Gene 557 (2015) 195–200
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Comprehensive expression analysis of miRNA in breast cancer at the miRNA and isomiR levels Xianjin Wu a,b,1, Rong Zeng c,1, Shaoke Wu c, Jixin Zhong d, Lawei Yang e, Junfa Xu f,g,⁎ a
The First Affiliated Hospital of Jinan University, Guangzhou 510630, China Department of Clinical Laboratory, Affiliated Hospital of Guangdong Medical College, Zhanjiang, Guangdong 524001, China Orthopedic Center, Affiliated Hospital of Guangdong Medical College, Zhanjiang, Guangdong 524001, China d Oncology Center, Affiliated Hospital of Guangdong Medical College, Zhanjiang, Guangdong 524001, China e Clinical Research Center, Guangdong Medical College, Zhanjiang, Guangdong 524001, China f Institute of Laboratory Medicine, Guangdong Medical College, Dongguan 523808, China g Guangdong Provincial Key Laboratory of Medical Molecular Diagnostics, Dongguan 523808, China b c
a r t i c l e
i n f o
Article history: Received 5 August 2014 Received in revised form 9 December 2014 Accepted 14 December 2014 Available online 16 December 2014 Keywords: Breast cancer (BC) MicroRNA (miRNA) IsomiR Expression
a b s t r a c t Breast cancer (BC) is the main factor that leads cause of cancer death in women worldwide. A class of small noncoding RNAs, microRNAs (miRNAs), has been widely studied in human cancers as crucial regulatory molecule. Recent studies indicate that a series of isomiRs can be yielded from a miRNA locus, and these physiological miRNA isoforms have versatile roles in miRNA biogenesis. Herein, we performed a comprehensive analysis of miRNAs at the miRNA and isomiR levels in BC using next-generation sequencing data from The Cancer Genome Atlas (TCGA). Abnormally expressed miRNA (miR-21, miR-221, miR-155, miR-30e and miR-25) and isomiR profiles could be obtained at the miRNA and isomiR levels, and similar biological roles could be detected. IsomiR expression profiles should be further concerned, and especially isomiRs are actual regulatory molecules in the miRNA–mRNA regulatory networks. The study provides a comprehensive expression analysis at the miRNA and isomiR levels in BC, which indicates biological roles of isomiRs. © 2014 Elsevier B.V. All rights reserved.
1. Introduction MicroRNAs (miRNAs), a series of small non-coding RNAs, about 22 nts (nucleotides) in length, can negatively regulate gene expression at the post-transcriptional levels (Bartel, 2004). As phylogenetically wellconserved miRNAs, they have similar roles in the development of diverse species, especially in the animal kingdom (Bartel and Chen, 2004; Plasterk, 2006). Critical roles in various biological processes, including cell development, differentiation, proliferation, apoptosis and metabolism (Alvarez-Garcia and Miska, 2005), have been widely reported and identified. Some miRNAs are located at fragile sites or genomic regions, have been validated as crucial regulatory molecules in specific human diseases, including various cancers, and they are prone to be aberrantly expressed in cancers due to frequent deletion or amplification (Wang et al., 2009; Cho, 2010). The dysregulation of miRNAs is mainly derived from nucleotide deletion, mutation and methylation of miRNA genes in human disease. Indeed, a series of miRNAs have been Abbreviations: BC, breast cancer; KEGG, Kyoto Encyclopedia of Genes and Genomes; GO, geneontology; BRCA, breastcancer tissue; BRCA-NT, breast cancer-normaltissue; TCGA,The Cancer Genome Atlas. ⁎ Corresponding author at: Institute of Laboratory Medicine, Guangdong Medical College, Dongguan 523808, China. E-mail address: [email protected] (J. Xu). 1 X. Wu and R. Zeng contributed equally to this work.
http://dx.doi.org/10.1016/j.gene.2014.12.030 0378-1119/© 2014 Elsevier B.V. All rights reserved.
