%0 Journal Article
%A Rong, Chao
%A Liu, Yun
%A Xiang, Fang
%A Zhao, Xin
%A Zhang, Jinjin
%A Xiao, Zuorun
%A Wang, Jinsha
%A Chen, Lin
%A Guo, Zhiqi
%A Zhang, Ziyu
%A An, Jingnan
%A Shen, Jing
%A Hess, Jochen
%A Yuan, Xiaodong
%A Zhang, Qiong
%A Wang, Shouli
%T Integrative bioinformatics analysis and experimental validation identify CHEK1 as an unfavorable prognostic biomarker related to immunosuppressive phenotypes in soft tissue sarcomas.
%J npj precision oncology
%V 9
%N 1
%@ 2397-768X
%C [London]
%I Springer Nature
%M DKFZ-2025-01610
%P 268
%D 2025
%X 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.
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:40751074
%2 pmc:PMC12317078
%R 10.1038/s41698-025-01064-8
%U https://inrepo02.dkfz.de/record/303360