Integrative bioinformatics analysis and experimental validation identify CHEK1 as an unfavorable prognostic biomarker related to immunosuppressive phenotypes in soft tissue sarcomas

Rhabdomyosarcoma (RMS) represents one of the most common soft tissue sarcoma (STS) in children and adolescents. Transforming growth factor beta 1 (TGFβ1) is a potent inhibitor of myogenic differentiation in RMS and plays a significant function in the tumour immune microenvironment. Currently, unsupervised tumor immune phenotype based on multi-omics expression profiling has been less studied. To reveal the tumour immune phenotype of STS and identify promising therapeutic targets, multi-omics expression profiling in 363 tumours across subtypes of STS was investigated. Here, we validated the TGFβ1 signal function in RMS myogenic differentiation and established a novel molecular classifier based on immune cell subsets related to TGFβ1 and Interferon-γ (IFNγ) to identify distinct immune phenotypes with higher or lower cytotoxic contents. Moreover, we compared multi-omics expression profiling across subgroups of RMS and STS to identify CHEK1 as an unfavourable prognostic biomarker related to immunosuppressive phenotypes. In situ analysis of independent validation cohorts addresses the correlation between CHEK1 and tumour-infiltrating immune cells. Collectively, our data validate the TGFβ1 signal function in RMS myogenic differentiation and establish a novel risk assessment strategy for RMS and STS patients. This work potentially improves risk assessment for STS patients and offers a new therapeutic strategy to increase antitumor immunity through the combined targeting of CHEK1 inhibition.