title: The use of miRNA microarrays for the analysis of cancer samples with global miRNA decrease.
abstract: 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.
authors.affiliation: Centre for Cancer Research, Monash Institute of Medical Research, Monash University, Clayton, Victoria 3168, Australia.
authors.forename: Di
authors.initials: D
authors.lastname: Wu
authors.forename: Yifang
authors.initials: Y
authors.lastname: Hu
authors.forename: Stephen
authors.initials: S
authors.lastname: Tong
authors.forename: Bryan R G
authors.initials: BR
authors.lastname: Williams
authors.forename: Gordon K
authors.initials: GK
authors.lastname: Smyth
authors.forename: Michael P
authors.initials: MP
authors.lastname: Gantier
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods; D053487:DEAD-box RNA Helicases / Q000235:genetics* / Q000378:metabolism; D015536:Down-Regulation; D005347:Fibroblasts / Q000378:metabolism; D017353:Gene Deletion; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008297:Male; D051379:Mice; D035683:MicroRNAs / Q000235:genetics / Q000378:metabolism*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D011471:Prostatic Neoplasms / Q000175:diagnosis*; D015347:RNA Probes / Q000235:genetics / Q000378:metabolism; D012334:RNA, Neoplasm / Q000235:genetics / Q000378:metabolism*; D043244:Ribonuclease III / Q000235:genetics* / Q000378:metabolism; D012680:Sensitivity and Specificity; D015854:Up-Regulation
chemical_list: D035683:MicroRNAs; D015347:RNA Probes; D012334:RNA, Neoplasm; C509781:Dicer1 protein, mouse; D043244:Ribonuclease III; D053487:DEAD-box RNA Helicases
keywords: Dicer1; miRNA microarray; microRNA; normalization