Integrative bioinformatics analysis and experimental validation identify CHEK1 as an unfavorable prognostic biomarker related to immunosuppressive phenotypes in soft tissue sarcomas - Rong, Chao; Liu, Yun; Xiang, Fang; Zhao, Xin; Zhang, Jinjin; Xiao, Zuorun; Wang, Jinsha; Chen, Lin; Guo, Zhiqi; Zhang, Ziyu; An, Jingnan; Shen, Jing; et al. (npj precision oncology, 2025)
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.