Mining TCGA to Reveal Immunotherapy-related Genes for Soft Tissue Sarcoma

Objective: By mining the TCGA database to look for immunotherapy targets of soft tissue sarcoma, and analyzed their biological behavior. Methods: The data of 265 samples were downloaded from the TCGA database to analyze the expression profile of soft tissue sarcomas. Research methods include immune and stromal scores, calculating DEGs, volcano maps and differential gene survival curves, gene enrichment analysis. Results: Kaplan-Meier survival curves showed that in the high immune score group, the total survival time was generally higher than that in the low immune score group. Analysis of the top ten terms resulted in the minimum P values for immune and inflammatory responses, plasma membrane, receptor activity, and chemokine activity. By plotting the K-M curves, we obtained 86 survivals related DEGs. Finally, the genes that can be used as independent risk factors for prognosis of soft tissue sarcoma were obtained by multivariate analysis of the DEGs. Conclusion: We believe that these genes are expected to be new targets for sarcoma immunotherapy and key genes for the analysis of prognosis of sarcoma.