Abstract

As the most common transcriptional regulators, zinc finer proteins (ZNFs) play vital roles in occurrence and progression of malignant tumors. Whereas, information regarding the roles of ZNFs in soft tissue sarcomas (STS) remains scarce. In this study, a comprehensive bioinformatics analysis investigating roles of ZNFs in STS was performed. Initially, we extracted raw datasets of differentially expressed ZNFs from GSE2719. Using a sequence of bioinformatics methods, we then investigated the prognostic significance, function, and molecular subtype of these differentially expressed ZNFs. In addition, CCK8 and plate clone formation assays were used to explore the effect of ZNF141 on STS cells. A total of 110 differentially expressed ZNFs were identified. Nine ZNFs (HLTF, ZNF292, ZNF141, LDB3, PHF14, ZNF322, PDLIM1, NR3C2, and LIMS2) were selected to establish an overall survival (OS) prediction model, and seven ZNFs (ZIC1, ZNF141, ZHX2, ZNF281, ZNHIT2, NR3C2, and LIMS2) were used to develop a progression-free survival (PFS) prediction model. Compared with patients with low-risk in the TCGA training and testing cohorts, as well as the GEO validation cohorts, patients with high-risk had poorer OS and PFS. Using nomograms constructed with the identified ZNFs predicting OS and PFS, we established a clinically useful model. Four distinct molecular subtypes with different prognostic and immune infiltration characteristics were identified. In vitro experiments showed that ZNF141 promoted the proliferation and viability of STS cells. In conclusion, ZNF-related models are useful as prognostic biomarkers, suggesting their potentials as therapeutic targets in STS. These findings will enable us to develop novel strategies treating STS, which will potentially improve outcomes of patients with STS.