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Article Abstract
Immunotherapy of soft tissue sarcoma is considered an important development direction for the future. Bioinformatics analysis of genetic changes in tumors and the immune microenvironment around tumors has proven to be a mature and reliable method for predicting tumor prognosis. By mining the Cancer Genome Atlas Program database, we found immunotherapy targets of soft tissue sarcoma and analyzed their biological behavior. The data of 265 samples were downloaded to analyze the expression profile of soft tissue sarcomas. This included calculating tumor purity through the estimation of stromal and immune cells in malignant tumors using expression data, acquisition of differential genes as prognostic factors, and enrichment analysis of the differential genes. Survival analysis showed longer overall survival times for patients with higher immune scores. We obtained 83 survival-related differential genes through survival analysis, and 23 genes that could be used as independent risk factors for the prognosis of soft tissue sarcoma were obtained by multiple regression analysis of the differential genes and other recognized risk factors. Gene set enrichment analysis of the differential genes obtained immune and inflammatory gene ontology terms and signal pathways, including regulation of the T-cell apoptotic process and leukocyte transendothelial migration. After validation in an independent data set of the Gene Expression Omnibus database, 12 genes were confirmed as a result. We believe that these differential genes will be new targets for sarcoma immunotherapy and key genes for the prognosis of soft tissue sarcoma.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11875607 | PMC |
| http://dx.doi.org/10.1097/MD.0000000000041392 | DOI Listing |
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