Identification of a RNA-seq-based signature to improve prognostics for uterine sarcoma

Abstract Objective Uterine sarcoma (US) is a highly malignant cancer with poor prognosis and high mortality. This study focused on the identification of a RNA-Seq expression signature for prognosis prediction in uterine sarcoma. Methods We obtained RNA-Seq expression profiles from The Cancer Genome Atlas database, and differentially expressed genes were identified between US tissues and normal tissues. Univariate Cox proportional hazards regression analysis and LASSO Cox model were performed to identify and construct the prognostic gene signature. Time-dependent receiver operating characteristic, Kaplan-Meier curve and multivariate Cox regression analysis were used to assess the prognostic capacity of the six-gene signature. The nomogram was developed including prognostic signature and independent clinical factors to predict the overall survival (OS) of US patients. The functional enrichment and somatic mutation analysis were also analyzed by bioinformatics to understand the molecular mechanisms. Results This study identified a prognostic signature based on 6 genes: FGF23, TLX2, TIFAB, RNF223, HIST1H3A and AADACL4. In the training group, the median OS in the high- and low-risk groups was 19.6 vs 88.1 months (HR, 0.1412, 95% CI: 0.03295 - 0.6054; P = 0.002), respectively. In the testing group, the median OS in the high- and low-risk groups were 30 vs NR (not reach) months (HR, Conclusion Our study established a novel 6-gene signature and nomogram which could improve prognosis prediction in patients with US.