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Background Dedifferentiated liposarcoma, a member of malignant mesenchymal tumors, has a high local recurrence rate and poor prognosis. Pyroptosis, a newly discovered programmed cell death, is tightly connected with the progression and outcome of tumor. However, the role of pyroptosis in Dedifferentiated liposarcoma remained unclear. Methods We obtained the RNA sequencing data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases to identify different pyroptosis-related genes (PRGs) expression patterns. An unsupervised method for clustering based on PRGs was performed. Clinical outcomes and immune microenvironment varied with the clusters according to the result of cluster analysis. The differentially expressed genes between the two clusters were used to develop a prognosis model by LASSO Cox regression method, followed by the performance of functional enrichment analysis and single-sample gene set enrichment analysis(ssGSEA). All of the above results were validated in Gene Expression Omnibus (GEO) dataset. Results Forty-one differentially expressed PRGs were found between tumor and normal tissues. DDL patients were classified into two clusters using consensus clustering analysis based on PRGs. Cluster 2 showed a better outcome, higher immune scores, stronger immune cells abundances, and elevated expression levels in numerous immune checkpoints compared with Cluster 1. Differentially expressed genes (DEGs) between clusters were identified. A total of 5 gene signature was built based on the DEGs and divided all DDL patients of the TCGA cohort into low-risk and high-risk groups. The low-risk group indicated greater inflammatory cell infiltration and better outcome. External validation verified significant differences of survival and immune landscape again between two risk groups of GEO cohort. Receiver operating characteristic (ROC) curves implied that risk model could exert its great value in predicting DDL patients’ prognoses. Conclusion Our findings revealed the clinical implication and key role in tumor immunity of pyroptosis-related genes in dedifferentiated liposarcoma. The risk model is a promising predictive tool, which could provide a fundamental basis for future studies and individualized immunotherapy.

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