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Article

Identification of RCC Subtype-Specific microRNAs–Meta-Analysis of High-Throughput RCC Tumor microRNA Expression Data

1
Laboratory of Human Molecular Genetics, Faculty of Biology, Institute of Molecular Biology and Biotechnology, Adam Mickiewicz University Poznan, Uniwersytetu Poznanskiego 6, 61-614 Poznan, Poland
2
Laboratory of High Throughput Technologies, Faculty of Biology, Adam Mickiewicz University Poznan, Uniwersytetu Poznanskiego 6, 61-614 Poznan, Poland
3
Department of Urology, Poznan University of Medical Sciences, Szwajcarska 3, 61-285 Poznan, Poland
*
Authors to whom correspondence should be addressed.
Both authors contributed equally to this work.
Academic Editor: Paola Tucci
Cancers 2021, 13(3), 548; https://doi.org/10.3390/cancers13030548
Received: 14 December 2020 / Revised: 19 January 2021 / Accepted: 20 January 2021 / Published: 1 February 2021
(This article belongs to the Special Issue MicroRNA and Cancer)
In the majority of renal cancer cases, the disease course is non-symptomatic which frequently leads to late diagnosis of disease. Currently, there are no molecular tools dedicated to the detection and monitoring of renal cancer. Our study aimed to investigate changes in microRNA (miRNA) expression in tissue samples of renal cancer patients. We performed meta-analysis using results of 14 high-throughput studies (both, NGS and microarrays) and as a result, selected a group of miRNAs deregulated in renal cancer and its subtypes. Later, the expression changes of selected miRNA were validated in an independent sample set. We confirmed that the investigation of miRNA expression might be potentially applicable in the detection and monitoring of renal cancer and its subtypes.
Renal cell carcinoma (RCC) is one of the most common cancers worldwide with a nearly non-symptomatic course until the advanced stages of the disease. RCC can be distinguished into three subtypes: papillary (pRCC), chromophobe (chRCC) and clear cell renal cell carcinoma (ccRCC) representing up to 75% of all RCC cases. Detection and RCC monitoring tools are limited to standard imaging techniques, in combination with non-RCC specific morphological and biochemical read-outs. RCC subtype identification relays mainly on results of pathological examination of tumor slides. Molecular, clinically applicable and ideally non-invasive tools aiding RCC management are still non-existent, although molecular characterization of RCC is relatively advanced. Hence, many research efforts concentrate on the identification of molecular markers that will assist with RCC sub-classification and monitoring. Due to stability and tissue-specificity miRNAs are promising candidates for such biomarkers. Here, we performed a meta-analysis study, utilized seven NGS and seven microarray RCC studies in order to identify subtype-specific expression of miRNAs. We concentrated on potentially oncocytoma-specific miRNAs (miRNA-424-5p, miRNA-146b-5p, miRNA-183-5p, miRNA-218-5p), pRCC-specific (miRNA-127-3p, miRNA-139-5p) and ccRCC-specific miRNAs (miRNA-200c-3p, miRNA-362-5p, miRNA-363-3p and miRNA-204-5p, 21-5p, miRNA-224-5p, miRNA-155-5p, miRNA-210-3p) and validated their expression in an independent sample set. Additionally, we found ccRCC-specific miRNAs to be differentially expressed in ccRCC tumor according to Fuhrman grades and identified alterations in their isoform composition in tumor tissue. Our results revealed that changes in the expression of selected miRNA might be potentially utilized as a tool aiding ccRCC subclass discrimination and we propose a miRNA panel aiding RCC subtype distinction. View Full-Text
Keywords: microRNA; renal cancer; RCC; ccRCC; meta-analysis microRNA; renal cancer; RCC; ccRCC; meta-analysis
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MDPI and ACS Style

Kajdasz, A.; Majer, W.; Kluzek, K.; Sobkowiak, J.; Milecki, T.; Derebecka, N.; Kwias, Z.; Bluyssen, H.A.R.; Wesoly, J. Identification of RCC Subtype-Specific microRNAs–Meta-Analysis of High-Throughput RCC Tumor microRNA Expression Data. Cancers 2021, 13, 548. https://doi.org/10.3390/cancers13030548

AMA Style

Kajdasz A, Majer W, Kluzek K, Sobkowiak J, Milecki T, Derebecka N, Kwias Z, Bluyssen HAR, Wesoly J. Identification of RCC Subtype-Specific microRNAs–Meta-Analysis of High-Throughput RCC Tumor microRNA Expression Data. Cancers. 2021; 13(3):548. https://doi.org/10.3390/cancers13030548

Chicago/Turabian Style

Kajdasz, Arkadiusz, Weronika Majer, Katarzyna Kluzek, Jacek Sobkowiak, Tomasz Milecki, Natalia Derebecka, Zbigniew Kwias, Hans A.R. Bluyssen, and Joanna Wesoly. 2021. "Identification of RCC Subtype-Specific microRNAs–Meta-Analysis of High-Throughput RCC Tumor microRNA Expression Data" Cancers 13, no. 3: 548. https://doi.org/10.3390/cancers13030548

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