Reference miRNAs for miRNAome Analysis of Urothelial Carcinomas

Background/Objective: Reverse transcription quantitative real-time PCR (RT-qPCR) is widely used in microRNA (miRNA) expression studies on cancer. To compensate for the analytical variability produced by the multiple steps of the method, relative quantification of the measured miRNAs is required, which is based on normalization to endogenous reference genes. No study has been performed so far on reference miRNAs for normalization of miRNA expression in urothelial carcinoma. The aim of this study was to identify suitable reference miRNAs for miRNA expression studies by RT-qPCR in urothelial carcinoma. Methods: Candidate reference miRNAs were selected from 24 urothelial carcinoma and normal bladder tissue samples by miRNA microarrays. The usefulness of these candidate reference miRNAs together with the commonly for normalization purposes used small nuclear RNAs RNU6B, RNU48, and Z30 were thereafter validated by RT-qPCR in 58 tissue samples and analyzed by the algorithms geNorm, NormFinder, and BestKeeper. Principal Findings: Based on the miRNA microarray data, a total of 16 miRNAs were identified as putative reference genes. After validation by RT-qPCR, miR-101, miR-125a-5p, miR-148b, miR-151-5p, miR-181a, miR-181b, miR-29c, miR-324-3p, miR-424, miR-874, RNU6B, RNU48, and Z30 were used for geNorm, NormFinder, and BestKeeper analyses that gave different combinations of recommended reference genes for normalization. Conclusions: The present study provided the first systematic analysis for identifying suitable reference miRNAs for miRNA expression studies of urothelial carcinoma by RT-qPCR. Different combinations of reference genes resulted in reliable expression data for both strongly and less strongly altered miRNAs. Notably, RNU6B, which is the most frequently used reference gene for miRNA studies, gave inaccurate normalization. The combination of four (miR-101, miR-125a-5p, miR-148b, and miR-151-5p) or three (miR-148b, miR-181b, and miR-874,) reference miRNAs is recommended for normalization

Referenz-miRNAs für die miRNAome Analyse des Urothelkarzinoms

Reverse transcription quantitative real-time PCR (RT-qPCR) is widely used in microRNA (miRNA) expression studies on cancer. To compensate for the analytical variability produced by the multiple steps of the method, relative quantification of the measured miRNAs is required, which is based on normalization to endogenous reference genes. No study has been performed so far on reference miRNAs for normalization of miRNA expression in urothelial carcinoma. The aim of this study was to identify suitable reference miRNAs for miRNA expression studies by RT-qPCR in urothelial carcinoma. Methods: Candidate reference miRNAs were selected from 24 urothelial carcinoma and normal bladder tissue samples by miRNA microarrays. The usefulness of these candidate reference miRNAs together with the commonly for normalization purposes used small nuclear RNAs RNU6B, RNU48, and Z30 were thereafter validated by RT-qPCR in 58 tissue samples and analyzed by the algorithms geNorm, NormFinder, and BestKeeper. Principal Findings: Based on the miRNA microarray data, a total of 16 miRNAs were identified as putative reference genes. After validation by RT-qPCR, miR-101, miR-125a-5p, miR-148b, miR-151-5p, miR-181a, miR-181b, miR-29c, miR-324-3p, miR-424, miR-874, RNU6B, RNU48, and Z30 were used for geNorm, NormFinder, and BestKeeper analyses that gave different combinations of recommended reference genes for normalization. Conclusions: The present study provided the first systematic analysis for identifying suitable reference miRNAs for miRNA expression studies of urothelial carcinoma by RT-qPCR. Different combinations of reference genes resulted in reliable expression data for both strongly and less strongly altered miRNAs. Notably, RNU6B, which is the most frequently used reference gene for miRNA studies, gave inaccurate normalization. The combination of four (miR-101, miR-125a-5p, miR-148b, and miR-151-5p) or three (miR-148b, miR-181b, and miR-874,) reference miRNAs is recommended for normalization.Die quantitative reverse Transkriptions-Polymerase-Kettenreaktion (RT-qPCR) ist eine häufig verwendete Methode zur Untersuchung von microRNA(miRNA)-Expressionen bei Tumorerkrankungen. Die relative Quantifizierung der gemessenen miRNAs, basierend auf endogenen Referenzgenen, ist dabei unerlässlich, um die Variabilität, bedingt durch die einzelnen Teilschritte der Analyse, zu kompensieren. Eine Literaturrecherche ergab, dass bis zum jetzigen Zeitpunkt keine Studien zur Ermittlung von Referenz-miRNAs für das Harnblasenkarzinom vorliegen. Das Ziel dieser Studie war es, in systematischer Weise geeignete Referenz-miRNAs für RT-qPCR basierte miRNA- Expressionsstudien des Harnblasenkarzinoms zu identifizieren. Methodik: Unter Zuhilfenahme eines miRNA-Microarrays wurden aus insgesamt 24 Karzinom- und Normalgewebeproben der Harnblase Kandidaten von Referenz-miRNAs anhand ihrer Invarianz in der Expressionsstabilität zwischen den Proben ermittelt. Die Validierung dieser potenziellen Referenz-miRNAs erfolgte zusammen mit den häufig in der Literatur verwendeten small RNAs, RNU6B, RNU48 und Z30, an 58 Gewebeproben mittels RTqPCR. Die anschließende bioinformatorische Analyse wurde mit den Computerprogrammen geNorm, NormFinder und BestKeeper durchgeführt. Grundlegende Ergebnisse: Insgesamt wurden 16 potenzielle Referenz-miRNAs auf der Grundlage der miRNAMicroarraydaten identifiziert. Nach der Validierung mittels RT-qPCR zeigten miR-101, miR-125a-5p, miR-148b, miR-151-5p, miR-181a, miR-181b, miR-29c, miR-324-3p, miR- 424, miR-874, RNU6B, RNU48 und Z30 keine Unterschiede zwischen den Gewebeproben, sodass ihre Eignung als Referenzgene mit den drei Programmen ermittelt werden konnte. Daraus resultierten unterschiedliche Referenzgenkombinationen. Schlussfolgerungen: Die vorliegende Studie lieferte die erste systematische Analyse zur Identifizierung geeigneter Referenz-miRNAs für miRNA- Expressionsstudien des Harnblasenkarzinoms mittels RT-qPCR. Verschiedene Referenzgenkombinationen ergaben sowohl für starkals auch für schwach- regulierte miRNAs vergleichbare Expressionsergebnisse. Besonders eindrucksvoll konnte die fehlerhafte Normalisierung mit der RNU6B belegt werden, die bisher am häufigsten in miRNA-Studien als Referenzgen zum Einsatz kam. Die Kombination aus vier (miR-101, miR-125a-5p, miR-148b und miR-151-5p) bzw. aus drei (miR-148b, miR-181b und miR-874) Referenz-miRNAs wird für die Normalisierung von Expressionsstudien beim Harnblasenkarzinom empfohlen

