Screening and identification of novel promoter signatures in clear cell renal cell carcinoma metastasis.

Abstract

737 Background: Clear cell renal cell carcinoma (ccRCC) patient usually face aggressive progression when metastasis occurs. Therefore, in-depth investigation is needed to elucidate underlying mechanisms behind the metastasis of ccRCC to promote therapeutic benefits.This study aims to explore and investigate prognostic gene expression profiles based on multi-cohorts. Methods: Three microarray datasets were obtained from the Gene Expression Omnibus (GEO) database to screen and identify differentially expressed genes (DEGs) according to normalization annotation information. A total of 112 DEGs with functional enrichment were identified as candidate prognostic biomarkers. A protein–protein interaction network (PPI) of DEGs was developed, and the modules were analyzed using STRING and Cytoscape. Results: LASSO Cox regression suggested 31 significant involved genes, and 10 hub genes were identified as independent oncogenes in ccRCC patients. Distinct integrated scores of the hub genes mRNA expression showed statistical significance in predicting disease-free survival (DFS; p<0.001) and overall survival (OS; p<0.001) in TCGA and real-world cohorts. Meanwhile, ROC curves were constructed to validate specificity and sensitivity of the Cox regression penal to predict prognosis. The AUC index for the integrated genes scores was 0.758 for OS and 0.772 for DFS. Conclusions: In conclusion,the present study identifies DEGs and hub genes that may be involved in earlier recurrence and poor prognosis of ccRCC. The expression levels of ADAMTS9, C1S, DPYSL3, H2AFX, MINA, PLOD2, RUNX1, SLC19A1, TPX2 and TRIB3 are of high prognostic value, and may help us understand better the underlying carcinogenesis or progression of ccRCC.