Unknown,Transcriptomics,Genomics,Proteomics

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Bladder cancer: analysis of miRNA-mRNA interactions

ABSTRACT: Background: MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression. Their abilyty to affect multiple gene pathways by targeting to various mRNAs makes them to an interesting class of regulators. The interplay between miRNA and mRNA has been proposed as an important process in cancer development and progression. In this study, we analyzed miRNA -mRNA interactions in bladder urothelial carcinoma. Methodology/Principal Findings: We have developed a new algorithm which is capable of identifying altered miRNA-mRNA regulation between tissues samples without preexisting stratification of groups. Microarray expression profiling of both miRNA and mRNA from the same sample were performed using a collective of 24 urothelial carcinoma and normal bladder tissue samples. Using our approach, normal and tumor tissue samples as well as different stages of tumor progression were successfully stratified. Also, we were able to analyzed individual miRNA-mRNA interactions from each patient, focusing on different miRNA families. Conclusions: Just recently, the need for tools that allow an integrative analysis of microRNA and mRNA expression data has been addressed. With this study, we provide an algorithm that considers the special nature of miRNA induced regulation and shows good specificities and sensitivities when applied to bladder cancer expression data. mRNA and microRNA expression data were analyzed together to identify bladder cancer specific micoRNA-mRNA interaction

ORGANISM(S): Homo sapiens

SUBMITTER: Hellmuth-A Meyer

PROVIDER: E-GEOD-40355 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Background/Objective: Quantitative real-time PCR (RT-qPCR) is widely used in 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. A literature search in PubMed revealed that 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 genes for miRNA expression studies by RT-qPCR in urothelial carcinoma. Methods: Candidate reference miRNAs were selected from 24 papillary 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-151-3p, 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-125a-5p, miR-148b, miR-151-3p, and miR-151-5p) or three (miR-148b, miR-874, miR-181b) miRNA reference genes is recommended for normalization. Candidate reference miRNAs (for RT-qPCR analysis) were selected from 24 papillary urothelial carcinoma and normal bladder tissue samples by miRNA microarrays.

Project description:Ph-negative myeloproliferative neoplasms (MPNs) are characterized by many somatic mutations which have already been shown useful in the prognostic assessment of MPN patients. Moreover, aberrant microRNA (miRNA) expression seems to add to the molecular complexity of MPNs, as specific miRNA signatures capable of discriminating MPN cells from those of normal donors were previously reported. In order to have a comprehensive picture of miRNA deregulation and its relationship with differential gene expression in primary myelofibrosis (PMF) cells, we obtained gene- (GEP) and miRNA expression profiles (miEP) of CD34+ cells from 31 healthy donors and 42 PMF patients using Affymetrix technology (HG-U219 and miRNA 2.0 arrays). Differentially expressed genes (DEG) and miRNAs (DEM) were sorted out by means of Partek Genomic Suite vs 6.6. Since each miRNA can target many mRNAs while a single mRNA can be targeted by multiple miRNAs, we performed Integrative Analysis (IA) by means of Ingenuity Pathway Analysis (IPA) to untangle this combinatorial complexity. In particular, IPA points out DEM-DEG pairs among experimentally validated interactions from TarBase, miRecords and Ingenuity Expert Findings as well as predicted microRNA-mRNA interactions from TargetScan. IPA microRNA Target Filter was then employed to select only the DEM-DEG pairs showing an anti-correlated expression pattern and to build regulatory networks. Finally, 3'UTR luciferase reporter assays were performed to validate IPA predicted miRNA-mRNA interactions. This study allowed the identification of different networks possibly involved in PMF onset and progression, highlighting an aberrant cross-regulation in miRNA-targets involved in malignant hematopoiesis. Furthermore, Integrative analysis was proved a powerful tool to unravel miRNA-mRNA interactions in functional networks, shedding light on the potential contribution of miRNAs to PMF pathogenesis. Gene expression profile (GEP) and miRNA expression profile (miEP) were performed starting from the same totalRNA of CD34+ cells from 42 PMF patients and 31 healthy donors (n=16 PB CD34+, n=15 BM CD34+) (1 replicate for each sample). In particular, GEP and miEP were performed on 23 PMF patients carrying the mutation JAK2V617F and 19 wild-type samples.

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Bladder cancer: analysis of miRNA-mRNA interactions

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