The use of miRNA microarrays for the analysis of cancer samples with global miRNA decrease
Open accessAbstract
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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This weighting ability has been exploited for normalizing assays when the proportion of differentially expressed genes may be high, for example boutique arrays, miRNA arrays, PCR arrays, protein arrays or protein mass spectrometry.
“The latter ability has been exploited for normalizing assays when the proportion of differentially expressed genes may be high, for example boutique arrays (39), miRNA arrays (40), PCR arrays, protein arrays or protein mass spectrometry.”
From limma powers differential expression analyses for RNA-sequencing and microarray studies (2015) · cites this paper as [40]
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1 retracted
A TARBP2 mutation in human cancer impairs microRNA processing and DICER1 function
Melo, S. A., Ropero, S., Moutinho, C., Aaltonen, L. A., Yamamoto, H., Calin, G. A., Rossi, S., Fernández, A. F., Carneiro, F., Oliveíra, C., et al. (2009) · Nature Genetics · doi:10.1038/ng.317 · Cited by 375 · see citing works
RetractedR: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,706 · see citing works
Bioconductor: open software development for computational biology and bioinformatics
Gentleman, R., Carey, V., Bates, D., Bolstad, B., Dettling, M., Dudoit, S., Ellis, B., Gautier, L., Ge, Y., Gentry, J., et al. (2004) · Genome Biology · doi:10.1186/gb-2004-5-10-r80 · Cited by 13,133 · see citing works
Self-citationSmyth, G. K. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1027 · Cited by 11,829 · see citing works
Self-citationExploration, normalization, and summaries of high density oligonucleotide array probe level data
Irizarry, R. A. (2003) · Biostatistics · doi:10.1093/biostatistics/4.2.249 · Cited by 10,603 · see citing works
MicroRNA expression profiles classify human cancers
Lü, J., Getz, G. A., Miska, E. A., Alvarez-Saavedra, E., Lamb, J., Peck, D., Sweet-Cordero, A., Ebert, B. L., Mak, R. H., Ferrando, A. A., et al. (2005) · Nature · doi:10.1038/nature03702 · Cited by 9,497 · see citing works
Bolstad, B. M., Irizarry, R. A., Åstrand, M., & Speed, T. P. (2003) · Bioinformatics · doi:10.1093/bioinformatics/19.2.185 · Cited by 8,185 · see citing works
limma: Linear Models for Microarray Data
Smyth, G. K. (2005) · Statistics for Biology and Health · doi:10.1007/0-387-29362-0_23 · Cited by 5,796 · see citing works
Self-citationA microRNA expression signature of human solid tumors defines cancer gene targets
Volinia, S., Calin, G. A., Liu, C.-G., Ambs, S., Cimmino, A., Petrocca, F., Visone, R., Iorio, M., Roldo, C., Ferracin, M., et al. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0510565103 · Cited by 5,697 · see citing works
affy—analysis of Affymetrix GeneChip data at the probe level
Gautier, L., Cope, L., Bolstad, B. M., & Irizarry, R. A. (2004) · Bioinformatics · doi:10.1093/bioinformatics/btg405 · Cited by 5,221 · see citing works
The widespread regulation of microRNA biogenesis, function and decay
Krol, J., Loedige, I., & Filipowicz, W. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2843 · Cited by 4,672 · see citing works
Yang, Y., Dudoit, S., Luu, P., Lin, D., Peng, V., Ngai, J., & Speed, T. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.4.e15 · Cited by 3,722 · see citing works
Unique microRNA molecular profiles in lung cancer diagnosis and prognosis
Yanaihara, N., Caplen, N., Bowman, E., Seike, M., Kumamoto, K., Yi, M., Stephens, R. M., Okamoto, A., Yokota, J., Tanaka, T., et al. (2006) · Cancer Cell · doi:10.1016/j.ccr.2006.01.025 · Cited by 3,023 · see citing works
Normalization of cDNA microarray data
