Abstract
Sarcoma (SARC), a diverse group of stromal tumors arising from mesenchymal tissues, is often associated with a poor prognosis. Emerging evidence indicates that senescent cells within the tumor microenvironment (TME) significantly contribute to cancer progression and metastasis. Although the influence of senescence on SARC has been partially acknowledged, it has yet to be fully elucidated. In this study, we revealed that senescence level and age were associated with TME, immune treatment indicators, and prognosis in SARC. Utilizing the weighted gene co-expression network analysis and least absolute shrinkage and selection operator algorithm, we identified senescence-related genes and developed a senescence predictor. Three genes, RAD54, PIK3IP1, and TRIP13, were selected to construct a multiple linear regression model. Validation cohorts, immunohistochemistry, and quantitative reverse transcription polymerase chain reaction confirmed that the predictor derived from these three genes possessed prognostic and pathological relevance. Our senescence predictor provides comprehensive insights into the molecular mechanisms of SARC and identifies potential biomarkers for prognosis, paving the way for effective treatments. The results of this study hold promise for developing therapeutic strategies tailored to the unique characteristics of SARC.