characterized as potential tumor suppressors or oncomiRs, and have potential biological roles in the occurrence and development of cancer. More recently, polymorphisms in miRNAs themselves or in their binding sites in target genes have been identified to incur increased risk of breast cancer in certain populations (Mulrane et al., 2013). The small RNAs are quite stable and are not degraded, and emerging evidence suggests that the small RNAs may be potential biomarkers, especially for circulating miRNAs (Ji et al., 2009; Huang et al., 2010; Tsujiura et al., 2010; Brase et al., 2011; Madhavan et al., 2012; Redova et al., 2013). Some miRNAs were identified to be associated with human tumors, such as ovarian cancer and colon cancer. Thus, miRNA expression profile can classify different human cancers (Lu et al., 2005). Breast cancer is the most common cancer in women worldwide (Lacey et al., 2002). Patients have a very poor prognosis. A major reason of BC is BRCA1 mutation that plays an important role in DNA doublestrand break repair, contributing to the maintenance of DNA stability (Pongsavee et al., 2009). In recent decades, miRNAs have been involved in the study of the human diseases, including BC (Kondo et al., 2008; Miller et al., 2008; Valastyan et al., 2009; Yang et al., 2009; Png et al., 2011; Augoff et al., 2012). By applying miRNA microarrays and high throughput sequencing technologies, a series of miRNAs have been reported to be associated with BC. For example, dysregulation of miR210 is correlated with tumor aggressiveness and poor prognosis (Madhavan et al., 2012; Volinia et al., 2012), while miR-355 inhibits
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tumor reinitiation (Hongay et al., 2006). Most current studies only focus on single miRNA sequence from miRBase database, and the specific sequence is canonical miRNA sequences. However, recent studies have indicated that a series of multiple variants, termed as isomiRs (Borel and Antonarakis, 2008), can be yielded from a miRNA locus, and these physiological miRNA isoforms have versatile roles in miRNA biogenesis (Guo et al., 2011, 2013b; Guo and Chen, 2014). In the study, we attempted to investigate expression of some miRNAs in BC, especially at the miRNA and isomiR levels. Firstly, a series of associated BC miRNAs (miR-21 (Qian et al., 2009; Selcuklu et al., 2009; Wickramasinghe et al., 2009; Yang et al., 2009; Madhavan et al., 2012; Volinia et al., 2012), miR-221 (Zhao et al., 2011; Dentelli et al., 2014), miR-155 (Sun et al., 2012; Wang and Wu, 2012; Zhang et al., 2013; Dinami et al., 2014), miR-30e (Ouzounova et al., 2013) and miR-25 (Wu et al., 2012; Guo et al., 2013a)) are collected according to published literatures. These miRNAs have been reported as crucial regulatory molecules in occurrence and development of BC. Secondly, expression profiles at the miRNA and isomiR levels are analyzed using public small RNA database. Thirdly, these miRNAs are validated by RTqPCR method. Finally, functional analysis of KEGG/GO pathways of these miRNAs is performed based on predicted target mRNAs. The study will provide new sights for miRNAs, especially at the isomiR levels. 2. Methods and material 2.1. Source data from public database miRNA expression data were collected from public database of small RNA sequencing data in The Cancer Genome Atlas (TCGA) pilot project which is established by the National Cancer Institute (NCI) and National Human Genome Research Institute (NHGRI) (https://tcga-data.nci.nih. gov/tcga/dataAccessMatrix.htm). A total of 683 breast cancer tissue (BRCA) and 87 normal tissues (breast cancer-normal tissue, BRCA-NT) were obtained from TCGA database. Expression data of several specific miRNAs at the miRNA and isomiR levels were further extracted using self-developed scripts. The miRNA sequences were obtained from the canonical public miRBase database (Release 20.0, http://www. mirbase.org/), and isomiR sequences were identified based on the miRNA sequences on pre-miRNAs (precursor miRNAs). 