Functional Epigenetic Analysis of Prostate Carcinoma: A Role for Seryl-tRNA Synthetase?

Transcriptional silencing, as a result of aberrant promoter hypermethylation, is a common mechanism through which genes in cancer cells become inactive. Functional epigenetic screens using demethylating agents to reexpress transcriptional silenced genes may identify such inactivated genes for needing further evaluation. We aimed to identify genes so far not known to be inactivated by promoter hypermethylation in prostate cancer. DU-145 and LNCaP cells were treated with the DNMT inhibitor zebularine. Expression changes of total RNA from treated and untreated cells were compared using an RNA expression microarray. Genes upregulated more than 2-fold were evaluated by RT-qPCR in 50 cases of paired normal and tumor tissues of prostate cancer patients. SARS was found to be downregulated in prostate cancer in 42/50 cases (84%). In addition, GADD45A and SPRY4 showed a remarkable diminished expression (88% and 74%, resp.). The gold standard for promoter hypermethylation-inactivated genes in prostate cancer (GSTP1) was repressed in 90% of our patient samples. ROC analyses reported statistically significant AUC curves in SARS, GADD45A, and GSTP1 and positive Spearman correlations were found between these genes. SARS was discovered to be a novel gene that is repressed in prostate cancer and could therefore be recommended for its involvement in prostate carcinogenesis

Diagnostic and Prognostic Potential of MicroRNA Maturation Regulators Drosha, AGO1 and AGO2 in Urothelial Carcinomas of the Bladder

