Integrated Analysis of Nine Prognostic RNA-Binding Proteins in Soft Tissue Sarcoma

Abstract

RNA-binding proteins (RBPs) have been shown to be dysregulated in cancer transcription and translation, but few studies have investigated their mechanism of action in soft tissue sarcoma (STS). Here, The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases were used to identify differentially expressed RBPs in STS and normal tissues. Through a series of biological information analyses, 329 differentially expressed RBPs were identified. Functional enrichment analysis showed that differentially expressed RBPs were mainly involved in RNA transport, RNA splicing, mRNA monitoring pathways, ribosome biogenesis and translation regulation. Through Cox regression analyses, 9 RBPs (BYSL, IGF2BP3, DNMT3B, TERT, CD3EAP, SRSF12, TLR7, TRIM21 and MEX3A) were all up-regulated in STS as prognosis-related genes, and a prognostic model was established. The model calculated a risk score based on the expression of 9 hub RBPs. The risk score could be used for risk stratification of patients and had a high prognostic value based on the receiver operating characteristic (ROC) curve. We also established a nomogram containing risk scores and 9 key RBPs to predict the 1-year, 3-year, and 5-year survival rates of patients in STS. Afterwards, methylation analysis showed significant changes in the methylation degree of BYSL, CD3EAP and MEX2A. Furthermore, the expression of 9 hub RBPs was closely related to immune infiltration rather than tumor purity. Based on the above studies, these findings may provide new insights into the pathogenesis of STS and will provide candidate biomarkers for the prognosis of STS.