2.2. Sample collection and RT-qPCR confirmation A total of 10 paired BC tumor and adjacent normal tissues were obtained from 10 patients. The institutional review board of Guangdong Medical College approved this study, and written informed consent was obtained from each participant prior to tissue acquisition. Bulge-loop miRNA qRT-PCR Primer Sets (one RT primer and a pair of qPCR primers for each set) specific for miR-21, miR-221, miR-155, miR30e and miR-25 were designed by RiboBio (Guangzhou, China). Total RNA from these tissues was respectively extracted with TRIzol Reagent (Invitrogen Corp., Carlsbad, CA), and miRNA bulge-loop was then reverse transcribed with the PrimeScript RT reagent kit (Takara Bio, Tokyo, Japan). According to the indicated manufacturer's instructions, miRNA was quantified by qPCR using SYBR Premix Ex TaqTM II (Takara Bio, Tokyo, Japan), and miRNA expression was normalized to snRNA U6. Three independent experiments were performed, and mean with standard errors were presented. 2.3. Functional analysis Target mRNAs of these miRNAs were predicted using the TargetScan program (http://www.targetscan.org/) (the cutoff of total context score was ≤−0.30) (Lewis et al., 2003). These mRNAs were analyzed Gene Ontology and KEGG pathway Enrichment categories using the CapitalBio
Molecule Annotation System V4.0 (MAS, http://bioinfo.capitalbio.com/ mas3/). 2.4. Statistical analysis Firstly, the relative expression level of isomiR was described using expression rate in the miRNA locus. According to the expression rates in different individuals, isomiRs were described using x ± sd (mean ± standard deviation) based on the relative expression rates. A t-test was used to estimate the difference between isomiR expression profiles using public data, and a paired t-test was used to estimate the difference using confirmed data. P value b 0.05 was considered statistically significant, and all tests were conducted using Stata software (Version 11.0). 3. Results 3.1. Obtained miRNAs and expression patents According to collected miRNAs from the published literatures, we found that they were abundantly expressed in BC and normal tissues in TCGA database. In each miRNA locus, a series of isomiRs could be detected (Fig. 1). In some miRNA loci, there was only one specific dominantly expressed isomiR, for example, in miR-25 and miR-30e (Fig. 1). These isomiRs always had the same 5′ positions on human chromosomes, which leaded to the same 5′ ends. The annotated miRNA sequences in miRBase database were always dominant sequences. Compared to the canonical miRNA sequences, other isomiRs had the same 5′ ends. Statistical analysis showed that no significant difference could be detected between BC and normal tissues based on the isomiR expression profiles (Table 1). 3.2. Validation of the differentially expressed miRNAs (miR-21, miR-221, miR-155, miR-30e, miR-25) by RT-qPCR Similar to literatures and bioinformatics analysis from the public database, these miRNAs (miR-21, miR-221, miR-155, miR-30e, miR-25) showed diverse deregulated expression patterns. Except for miR-221, other miRNAs were up-regulated and had higher expression levels in BC (especially for miR-30e and miR-155), while miR-221 was downregulated (Fig. 2). Over-expression of miRNAs would lead to down-regulation of target mRNAs, whereas down-expression of miRNAs would lead to over-regulation of target mRNAs. Deregulated miRNAs would play an important role in biological process, which might lead to a series of abnormal biological pathways. 3.3. Analysis of KEGG/GO pathways Based on predicted mRNAs of miRNAs, functional analysis was performed. Although there were a series of isomiRs that could be detected from the miRNA locus, due to the same 5′ ends between them, the common targets could be obtained. The main reason was that the prediction of target mRNAs was performed based on the seed sequences of miRNAs. Functional enrichment analysis showed that these miRNAs had important roles in basic biological regulatory network (Fig. 3). miRNAs contributed to biological processes via regulating directly or indirectly mRNAs in networks. Simultaneously, we found that involved KEGG/GO pathways included some basic biological processes, such as calcium signaling pathway, regulation of actin cytoskeleton, and MAPK signaling pathway. KEGG pathways suggested that they also contributed to the occurrence and development of some human cancers, including colorectal cancer and small cell lung cancer (Tables 2 and 3). 4. Discussion As a class of single-stranded non-coding-RNA regulatory molecules, miRNAs have been largely concerned. They can control gene expression
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Fig. 1. IsomiR expression profiles from miRNA loci. Only those dominant isomiRs (N5%) are presented here.
