INTEGRATED GENOMICS ANALYSIS OF GENE AND MICRORNA EXPRESSION PROFILES IN CLEAR CELL RENAL CARCINOMA CELL LINES

Renal cell carcinoma (RCC) is the most common neoplasm of the adult kidney, accounting for a total of 2-3% of adult neoplasias, and it arises from the renal epithelium. Clear cell renal cell carcinoma (ccRCC) is the most common, invasive and metastatic among RCC subtypes, representing 75-80% of kidney primary malignancies. The von Hippel-Lindau (VHL) gene, which is the main tumor suppressor gene involved in early steps of RCC tumorigenesis, undergoes complete inactivation by mutation, deletion, and promoter methylation in the majority of sporadic ccRCCs and in all inherited forms. Defining the prognosis for RCC cases is important for both decision-making and counseling patients, but sometimes the diagnosis is difficult because tumor subtypes have overlapping histo-pathological features, thus resulting undistinguishable by microscopy investigation. In recent years, in several human cancers, microarray gene expression profiling proved to be a powerful tool to better classify tumor subtypes and to identify novel molecular biomarkers potentially useful for clinical applications. In fact, tumor transcriptomic profiling may identify patterns of genes that are functionally related to patients’ prognosis, response to therapy and overall survival. Recent evidences have shown that microRNA (miRNA) molecules are involved in tumorigenesis, indicating that miRNAs might function as both tumor suppressors and oncogenes, and their role in RCC pathogenesis is now emerging. miRNAs are small single-stranded non-protein-coding RNA molecules, that function as negative post-transcriptional gene regulators in animals, plants and viruses, and are involved in many biological processes, also including haematopoietic cell differentiation, apoptosis, cell proliferation and organ development. miRNA and gene expression patterns are closely related, since they cooperatively work to create gene regulatory networks. Therefore, integrative genomics approach might be a useful tool to elucidate the complex relationships underlying these networks. The aim of my PhD fellowship work was to reconstruct miRNA-gene post-transcriptional regulatory networks involved in RCC biology, using miRNA and gene expression profiles of three RCC cell lines compared to a normal one, obtained by Affymetrix high-density microarray technology. We calculated differentially expressed genes and miRNAs, and, by functional enrichment analysis, we identified genes and miRNAs that were already known to be associated with RCC and involved in relevant pathways for this pathology, such as hypoxia, p53 signaling, focal adhesion, angiogenesis and mTOR signaling. Through integrated analysis of miRNA-gene expression profiles, we reconstructed potentially active regulatory networks involving miRNAs and their predicted target genes. We validated some miRNA-gene pairs by quantitative PCR, thus confirming their anti-correlated expression levels. Our results demonstrated that RCC cell lines can be an useful in vitro model for RCC pathology, since they showed gene and miRNA expression profiles similar to renal tumoral tissues, as obtained by comparing our results with published data. The analysis of the correlations between gene and miRNA expression profiles using a genome-wide integrative approach could help the identification of both post-transcriptional regulatory networks and novel candidate markers functionally relevant for RCC pathology. However, further investigations are necessary to elucidate the actual role of miRNA-gene networks in the context of RCC progression and outcome.