Molecular characterization of ferroptosis in soft tissue sarcoma constructs a prognostic and immunotherapeutic signature through experimental and bioinformatics analyses.

Ferroptosis regulators have been found to affect tumor progression. However, studies focusing on ferroptosis and soft tissue sarcoma (STS) are rare. Somatic mutation, copy number variation, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis, consensus clustering, differentially expressed genes analysis (DEGs), principal component analysis (PCA) and gene set enrichment analysis (GSEA) were used to identify and explore different ferroptosis modifications in STS. A nomogram was constructed to predict the prognosis of STS. Moreover, three immunotherapy datasets were used to assess the Fescore. Western blotting, siRNA transfection, EdU assay and reactive oxygen species (ROS) measurement were performed. 16 prognostic ferroptosis regulators were screened and significant differences were observed in somatic mutation, copy number variation (CNV) and RT-qPCR among these ferroptosis regulators. 2 different ferroptosis modification patterns were found (Fe cluster A and B). Fe cluster A with higher Fescore was correlated with p53 pathway and had better prognosis of STS (p = 0.002) while Fe cluster B with lower Fescore was correlated with angiogenesis and MYC pathway and showed a poorer outcome. Besides, the nomogram effectively predicted the outcome of STS and the Fescore could also well predict the prognosis of other 16 tumors and immunotherapy response. Downregulation of LOX also inhibited growth and increased ROS production in sarcoma cells. The molecular characterization of ferroptosis regulators in STS was explored and an Fescore was constructed. The Fescore quantified ferroptosis modification in STS patients and effectively predicted the prognosis of a variety of tumors, providing novel insights for precision medicine.

Molecular Characteristics of m6A Regulators and Tumor Microenvironment Infiltration in Soft Tissue Sarcoma: A Gene-Based Study.

Background: N6-methyladenosine (m6A) methylation played a key role in tumor growth. However, the relationship between m6A and soft tissue sarcoma (STS) was still unclear. Methods: The characterization and patterns of m6A modification in STS (TCGA-SARC and GSE17674) were analyzed comprehensively through bioinformatics and real-time polymerase chain reaction (RT-PCR). The effects of different m6A modification patterns on prognosis and immune infiltration of STS were further explored. Differentially expressed gene (DEG) analysis was performed. Moreover, an m6Ascore was constructed by principal component analysis (PCA). In addition, two immunotherapy datasets (IMvigor210 and GSE78220) and a sarcoma dataset (GSE17618) were used to evaluate the m6Ascore. Results: Huge differences were found in somatic mutation, CNV, and expression of 25 m6A regulators in STS. Two modification patterns (A and B) in STS were further identified and the m6A cluster A showed a better clinical outcome with a lower immune/stromal score compared with the m6A cluster B (p < 0.050).In addition to , most STS samples from m6A cluster A showed a high m6Ascore, which was related to mismatch repair and a better prognosis of STS (p < 0.001). In contrast, the m6A cluster B, characterized by a low m6Ascore, was related to the MYC signaling pathway, which led to a poor prognosis of STS. A high m6Ascore also contributed to a better outcome of PD-1/PD-L1 blockade immunotherapy. Conclusion: The modification patterns of 25 m6A regulators in the STS microenvironment were explored comprehensively. The novel m6Ascore effectively predicted the characteristics of the tumor microenvironment (TME) and outcome in STS and provided novel insights for future immunotherapy.