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| Status |
Public on Feb 01, 2021 |
| Title |
Identification of RCC subtype-specific microRNAs – meta-analysis of high-throughput RCC tumor microRNA expression data [miRNA-Seq] |
| Organism |
Homo sapiens |
| Experiment type |
Non-coding RNA profiling by high throughput sequencing
|
| Summary |
Renal cell carcinoma (RCC) is one of the most common cancers worldwide with nearly non-symptomatic course till advanced stage of 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 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 available NGS and seven microarray RCC studies in order to identify subtype-specific expression of miRNAs. We concentrated on four potentially oncocytoma-specific miRNAs (miRNA-424-5p, miRNA-146b-5p, miRNA-183-5p, miRNA-218-5p), two pRCC (miRNA-127-3p, miRNA-139-5p) and eight 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 Fuhrman grades and identified alterations in their isoform composition in tumor tissue. Our results revealed that changes in expression of selected miRNA might be potentially utilized as a tool aiding ccRCC subclass discrimination and propose a miRNA panel aiding RCC subtype distinction.
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| Overall design |
26 ccRCC tumor samples and 6 normal adjacent kidney tissue samples
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| |
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| Contributor(s) |
Kajdasz AP, Majer W, Kluzek K, Sobkowiak J, Milecki T, Derebecka N, Kwias Z, Bluyssen HA, Wesoly J |
| Citation(s) |
33535553 |
| Submission date |
May 29, 2020 |
| Last update date |
Feb 04, 2021 |
| Contact name |
Arkadiusz Kajdasz |
| E-mail(s) |
akajdasz@ibch.poznan.pl
|
| Organization name |
Institute of Bioorganic Chemistry PAS
|
| Lab |
Laboratory of Bioinformatics
|
| Street address |
ul. Z. Noskowskiego 12/14
|
| City |
Poznań |
| State/province |
wielkopolskie |
| ZIP/Postal code |
61-704 |
| Country |
Poland |
| |
|
| Platforms (1) |
| GPL15456 |
Illumina HiScanSQ (Homo sapiens) |
|
| Samples (32)
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| This SubSeries is part of SuperSeries: |
| GSE151428 |
Identification of RCC subtype-specific microRNAs – meta-analysis of high-throughput RCC tumor microRNA expression data |
|
| Relations |
| BioProject |
PRJNA635803 |
| SRA |
SRP265244 |
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