Smyth, G. K., & Speed, T. (2003) · Methods · doi:10.1016/s1046-2023(03)00155-5 · Cited by 1,871 · see citing works
Self-citationA dicer-independent miRNA biogenesis pathway that requires Ago catalysis
Cheloufi, S., Dos Santos, C. O., Chong, M. M. W., & Hannon, G. J. (2010) · Nature · doi:10.1038/nature09092 · Cited by 1,026 · see citing works
A comparison of background correction methods for two-colour microarrays
Ritchie, M. E., Silver, J., Oshlack, A., Holmes, M., Diyagama, D., Holloway, A., & Smyth, G. K. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm412 · Cited by 907 · see citing works
Self-citationAn oligonucleotide microchip for genome-wide microRNA profiling in human and mouse tissues
Liu, C.-G., Calin, G. A., Meloon, B., Gamliel, N., Sevignani, C., Ferracin, M., Dumitru, C. D., Shimizu, M., Zupo, S., Dono, M., et al. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0403293101 · Cited by 778 · see citing works
Dicer, Drosha, and Outcomes in Patients with Ovarian Cancer
Merritt, W. M., Lin, Y. G., Han, L. Y., Kamat, A. A., Spannuth, W. A., Schmandt, R. E., Urbauer, D. L., Pennacchio, L. A., Cheng, J., Nick, A. M., et al. (2008) · New England Journal of Medicine · doi:10.1056/nejmoa0803785 · Cited by 710 · see citing works
Bachellerie, J., Cavaillé, J., & Hüttenhofer, A. (2002) · Biochimie · doi:10.1016/s0300-9084(02)01402-5 · Cited by 669 · see citing works
miR-15a and miR-16-1 in cancer: discovery, function and future perspectives
Aqeilan, R. I., Calin, G. A., & Croce, C. M. (2009) · Cell Death and Differentiation · doi:10.1038/cdd.2009.69 · Cited by 650 · see citing works
Widespread deregulation of microRNA expression in human prostate cancer
Özen, M., Creighton, C. J., Ozdemir, M., & Ittmann, M. (2007) · Oncogene · doi:10.1038/sj.onc.1210809 · Cited by 634 · see citing works
Reduced expression of Dicer associated with poor prognosis in lung cancer patients
Karube, Y., Tanaka, H., Osada, H., Tomida, S., Tatematsu, Y., Yanagisawa, K., Yatabe, Y., Takamizawa, J., Miyoshi, S., Mitsudomi, T., et al. (2005) · Cancer Science · doi:10.1111/j.1349-7006.2005.00015.x · Cited by 601 · see citing works
Gaur, A., Jewell, D. A., Liang, Y., Ridzon, D., Moore, J. H., Chen, C., Ambros, V. R., & Israel, M. A. (2007) · Cancer Research · doi:10.1158/0008-5472.can-06-2698 · Cited by 593 · see citing works
Genetic dissection of the miR-17∼92 cluster of microRNAs in Myc-induced B-cell lymphomasPreprint
Mu, P., Han, Y.-C., Betel, D., Yao, E. S., Squatrito, M., Ogrodowski, P., de Stanchina, E., D’Andrea, A., Sander, C., & Ventura, A. (2009) · Genes & Development · doi:10.1101/gad.1872909 · Cited by 449 · see citing works
Dicer1 functions as a haploinsufficient tumor suppressorPreprint
Kumar, M. S., Pester, R. E., Chen, C. Y., Lane, K. M., Chin, C., Lü, J., Kirsch, D. G., Golub, T. R., & Jacks, T. (2009) · Genes & Development · doi:10.1101/gad.1848209 · Cited by 437 · see citing works
Analysis of microRNA turnover in mammalian cells following Dicer1 ablation
Gantier, M. P., McCoy, C. E., Rusinova, I., Saulep-Easton, D., Wang, D., Xu, D., Irving, A. T., Behlke, M. A., Hertzog, P. J., Mackay, F., et al. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr148 · Cited by 397 · see citing works
Self-citationA Genetic Defect in Exportin-5 Traps Precursor MicroRNAs in the Nucleus of Cancer Cells
Melo, S. A., Moutinho, C., Ropero, S., Calin, G. A., Rossi, S., Spizzo, R., Fernández, A. F., Dávalos, V., Villanueva, A., Montoya, G., et al. (2010) · Cancer Cell · doi:10.1016/j.ccr.2010.09.007 · Cited by 347 · see citing works
Dysregulation of microRNAs in cancer: Playing with fire
Melo, S. A., & Esteller, M. (2010) · FEBS Letters · doi:10.1016/j.febslet.2010.08.009 · Cited by 317 · see citing works