Bladder cancer still requires improvements in diagnosis and prognosis, because many of the cases will recur and/or metastasize with bad outcomes. Despite ongoing research on bladder biomarkers, the clinicopathological impact and diagnostic function of miRNA maturation regulators Drosha and Argonaute proteins AGO1 and AGO2 in urothelial bladder carcinoma remain unclear. Therefore, we conducted immunohistochemical investigations of a tissue microarray composed of 112 urothelial bladder carcinomas from therapy-naïve patients who underwent radical cystectomy or transurethral resection and compared the staining signal with adjacent normal bladder tissue. The correlations of protein expression of Drosha, AGO1 and AGO2 with sex, age, tumor stage, histological grading and overall survival were evaluated in order to identify their diagnostic and prognostic potential in urothelial cancer. Our results show an upregulation of AGO1, AGO2 and Drosha in non-muscle-invasive bladder carcinomas, while there was increased protein expression of only AGO2 in muscle-invasive bladder carcinomas. Moreover, we were able to differentiate between non-muscle-invasive and muscle-invasive bladder carcinoma according to AGO1 and Drosha expression. Finally, despite Drosha being a discriminating factor that can predict the probability of overall survival in the Kaplan–Meier analysis, AGO1 turned out to be independent of all clinicopathological parameters according to Cox regression. In conclusion, we assumed that the miRNA processing factors have clinical relevance as potential diagnostic and prognostic tools for bladder cancer

Ranking of candidate reference miRNAs and small RNAs in human nonmalignant and malignant bladder tissues according to their stability value using geNorm, NormFinder, and BestKeeper algorithms.

&<p>High expression stability is indicated by low stability value.</p>#<p>SD [±x-fold]: standard deviation of the absolute regulation coefficients. SD >1 can be considered inconsistent.</p

geNorm analysis of RT-qPCR-based candidate reference genes.

<p>(A) The geNorm analysis shows the calculation of the average expression stability value M of all candidate reference genes determined by RT-qPCR. Genes with the highest M value have the least stable expression, while the genes with the lowest M value have the most stable expression. The x-axis presents the ranking of reference genes in order of increasing stability from left to the right. (B) Calculation of the optimal number of reference genes for normalization. geNorm calculates a normalization factor assessing the optimal number of reference genes for generating that factor. The normalization factor is calculated from at least two genes taking into account the variable V as the average pairwise variation (V_NF) between two sequential normalization factors. The thin broken line illustrates the cut-off value V_NF <0.15. In this experiment, the optimal number of reference genes was four (V4/5). geNorm shows the variation of the normalization factor of four genes as the best combination (miR-101, miR-148b; miR-125a-5p, and miR-151-5p) in relation to five genes as shown in (A) and in the following order. All the results are presented according to the output files of the geNorm program.</p

Expression of candidate reference genes in human nonmalignant and malignant bladder tissue samples.

<p>RT-qPCR analyses were performed from 17 nonmalignant bladder tissue samples and 41 samples from low-grade and high-grade papillary urothelial carcinoma. Expression levels of the candidate reference genes are given as arbitrary units. Boxes (blank, nonmalignant samples; black, malignant samples) represent lower and upper quartiles with median as horizontal line; whiskers depict the 10 and 90 percentiles. Significances are illustrated as <i>P</i> values of the Mann-Whitney <i>U</i> test.</p

Candidate reference miRNAs selected from microarray analysis.^†

†<p>The TaqMan MicroRNA Assay ID, miRBase accession number, and the sequence for each miRNA are compiled in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0039309#pone.0039309.s002" target="_blank">Table S2</a>.</p>&<p>miRNAs marked in Italics were not included in further analyses because their low expression level was beyond the dynamic range of the assay (>35Cq) (further details see text).</p>#<p>The miRNA ID from the miRBase version 10.1 and 18, respectively.</p>§<p>Symbols “N” and “R” indicate the selection of the candidate reference miRNAs based on normalized or raw microarray data as described in the text.</p

Effects of different normalization approaches on the expression of miR-200a and miR-20a.

<p>The relative expression of (A) miR-200a and (B) miR-20a as highly and moderately differentially expressed miRNAs, respectively was calculated using the following normalization strategies recommended by geNorm (a–c), NormFinder (d–f), BestKeeper (g), and RNU6B (h). The geNorm approaches were: (a) the four-reference-miRNA combination recommended as necessary number of reference miRNAs (miR-101, miR-125a-5p, miR-148b, miR-151-5p); (b) the three best ranked miRNAs according to their M values (miR-125a-5p, miR-148b, and miR-151-5p) and (c) the best two-gene-reference combination (miR-125a-5p, miR-151-5p). NormFinder normalization approaches were: (d) the best two reference gene combination (miR-125a-5p, Z30); (e) the three best ranked reference genes (miR-148b, miR-181b, miR-874); (f) the best single miRNA, miR-148b. BestKeeper normalization approach was (g) RNU48; (j) RNU6B as the most frequently recommended normalizer in bladder cancer studies. Values are given as arbitrary units; boxes (blank, nonmalignant tissue; black, malignant tissue) represent lower and upper quartiles with medians as horizontal line; whiskers depict the 10–90 percentiles. Significances are illustrated as <i>P</i> values of the Mann-Whitney <i>U</i> test.</p