% 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{Rong:303360,
      author       = {C. Rong and Y. Liu and F. Xiang and X. Zhao and J. Zhang
                      and Z. Xiao and J. Wang and L. Chen and Z. Guo and Z. Zhang
                      and J. An and J. Shen and J. Hess$^*$ and X. Yuan and Q.
                      Zhang and S. Wang},
      title        = {{I}ntegrative bioinformatics analysis and experimental
                      validation identify {CHEK}1 as an unfavorable prognostic
                      biomarker related to immunosuppressive phenotypes in soft
                      tissue sarcomas.},
      journal      = {npj precision oncology},
      volume       = {9},
      number       = {1},
      issn         = {2397-768X},
      address      = {[London]},
      publisher    = {Springer Nature},
      reportid     = {DKFZ-2025-01610},
      pages        = {268},
      year         = {2025},
      abstract     = {Soft tissue sarcomas (STS), including rhabdomyosarcoma
                      (RMS), exhibit significant heterogeneity and limited
                      responsiveness to immune checkpoint blockade (ICB).
                      Unsupervised tumor immune phenotype based on multi-omics
                      expression profiling of STS has been less studied. To reveal
                      the tumor immune phenotype of STS and identify promising
                      therapeutic targets, multi-omics expression profiling across
                      various subtypes of STS was investigated. Here, we
                      established a novel molecular classifier based on immune
                      cell subsets related to TGFβ1 and IFNγ to identify
                      distinct immune phenotypes with higher or lower cytotoxic
                      contents. Immune-high clusters demonstrated enriched immune
                      cell infiltration, elevated IFNγ-related signatures, and
                      favorable clinical outcomes. In contrast, immune-low
                      clusters were enriched for immunosuppressive cell types and
                      exhibited poor survival. CHEK1 emerged as a key node
                      associated with immunosuppressive phenotypes and was
                      significantly overexpressed in immune-low tumors. In situ
                      analysis of independent validation cohorts revealed the
                      significant correlation between CHEK1 and tumor-infiltrating
                      immune cells. Collectively, our findings establish a novel
                      risk assessment strategy for RMS and STS patients, and
                      highlight the potential of CHEK1 as a promising therapeutic
                      target in combination with immune checkpoint inhibitor
                      therapy.},
      cin          = {E221},
      ddc          = {610},
      cid          = {I:(DE-He78)E221-20160331},
      pnm          = {315 - Bildgebung und Radioonkologie (POF4-315)},
      pid          = {G:(DE-HGF)POF4-315},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:40751074},
      pmc          = {pmc:PMC12317078},
      doi          = {10.1038/s41698-025-01064-8},
      url          = {https://inrepo02.dkfz.de/record/303360},
}