Identification of Prognosis- and Metastasis-related Enhancer RNAs in Renal Cell Carcinoma

Abstract

Abstract Background: Renal cell carcinoma (RCC) is one of themost prevalent and lethal malignancies globally. Enhancer RNAs (eRNAs) serve as potential diagnostic and prognostic markers andpotential therapeutic targets for cancer. This study aim to explore the roles of enhancer RNAs (eRNAs) in renal cell carcinoma (RCC) metastasis. Methods: RNA-seq data of RCC samples were downloaded from the TCGA database and MET500 database. And normalized eRNA expression profiles were obtained from the eRic database. The differential expressed eRNAs (DEEs) were identified through differential expression analysis. Then, identification of prognosis-related DEEs and construction of the prognosis model were conducted by univariate and multivariate Cox regression analysis. Moreover, CIBERSORT, ssGSEA and GSVA algorithm were utilized. Finally, we established a co-expression regulation network including key prognosis-related DEEs, transcription factors, hallmarks of cancer, immune cells/gene sets, target genes of eRNAs, and protein chips using Pearson correlation analysis. Moreover, CMap analysis, multidimensional external validation, ChIP, and ATAC-seq were conducted to highlight our study’s reliability. Results: A total of 353 eRNAs were identified as DEEs. 35 prognosis-related DEEs were selected out and a credible prognosis model was established with the Area Under Curve (AUC) of 0.859. In addition, the expression value of 22 kinds of immune cells and 29 immune gene sets were quantified. Ultimately, a co-expression regulation network which consisted of 4 significant prognosis-related DEEs, 11 differential expressed TFs, 23 significant hallmarks of cancer, 13 types of immune cells, 19 immune gene sets, 22 target genes of eRNAs and 20 protein chips was constructed. Conclusion: We illustrated that eRNAs played a significant role in RCC metastasis. Four key prognosis-related DEEs (SHROOM3, PWWP2B, ZSCAN5A and DTNA) were identified as therapeutic targets, metastasis and poor prognosis biomarkers.