TCGA, our IFN-II signature produced distinct profiles
                      compared to published IFN-I signatures and correlated
                      strongly with published CD8+ T cell signatures. In cohorts
                      of three different cancer types, we observed higher
                      signature scores of our IFN-II signature in responders than
                      in non-responders to immune checkpoint inhibitor (ICI)
                      therapy.Our IFN-I and IFN-II response-specific gene
                      expression signatures can inform on complex IFN responses in
                      a more fine-grained way than previously possible. They can
                      be used to assess type I versus II IFN response in gene
                      expression data produced by different technologies, for
                      different diseases and even different cell types in single
                      cell studies. The association of high scores of our IFN-II
                      signature with anti-tumor response to ICIs suggests a role
                      as a biomarker to predict ICI response.},
      keywords     = {Humans / Neoplasms: genetics / Interferon Type I: genetics
                      / Interferon Type I: metabolism / Autoimmune Diseases:
                      genetics / Gene Expression Profiling / Reproducibility of
                      Results / Transcriptome / Gene expression signature
                      discovery (Other) / Immunology (Other) / Interferon (Other)
                      / Oncology (Other) / SLE-systemic lupus nephritis (Other) /
                      Transcriptomics (Other) / Interferon Type I (NLM Chemicals)},
      cin          = {B330 / HD01},
      ddc          = {610},
      cid          = {I:(DE-He78)B330-20160331 / I:(DE-He78)HD01-20160331},
      pnm          = {312 - Funktionelle und strukturelle Genomforschung
                      (POF4-312)},
      pid          = {G:(DE-HGF)POF4-312},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:40611262},
      pmc          = {pmc:PMC12231911},
      doi          = {10.1186/s12967-025-06628-7},
      url          = {https://inrepo02.dkfz.de/record/302809},
}