In Vitro and In Silico Analysis of Epithelial-Mesenchymal Transition and Cancer Stemness as Prognostic Markers of Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is a highly aggressive cancer responsible for about 85% of kidney cancers. The majority of the incidentally detected renal masses are small and confined to the kidney; however, a significant number of patients initially present with progressive metastatic cancer succumb to the disease in a short time frame. High levels of expression of hypoxia-inducible transcription factors (HIF) resulting in the downstream epithelial-mesenchymal transition (EMT) pathway and features of cancer stem cells (CSCs) leads to an aggressive and drug-resistant phenotype in ccRCC. In this paper, using data from in-house collected patient tumours and public domain datasets, we highlight EMT and CSC to be prominent players in ccRCC progression. Using these approaches of analysis, we show the development of multi-marker diagnostic and prognostic signatures, which may stratify high-risk patients likely to progress to metastatic disease. The process of epithelial-mesenchymal transition (EMT) involves the phenotypic transformation of cells from epithelial to mesenchymal status. The cells exhibiting EMT contain features of cancer stem cells (CSC), and the dual processes are responsible for progressive cancers. Activation of hypoxia-inducible factors (HIF) is fundamental to the pathogenesis of clear cell renal cell carcinoma (ccRCC), and their role in promoting EMT and CSCs is crucial for ccRCC tumour cell survival, disease progression, and metastatic spread. In this study, we explored the status of HIF genes and their downstream targets, EMT and CSC markers, by immunohistochemistry on in-house accrued ccRCC biopsies and adjacent non-tumorous tissues from patients undergoing partial or radical nephrectomy. In combination, we comprehensively analysed the expression of HIF genes and its downstream EMT and CSC-associated targets relevant to ccRCC by using publicly available datasets, the cancer genome atlas (TCGA) and the clinical proteome tumour analysis consortium (CPTAC). The aim was to search for novel biological prognostic markers that can stratify high-risk patients likely to experience metastatic disease. Using the above two approaches, we report the development of novel gene signatures that may help to identify patients at a high risk of developing metastatic and progressive disease.