dc.contributor.author | Zaravinos, Apostolos | en |
dc.contributor.author | Lambrou, George I. | en |
dc.contributor.author | Mourmouras, Nikos | en |
dc.contributor.author | Katafygiotis, Patroklos | en |
dc.contributor.author | Papagregoriou, Gregory N. | en |
dc.contributor.author | Giannikou, Krinio | en |
dc.contributor.author | Delakas, Dimitrios S. | en |
dc.contributor.author | Constantinou-Deltas, Constantinos D. | en |
dc.creator | Zaravinos, Apostolos | en |
dc.creator | Lambrou, George I. | en |
dc.creator | Mourmouras, Nikos | en |
dc.creator | Katafygiotis, Patroklos | en |
dc.creator | Papagregoriou, Gregory N. | en |
dc.creator | Giannikou, Krinio | en |
dc.creator | Delakas, Dimitrios S. | en |
dc.creator | Constantinou-Deltas, Constantinos D. | en |
dc.date.accessioned | 2019-11-04T12:52:55Z | |
dc.date.available | 2019-11-04T12:52:55Z | |
dc.date.issued | 2014 | |
dc.identifier.issn | 1932-6203 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/53459 | |
dc.description.abstract | Background: Upper tract urothelial carcinomas (UT-UC) can invade the pelvicalyceal system making differential diagnosis of the various histologically distinct renal cell carcinoma (RCC) subtypes and UT-UC, difficult. Correct diagnosis is critical for determining appropriate surgery and post-surgical treatments. We aimed to identify microRNA (miRNA) signatures that can accurately distinguish the most prevalent RCC subtypes and UT-UC form the normal kidney. Methods and Findings: miRNA profiling was performed on FFPE tissue sections from RCC and UT-UC and normal kidney and 434 miRNAs were significantly deregulated in cancerous vs. the normal tissue. Hierarchical clustering distinguished UT-UCs from RCCs and classified the various RCC subtypes among them. qRT-PCR validated the deregulated expression profile for the majority of the miRNAs and ROC analysis revealed their capability to discriminate between tumour and normal kidney. An independent cohort of freshly frozen RCC and UT-UC samples was used to validate the deregulated miRNAs with the best discriminatory ability (AUC>0.8, p<0.001). Many of them were located within cytogenetic regions that were previously reported to be significantly aberrated. miRNA targets were predicted using the miRWalk algorithm and ingenuity pathway analysis identified the canonical pathways and curated networks of the deregulated miRNAs. Using the miRWalk algorithm, we further identified the top anti-correlated mRNA/miRNA pairs, between the deregulated miRNAs from our study and the top co-deregulated mRNAs among 5 independent ccRCC GEO datasets. The AB8/13 undifferentiated podocyte cells were used for functional assays using luciferase reporter constructs and the developmental transcription factor TFCP2L1 was proved to be a true target of miR-489, which was the second most upregulated miRNA in ccRCC. Conclusions: We identified novel miRNAs specific for each RCC subtype and UT-UC, we investigated their putative targets, the networks and pathways in which they participate and we functionally verified the true targets of the top deregulated miRNAs. © 2014 Zaravinos et al. | en |
dc.source | PLoS ONE | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84898417570&doi=10.1371%2fjournal.pone.0091646&partnerID=40&md5=45eac6bd24aa49f1ad85e09252aac73d | |
dc.subject | article | en |
dc.subject | human | en |
dc.subject | Humans | en |
dc.subject | adult | en |
dc.subject | aged | en |
dc.subject | controlled study | en |
dc.subject | female | en |
dc.subject | tumor volume | en |
dc.subject | clinical article | en |
dc.subject | human tissue | en |
dc.subject | cancer staging | en |
dc.subject | cancer diagnosis | en |
dc.subject | kidney carcinoma | en |
dc.subject | Kidney Neoplasms | en |
dc.subject | male | en |
dc.subject | unclassified drug | en |
dc.subject | cancer grading | en |
dc.subject | tissue section | en |
dc.subject | down regulation | en |
dc.subject | gene expression regulation | en |
dc.subject | pathology | en |
dc.subject | upregulation | en |
dc.subject | middle aged | en |
dc.subject | diagnostic value | en |
dc.subject | metabolism | en |
dc.subject | cohort analysis | en |
dc.subject | differential diagnosis | en |
dc.subject | cytogenetics | en |
dc.subject | kidney | en |
dc.subject | diagnostic accuracy | en |
dc.subject | microRNA | en |
dc.subject | gene expression profiling | en |
dc.subject | genetics | en |
dc.subject | reverse transcription polymerase chain reaction | en |
dc.subject | transcription factor | en |
dc.subject | very elderly | en |
dc.subject | Chromosome Aberrations | en |
dc.subject | phylogeny | en |
dc.subject | sensitivity and specificity | en |
dc.subject | Cohort Studies | en |
dc.subject | urothelium | en |
dc.subject | chromosome aberration | en |
dc.subject | gene function | en |
dc.subject | MicroRNAs | en |
dc.subject | RNA analysis | en |
dc.subject | cytology | en |
dc.subject | gene identification | en |
dc.subject | genetic algorithm | en |
dc.subject | Aged, 80 and over | en |
dc.subject | Carcinoma, Renal Cell | en |
dc.subject | diagnostic test accuracy study | en |
dc.subject | kidney tumor | en |
dc.subject | microRNA 142 5p | en |
dc.subject | microRNA 148b 5p | en |
dc.subject | microRNA 191 5p | en |
dc.subject | microRNA 1912 | en |
dc.subject | microRNA 193b 3p | en |
dc.subject | microRNA 24 2 5p | en |
dc.subject | microRNA 24 3p | en |
dc.subject | microRNA 26a 2 3p | en |
dc.subject | microRNA 3117 3p | en |
dc.subject | microRNA 3144 5p | en |
dc.subject | microRNA 3164 | en |
dc.subject | microRNA 3615 | en |
dc.subject | microRNA 3648 | en |
dc.subject | microRNA 3656 | en |
dc.subject | microRNA 3687 | en |
dc.subject | microRNA 375 | en |
dc.subject | microRNA 378a 5p | en |
dc.subject | microRNA 489 | en |
dc.subject | microRNA 514b 5p | en |
dc.subject | microRNA 520b | en |
dc.subject | microRNA 520c 3p | en |
dc.subject | microRNA 587 | en |
dc.subject | microRNA 617 | en |
dc.subject | microRNA 638 | en |
dc.subject | microRNA 769 5p | en |
dc.subject | microRNA 885 5p | en |
dc.subject | receiver operating characteristic | en |
dc.subject | transcription factor TFCP2L1 | en |
dc.subject | transitional cell carcinoma | en |
dc.title | New miRNA profiles accurately distinguish renal cell carcinomas and upper tract urothelial carcinomas from the normal kidney | en |
dc.type | info:eu-repo/semantics/article | |
dc.identifier.doi | 10.1371/journal.pone.0091646 | |
dc.description.volume | 9 | |
dc.author.faculty | Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences | |
dc.author.department | Τμήμα Βιολογικών Επιστημών / Department of Biological Sciences | |
dc.type.uhtype | Article | en |
dc.description.notes | <p>Cited By :16</p> | en |
dc.source.abbreviation | PLoS ONE | en |
dc.contributor.orcid | Constantinou-Deltas, Constantinos D. [0000-0001-5549-9169] | |
dc.gnosis.orcid | 0000-0001-5549-9169 | |