This is the authors' abstract. We don't add key points for this paper.
Soft tissue sarcomas (STS) are rare and heterogeneous cancers with unpredictable clinical outcomes. Existing prognostic models based on histology and staging often fail to capture tumor dynamics, especially in the era of immunotherapy. Within the tumor microenvironment (TME), crosstalk between tumor-associated macrophages (TAMs) and cancer-associated fibroblasts (CAFs) plays a central role in promoting immunosuppression, therapy resistance, and metastasis. This bidirectional interaction occurs via cytokines, exosomes, direct contact, and metabolic coupling, facilitating immune evasion and matrix remodeling. Evidence suggests that quantifying TAMs-CAFs interactions using immunohistochemical or gene expression signatures correlates with poor prognosis, offering a potential tool for risk stratification. However, technical and standardization challenges, patient heterogeneity, and incomplete mechanistic understanding limit clinical translation. Future progress will require AI-integrated multimodal analysis and personalized frameworks combining stromal interaction metrics with clinical variables to enable dynamic monitoring and precision therapy in STS.
Answers are grounded in this paper and cite their sources.
No takes yet. Share an insight, caveat, or question.
Zhou et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: