J Cancer 2016; 7(14):1960-1967. doi:10.7150/jca.16123 This issue
1. C.A.R.S.O. Consortium, Valenzano, Italy;
2. Schena Foundation - European Research Center for Kidney Diseases, Valenzano, Italy;
3. DETO, Nephrology, Dialysis and Transplantation Unit, University of Bari, Italy;
4. DETO, Urology, Andrology and Kidney Transplantation Unit, University of Bari, Italy;
5. IRCCS "de Bellis", Laboratory of Experimental Immunopathology, Castellana Grotte, Italy.
Renal cell carcinoma (RCC) accounts for more than 2% of neoplasias in humans worldwide. Renal biopsy is the gold standard among the diagnostic procedures, but it is invasive and not suitable for all patients. Therefore, new reliable and non-invasive biomarkers for RCC are required. Secretion of extracellular vesicles (EVs), containing RNA molecules that can be transferred between cells, appears to be a common feature of neoplasia. Consistently, cancer-derived EVs are increased in blood and urine. Therefore, urinary samples may be a non-invasive approach for discovering new diagnostic biomarkers.
We enrolled 46 patients of whom 33 with clear cell renal cell carcinoma (ccRCC) and 22 healthy subjects (HS). Urinary EVs were isolated by differential centrifugation. Microarray analysis led to the identification of RNA molecules that were validated using RT-qPCR.
We found that urinary exosomal shuttle RNA (esRNA) pattern was significantly different in ccRCC patients compared to HS and to non-clear cell RCC (non-ccRCC) and we identified three esRNAs involved in the tumor biology that may be potentially suitable as non-invasive gene signature. GSTA1, CEBPA and PCBD1 esRNA levels were decreased in urine of patients compared with HS. This pattern was specific of the ccRCC and one month after partial or radical nephrectomy the esRNA levels increased to reach the normal level.
This study suggests, for the first time, the potential use of the RNA content of urinary EVs to provide a non-invasive first step to diagnose the ccRCC.
Keywords: extracellular vesicles, renal cell carcinoma, gene signature, transcriptomics.