Empirical array quality weights in the analysis of microarray data
Ritchie, M. E., Diyagama, D., Neilson, J., van Laar, R., Dobrovic, A., Holloway, A., & Smyth, G. K. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-261 · Cited by 312 · see citing works
Self-citationmiRBase: microRNA Sequences and Annotation
Griffiths‐Jones, S. (2010) · Current Protocols in Bioinformatics · doi:10.1002/0471250953.bi1209s29 · Cited by 259 · see citing works
The MicroRNA Profile of Prostate Carcinoma Obtained by Deep Sequencing
Szczyrba, J., Löprich, E., Wach, S., Jung, V., Unteregger, G., Barth, S., Grobholz, R., Wieland, W. F., Stöhr, R., Hartmann, A., et al. (2010) · Molecular Cancer Research · doi:10.1158/1541-7786.mcr-09-0443 · Cited by 227 · see citing works
Faster cyclic loess: normalizing RNA arrays via linear models
Ballman, K. V., Grill, D. E., Oberg, A. L., et al. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bth327 · Cited by 226 · see citing works
Optimizing the noise versus bias trade-off for Illumina Whole Genome Expression Beadchips
Shi, W., Oshlack, A., & Smyth, G. K. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq871 · Cited by 225 · see citing works
Self-citationMeyer, S. U., Pfaffl, M. W., & Ulbrich, S. E. (2010) · Biotechnology Letters · doi:10.1007/s10529-010-0380-z · Cited by 212 · see citing works
Silver, J. D., Ritchie, M. E., & Smyth, G. K. (2008) · Biostatistics · doi:10.1093/biostatistics/kxn042 · Cited by 208 · see citing works
Self-citationGrelier, G., Voirin, N., Ay, A.-S., Cox, D. G., Chabaud, S., Treilleux, I., Goddard‐Léon, S., Rimokh, R., Mikaélian, I., Venoux, C., et al. (2009) · British Journal of Cancer · doi:10.1038/sj.bjc.6605193 · Cited by 196 · see citing works
A miR-19 regulon that controls NF-κB signaling
Gantier, M. P., Stunden, H. J., McCoy, C. E., Behlke, M. A., Wang, D., Kaparakis‐Liaskos, M., Sarvestani, S. T., Yang, Y. H., Xu, D., Corr, S. C., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks521 · Cited by 176 · see citing works
Self-citationImpact of normalization on miRNA microarray expression profiling
Pradervand, S., Weber, J., Thomas, J., Bueno, M., Wirapati, P., Lefort, K., Dotto, G. P., & Harshman, K. (2009) · RNA · doi:10.1261/rna.1295509 · Cited by 171 · see citing works
MicroRNA profiles of prostate carcinoma detected by multiplatform microRNA screening
Wach, S., Nolte, E., Szczyrba, J., Stöhr, R., Hartmann, A., Orntoft, T. F., Dyrskjøt, L., Eltze, E., Wieland, W. F., Keck, B., et al. (2011) · International Journal of Cancer · doi:10.1002/ijc.26064 · Cited by 164 · see citing works
A Comparison of Normalization Techniques for MicroRNA Microarray Data
Rao, Y., Lee, Y., Jarjoura, D. G., Ruppert, A. S., Liu, C., Hsu, J. C., & Hagan, J. P. (2008) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1287 · Cited by 116 · see citing works
Evaluation of normalization methods in mammalian microRNA-Seq data
Garmire, L. X., & Subramaniam, S. (2012) · RNA · doi:10.1261/rna.030916.111 · Cited by 108 · see citing works
New Perspectives in MicroRNA Regulation of Innate Immunity
Gantier, M. P. (2010) · Journal of Interferon & Cytokine Research · doi:10.1089/jir.2010.0037 · Cited by 71 · see citing works
Self-citationOshlack, A., Emslie, D., Corcoran, L. M., & Smyth, G. K. (2007) · Genome biology · doi:10.1186/gb-2007-8-1-r2 · Cited by 69 · see citing works
Self-citationDicer‐Processed Small RNAs: Rules and Exceptions
Langenberger, D., Çakır, M. V., Hoffmann, S., & Stadler, P. F. (2012) · Journal of Experimental Zoology Part B Molecular and Developmental Evolution · doi:10.1002/jez.b.22481 · Cited by 65 · see citing works
Ding, L.-H., Xie, Y., Park, S., Xiao, G., & Story, M. D. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn234 · Cited by 65 · see citing works
