Comprehensive assessment of cellular senescence and aging in the tumor microenvironment of sarcoma

Abstract

Abstract SARC (sarcoma) is a heterogeneous group of stromal tumors originating from mesenchymal tissues with poor prognosis. There is growing evidence that senescent cells in the tumor microenvironments (TME) are associated with the development and metastasis of cancer. The impact of senescence on sarcomas has been initially recognized, but not fully understood. Here, we revealed that senescence level and age were both associated with TME, immune treatment indicators and prognosis in SARC. WGCNA and least-selection absolute regression algorithm (LASSO) were used to track senescence-related genes and create a senescence predictor. Consequently, the three genes (RAD54, PIK3IP1, TRIP13) were selected to construct a multiple linear regression model. Through validation cohorts, IHC and qPCR, the predictors conducted by the three genes were proved to have prognostic and pathological significance. The senescence predictor may provide a novel insight into the study of molecular mechanisms and candidate biomarkers for the prognosis, resulting in effective treatments for SARC.