Risk stratification of soft tissue sarcoma based on activity of prognostic molecules associated with unpolarized macrophages

Introduction Soft tissue sarcomas (STS), representing 80% of sarcomas, are a rare and diverse group of neoplasms with a dire prognosis. Macrophages and their subtypes play an essential role with diverse outcomes in the tumor microenvironment (TME) of cancers, including sarcomas. The aim of this study was to investigate the role of macrophages in the development and prognosis of sarcoma patients. Material and methods Transcriptomic data from 5 sarcoma cohorts including 581 patients and transcripts of 56,752 single cells from 6 sarcoma patients were retrieved from public databases and analyzed. The infiltration of immune cells in the TME was evaluated with the CIBERSORT algorithm. Kaplan-Meier estimation with the log-rank test and Cox regression hazards models were adopted for evaluation of prognostic impacts. Results Deconvolution of 22 types of immune cells via the CIBERSORT algorithm revealed macrophages as a prominent component of the TME of sarcoma patients. Of these, M0 was associated with worst prognosis. A six-gene prognostic signature, termed MRPS, was developed that was significantly positively correlated with M0 macrophages. The MRPS-stratified high-risk subgroup showed abundance of M0 macrophages, indicating inhibition of macrophage polarization, specifically the classically activated pro-inflammatory M1 phenotype. Moreover, enrichment of oncogenic pathways and glycolysis and high frequency of mutations were evident. The robustness of the MRPS as a predictive biomarker was validated in external soft-tissue sarcoma patient datasets. A nomogram based on MRPS was developed as a potentially accurate and practical predictive tool for identifying high-risk sarcoma patients with lower survival probabilities. Furthermore, the MRPS signature exhibited reliable predictive capabilities for immunotherapy response, suggesting its potential to enhance the effectiveness of personalized immunotherapy in sarcoma patients. Conclusions MRPS represents a robust biomarker for predicting outcomes and response to therapy in soft-tissue sarcoma patients.