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The use of miRNA microarrays for the analysis of cancer samples with global miRNA decrease

Recent studies have established that mutations or deletions in microRNA (miRNA) processing enzymes resulting in a global decrease of miRNA expression are frequent across cancers and can be associated with a poorer prognosis. While very popular in miRNA profiling studies, it remains unclear whether m...

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Autores principales: Wu, Di, Hu, Yifang, Tong, Stephen, Williams, Bryan R.G., Smyth, Gordon K., Gantier, Michael P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3683922/
https://www.ncbi.nlm.nih.gov/pubmed/23709276
http://dx.doi.org/10.1261/rna.035055.112
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author Wu, Di
Hu, Yifang
Tong, Stephen
Williams, Bryan R.G.
Smyth, Gordon K.
Gantier, Michael P.
author_facet Wu, Di
Hu, Yifang
Tong, Stephen
Williams, Bryan R.G.
Smyth, Gordon K.
Gantier, Michael P.
author_sort Wu, Di
collection PubMed
description Recent studies have established that mutations or deletions in microRNA (miRNA) processing enzymes resulting in a global decrease of miRNA expression are frequent across cancers and can be associated with a poorer prognosis. While very popular in miRNA profiling studies, it remains unclear whether miRNA microarrays are suited or not to accurately detecting global miRNA decreases seen in cancers. In this work, we analyzed the miRNA profiles of samples with global miRNA decreases using Affymetrix miRNA microarrays following the inducible genetic deletion of Dicer1. Surprisingly, up to a third of deregulated miRNAs identified upon Dicer1 depletion were found to be up-regulated following standard robust multichip average (RMA) background correction and quantile normalization, indicative of normalization bias. Our comparisons of five preprocess steps performed at the probe level demonstrated that the use of cyclic loess relying on non-miRNA small RNAs present on the Affymetrix platform significantly improved specificity and sensitivity of detection of decreased miRNAs. These findings were validated in samples from patients with prostate cancer, where conjugation of robust normal-exponential background correction with cyclic loess normalization and array weights correctly identified the greatest number of decreased miRNAs, and the lowest amount of false-positive up-regulated miRNAs. These findings highlight the importance of miRNA microarray normalization for the detection of miRNAs that are truly differentially expressed and suggest that the use of cyclic loess based on non-miRNA small RNAs can help to improve the sensitivity and specificity of miRNA profiling in cancer samples with global miRNA decrease.
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spelling pubmed-36839222014-07-01 The use of miRNA microarrays for the analysis of cancer samples with global miRNA decrease Wu, Di Hu, Yifang Tong, Stephen Williams, Bryan R.G. Smyth, Gordon K. Gantier, Michael P. RNA Bioinformatics Recent studies have established that mutations or deletions in microRNA (miRNA) processing enzymes resulting in a global decrease of miRNA expression are frequent across cancers and can be associated with a poorer prognosis. While very popular in miRNA profiling studies, it remains unclear whether miRNA microarrays are suited or not to accurately detecting global miRNA decreases seen in cancers. In this work, we analyzed the miRNA profiles of samples with global miRNA decreases using Affymetrix miRNA microarrays following the inducible genetic deletion of Dicer1. Surprisingly, up to a third of deregulated miRNAs identified upon Dicer1 depletion were found to be up-regulated following standard robust multichip average (RMA) background correction and quantile normalization, indicative of normalization bias. Our comparisons of five preprocess steps performed at the probe level demonstrated that the use of cyclic loess relying on non-miRNA small RNAs present on the Affymetrix platform significantly improved specificity and sensitivity of detection of decreased miRNAs. These findings were validated in samples from patients with prostate cancer, where conjugation of robust normal-exponential background correction with cyclic loess normalization and array weights correctly identified the greatest number of decreased miRNAs, and the lowest amount of false-positive up-regulated miRNAs. These findings highlight the importance of miRNA microarray normalization for the detection of miRNAs that are truly differentially expressed and suggest that the use of cyclic loess based on non-miRNA small RNAs can help to improve the sensitivity and specificity of miRNA profiling in cancer samples with global miRNA decrease. Cold Spring Harbor Laboratory Press 2013-07 /pmc/articles/PMC3683922/ /pubmed/23709276 http://dx.doi.org/10.1261/rna.035055.112 Text en © 2013; Published by Cold Spring Harbor Laboratory Press for the RNA Society http://creativecommons.org/licenses/by-nc/3.0/ This article is distributed exclusively by the RNA Society for the first 12 months after the full-issue publication date (see http://rnajournal.cshlp.org/site/misc/terms.xhtml). After 12 months, it is available under a Creative Commons License (Attribution-NonCommercial 3.0 Unported), as described at http://creativecommons.org/licenses/by-nc/3.0/.
spellingShingle Bioinformatics
Wu, Di
Hu, Yifang
Tong, Stephen
Williams, Bryan R.G.
Smyth, Gordon K.
Gantier, Michael P.
The use of miRNA microarrays for the analysis of cancer samples with global miRNA decrease
title The use of miRNA microarrays for the analysis of cancer samples with global miRNA decrease
title_full The use of miRNA microarrays for the analysis of cancer samples with global miRNA decrease
title_fullStr The use of miRNA microarrays for the analysis of cancer samples with global miRNA decrease
title_full_unstemmed The use of miRNA microarrays for the analysis of cancer samples with global miRNA decrease
title_short The use of miRNA microarrays for the analysis of cancer samples with global miRNA decrease
title_sort use of mirna microarrays for the analysis of cancer samples with global mirna decrease
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3683922/
https://www.ncbi.nlm.nih.gov/pubmed/23709276
http://dx.doi.org/10.1261/rna.035055.112
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