Meyer, S. U., Kaiser, S., Wagner, C., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0038946 · Cited by 57 · see citing works
Comparison of normalization methods with microRNA microarray
Hua, Y., Tu, K., Tang, Z.-Y., et al. (2008) · Genomics · doi:10.1016/j.ygeno.2008.04.002 · Cited by 55 · see citing works
Subset Quantile Normalization Using Negative Control Features
Wu, Z. J., & Aryee, M. J. (2010) · Journal of Computational Biology · doi:10.1089/cmb.2010.0049 · Cited by 53 · see citing works
A modified LOESS normalization applied to microRNA arrays: a comparative evaluation
Risso, D., Massa, M. S., Chiogna, M., & Romualdi, C. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp443 · Cited by 41 · see citing works
Estimating the proportion of microarray probes expressed in an RNA sample
Shi, W., de Graaf, C. A., Kinkel, S., Achtman, A. H., Baldwin, T. M., Schofield, L., Scott, H. S., Hilton, D. J., & Smyth, G. K. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkp1204 · Cited by 23 · see citing works
Self-citationEvaluation of normalization methods for two-channel microRNA microarrays
Zhao, Y., Wang, E., Liu, H., Rotunno, M., Koshiol, J. E., Marincola, F. M., Landi, M. T., & McShane, L. M. (2010) · Journal of Translational Medicine · doi:10.1186/1479-5876-8-69 · Cited by 19 · see citing works
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- Bolstad BM 2004 “ Low level analysis of high-density oligonucleotide array data: Background, normalization and summarization.” Ph.D. dissertation, University of California, Berkeley, CA
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limma powers differential expression analyses for RNA-sequencing and microarray studies
Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv007 · Cited by 40,458 · see citing works
Self-citationYu, L., Wu, D., Gao, H., Balic, J. J., Tsykin, A., Han, T.-S., Liu, Y. D., Kennedy, C. L., Li, J. K., Mao, J. Q., et al. (2018) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-17-2485 · Cited by 50 · see citing works
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- Authors
- Wu, D., Hu, Y., Tong, S., Williams, B. R. G., Smyth, G. K., & Gantier, M. P.
- Affiliations
- Harvard University (US)
- Walter and Eliza Hall Institute of Medical Research (AU)
- The University of Melbourne (AU)
- Monash University (AU)
- Corresponding author
- Gantier, Michael P.
- Venue
- RNA
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2013-05-24
- Volume
- 19
- Issue
- 7
- Pages
- 876-888
- ISSN
- 1355-8382 (ISSN-L)
- 1469-9001
- PMC
- PMC3683922
- OpenAlex
- W2107706017
- Cited by
- 71
- References
- 51
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 5 · 2023: 2 · 2022: 5 · 2021: 3 · 2020: 2 · 2019: 6 · 2018: 8 · 2017: 10 · 2016: 10 · 2015: 5 · 2014: 8
- FWCI
- 2.69
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- RNA (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by-nc)
- HighWire Press Open Archive (submittedVersion)
- Funders
- State Government of Victoria
- Medical Research Council
- National Health and Medical Research Council (1006590, 490970, 1022144)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › MicroRNA in disease regulation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Molecular Biology Techniques and Applications
- Keywords
- miRNA microarray, miRNA expression profiling, normalization bias, prostate cancer
- MeSH terms
- Animals, Fibroblasts, Humans, Male, Prostatic Neoplasms, RNA, Neoplasm, Sensitivity and Specificity, RNA Probes, Down-Regulation, Up-Regulation, Gene Expression Regulation, Neoplastic, Gene Deletion, Computational Biology, Oligonucleotide Array Sequence Analysis, MicroRNAs, Ribonuclease III, Mice, DEAD-box RNA Helicases
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