Exploration of the cancer genome atlas database reveals genes of interest related with cancer cell stemness indices in clear cell renal cell carcinoma

Abstract

Heterogeneity of kidney cancer poses great challenges in clinical management. Practicians are still in need of an effective way to identify high-risk patients. Here we browsed big data from The Cancer Genome Atlas database with reference to cancer cell stemness and identified genes of interest in clear cell renal cell carcinoma. We further analyzed these genes to uncover their role in cancer promotion and progression and presented an interaction network. The results highlighted the NOTCH signaling pathway and functions related with epithelial cell migration. Finally, we managed to construct a predictive model consisting of a reasonable number of genes that successfully recognized patients at higher risk, rendering these genes suitable as subjects in future research.

Keywords

• Clear cell renal cell carcinoma
• Stemness indices
• TCGA
• Predictive model
• Data mining