Zaravinos A 1 , Lambrou GI 2 , Mourmouras N 3 , Delakas D 3 , Deltas C 1

1. miRNA implication in the most common subtypes of renal cell carcinoma (RCC) and urothelial cell carcinoma of the upper urinary tract (UUT-UCC) Zaravinos A1, Lambrou GI2, Mourmouras N3, Delakas D3, Deltas C1 1 Molecular Medicine Research Center and Laboratory of Molecular and Medical Genetics, Department of Biological Sciences, University of Cyprus, Kallipoleos 75, 1678, Nicosia, Cyprus. 2 First Department of Pediatrics, Choremeio Research Laboratory, University of Athens, Athens 11527, Greece. 3Department of Urology, Asklipieio General Hospital, Athens, Greece. Renal cell carcinoma (RCC) is composed of various morphologically and cytogenetically distinct subtypes, the most prevalent of which are clear cell RCC (ccRCC, 75-80%), papillary RCC (papRCC, 10-15%) and chromophobe RCC (chRCC, 5%). Upper urinary tract urothelial cell carcinoma (UUT-UCC) of the renal pelvis is an aggressive tumour, which may invade the renal parenchyma, mimicking primary RCC. MicroRNAs (miRNAs) are small non-coding RNAs that modulate cellular differentiation, growth, apoptosis and proliferation. MiRNA profiling is used to distinguish different tumour entities among them. The aim of the present study was to identify miRNA signatures that can distinguish accurately RCC from UUT-UCC of the renal pelvis, and the most common RCC subtypes among them. MiRNA profiling was performed on FFPE sections from 27 RCCs (19 ccRCCs, 5 papRCCs and 3 chRCCs), 4 UUT-UCCs of the renal pelvis and 20 control samples. qRT-PCR and LNA-ISH were used to validate the expression of the most significantly deregulated miRNAs. MiRNA expression levels were correlated with tumour stage, grade, and size, as well as among them. The chromosomal distribution of the differentially expressed miRNAs was compared with reported genomic alterations in the RCC subtypes and UUT-UCC. The miRNA targets were predicted using miRWalk. Hypergeometric analysis was used to identify canonical pathways and curated networks having statistically significant enrichment of the deregulated miRNAs and their gene targets, in each RCC subtype and UUT-UCC. CONCLUSIONS BACKGROUND / OBJECTIVE RESULTS METHODS (A) (B) Fig. 1. Volcano plot depicting the 434 significantly deregulated miRNAs in tumor vs. normal. Fig. 2. Unsupervised two-way hierarchical clustering (HCl) with Euclidian distance. (C) (D) Fig. 8. The associated functions of the major miRNA networks were: (A) ccRCC: Inflammatory disease, Inflammatory response, renal inflammation (score=30); (B) papRCC: Endocrine System Disorders, Reproductive System Disease, Cellular Development (score=22); (C) chRCC: Hereditary Disorder, Skeletal and Muscular Disorders, Developmental Disorder (score=22); (D) UUT-UCC: Connective Tissue Disorders, Inflammatory Disease, Inflammatory Response (score=25). Fig. 4. Microarray and qRT-PCR revealed similar deregulation patterns in ccRCC (A), papRCC (B), chRCC (C) and UUT-UCC (D). Fig. 3. qRT-PCR validated the majority of the deregulated miRNAs in ccRCC vs. the normal kidney. The majority of the miRNAs (69.8%) was down-regulated in RCC (Fig. 1). Unsupervised hierarchical clustering with Euclidian distance accurately discriminated between RCC and UUT-UCC. Apart from one chRCC sample that was clustered with ccRCCs, HCl also managed to successfully classify the RCC subtypes among them. HCl showed that ccRCC is more closely related to papRCC and that both are distinct from chRCC or UUT-UCC (Fig. 2). qRT-PCR validated the expression of miR-3648, miR-489, miR-638, miR-3656, miR-3687, miR-663b, miR-25-5p and miR-21-5p in ccRCC (Fig. 3). Microarray and qRT-PCR results revealed similar expression patterns (Fig. 4). MiR-25-5p high expression was confirmed in all ccRCC, papRCC and chRCC sections by LNA-ISH and its expression was significantly stronger compared to their corresponding normal tissues. More aggressive ccRCCs also stained stronger than the less aggressive ones (Fig. 5). Chromosomal distribution analysis revealed that, for each RCC subtype, miRNAs had deregulated patterns that agreed with some of the previously reported chromosomal gains and losses (Fig. 6). Four major gene networks were constructed by IPA for the DE miRNA targets in each RCC subtype and in UUT-UCC, with scores≥22 (Fig. 7). Fig. 5. MiR-25-5p high expression was confirmed in all ccRCC and papRCC sections and stained stronger compared to their corresponding normal tissue sections. More aggressive ccRCCs stained stronger than the less aggressive ones. miRNA detection was confined to the cytoplasm. The nuclear expression of U6 snRNA (positive control) was confirmed in all the patient samples, whereas the scrambled oligonucleotide was negative in all samples. We provide a thorough investigation of the miRNAs implicated in the most common RCC subtypes and UUT-UCC of the renal pelvis, showing how they may contribute to kidney cancer pathogenesis. Deregulated miRNAs represent potential biomarkers for kidney cancer. Fig. 7. In each RCC subtype, miRNAs had deregulated patterns that agreed with some of the previously reported chromosomal gains and losses; i.e., up-regulated miRNAs were located in regions of chromosomal gains and vice versa.