Related Experiment Video
Updated: Sep 13, 2025
Author Spotlight: Unveiling Transmembrane Protein Family-Related Markers in Gastric Cancer and Implications for Targeted Therapies
Published on: September 15, 2023
Integrative bioinformatics analysis and experimental validation identify CHEK1 as an unfavorable prognostic biomarker
Chao Rong1, Yun Liu2,3, Fang Xiang4
1Department of Pathology, School of Basic Medical Sciences, Suzhou Medical College, Soochow University, Suzhou, Jiangsu, China. chaorong@suda.edu.cn.
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.
Insights
This study reveals distinct immune phenotypes in soft tissue sarcomas (STS), including rhabdomyosarcoma (RMS). CHEK1 is identified as a potential therapeutic target to improve immune checkpoint blockade (ICB) therapy response.
Area of Science:
- Oncology
- Immunology
- Genomics
Background:
- Soft tissue sarcomas (STS), including rhabdomyosarcoma (RMS), are heterogeneous and poorly responsive to immune checkpoint blockade (ICB).
- Understanding the tumor immune microenvironment of STS through multi-omics profiling is crucial for identifying new therapeutic strategies.
Purpose of the Study:
- To investigate the tumor immune phenotype of STS using multi-omics expression profiling.
- To develop a molecular classifier for distinct immune phenotypes and identify potential therapeutic targets.
Main Methods:
- Multi-omics expression profiling of various STS subtypes.
- Development of a molecular classifier based on immune cell subsets related to TGFβ1 and IFNγ.
- In situ analysis of independent validation cohorts.
Main Results:
- Identified distinct immune-high and immune-low clusters with differing immune cell infiltration and clinical outcomes.
- Immune-high clusters showed enriched immune cell infiltration and favorable prognosis.
- Immune-low clusters were associated with immunosuppressive cells, poor survival, and overexpression of CHEK1.
Conclusions:
- Established a novel risk assessment strategy for STS and RMS patients.
- Highlighted CHEK1 as a potential therapeutic target, particularly in combination with ICB therapy.
- Demonstrated the correlation between CHEK1 and tumor-infiltrating immune cells in independent cohorts.