in many cellular processes by reducing the stability of mRNAs, including those of genes that mediate processes in tumorigenesis, such as inflammation, cell cycle regulation, stress response, differentiation, apoptosis and invasion. miRNAs target mRNAs through specific base-pairing interactions between the 5′ end (“seed” region) of the miRNA and sites within coding and untranslated regions (UTRs) of mRNAs. Target sites in the 3′ UTR would lead to more effective mRNA destabilization. Prediction analysis shows that miRNAs can target hundreds of mRNAs, and vice versa. These results reveal a quite complex regulatory pathway or network. Simultaneously, accumulating reports suggest that miRNA sequence is not only a single sequence, but also a series of isomiR sequences (Guo and Chen, 2014). A miRNA locus can generate a series of multiple sequences with various lengths, 5′ and 3′ ends, and these sequences also have various expression levels. However, fewer studies are involved in the isomiRs, although some isomiRs have been identified as potential regulatory molecules with versatile biological roles (Guo et al., 2013b; Kozlowska et al., 2013). More and more researches showed that the miRNAs were related with tumor metastasis in BC. Expression of miR-126 and miR-335 is lost in the majority of primary breast tumors from patients who relapse, and the loss of expression of either microRNA is associated with poor distal metastasis-free survival. miR-335 and miR-126 are thus identified as metastasis suppressor microRNAs in human breast cancer (Tavazoie et al., 2008). Herein, based on the selected important miRNAs in BC, we found that these miRNAs have various isomiR expression profiles as expected (Fig. 1), suggesting the widespread phenomenon of multiple isomiRs in miRNAs. Indeed, in animal and plant miRNAs, almost all the miRNA loci have detected the multiple isomiRs, despite the fact that the types of
these isomiRs may be different, especially those dominantly expressed isomiRs. In the involved miRNA loci, we found that although a series of isomiRs are detected, only 1–3 of them are dominantly expressed, and only one specific isomiR is quite dominantly expressed in the specific miRNA locus. Indeed, most of these isomiRs have the same 5′ ends, and therefore they are prone to have the same seed sequences. Generally, the same seed sequences can be found between isomiRs and their canonical miRNA sequences, which reveal that they possessed the same target mRNAs using the TargetScan program and function analysis showed that they were involved in the same biological pathways. According to the current studies, these isomiRs are mainly derived from the imprecise and alternative cleavage of Drosha and Dicer in pre-miRNA processing and miRNA maturation processes (Cloonan et al., 2011; Neilsen et al., 2012; Guo and Chen, 2014). The interesting distributions of 5′ ends and seed sequences suggest that these isomiRs can co-coordinately regulate the same target mRNAs and contribute to the same biological pathways. isomiRs may be the extension of the miRNAs, which will contribute to flexible and robust coding– non-coding RNA regulatory network. Moreover, we found that the
Table 1 Statistical analysis of isomiR expression between tumor and control tissues. miRNA
Tumor vs. control
Mean
t value
P value
miR-21 miR-221 miR-155 miR-30e miR-25
BRCA vs. BRCA-NT BRCA vs. BRCA-NT BRCA vs. BRCA-NT BRCA vs. BRCA-NT BRCA vs. BRCA-NT
0.193 0.786 −0.068 0.304 0.094
0.101 0.527 −0.067 0.102 0.057
0.923 0.614 0.950 0.923 0.958
Fig. 2. RT-qPCR validation of typical deregulated miRNAs in BC tissues.
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Fig. 3. Gene pathway of KEGG. Functional enrichment analysis of miRNAs in this study showed important roles in basic biological regulatory network.
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Table 2 Enriched KEGG pathways based on involved miRNAs. Pathway
Count
P-value
Gene
Calcium signaling pathway Regulation of actin cytoskeleton MAPK signaling pathway Ubiquitin mediated proteolysis Colorectal cancer Melanogenesis Focal adhesion Neuroactive ligand–receptor interaction Cytokine–cytokine receptor interaction TGF-beta signaling pathway ErbB signaling pathway GnRH signaling pathway Cell cycle Purine metabolism Wnt signaling pathway Amyotrophic lateral sclerosis (ALS) Long-term potentiation Adherens junction Small cell lung cancer Gap junction
11 10 10 9 7 7 7 7 7 6 6 6 6 6 6 5 5 5 5 5
1.30E−07 5.28E−06 3.91E−05 9.34E−07 2.88E−06 1.19E−05 8.19E−04 0.002896 0.003289 4.42E−05 4.42E−05 1.40E−04 2.50E−04 9.14E−04 9.14E−04 5.63E−05 2.27E−04 2.90E−04 4.30E−04 6.15E−04
ADCY3;ADCY8;ADRB1;ATP2A2;CACNA1I;CAMK2A;CHRM5;GNAS;ITPR1;PPP3R1;SLC8A3 ARHGEF7;CHRM5;FGF18;ITGA5;ITGAV;PIK3R3;PIP5K3;TIAM1;VCL;WASL ACVR1C;CACNA1I;CACNB4;DUSP10;DUSP5;FGF18;MAP2K4;NLK;NTF3;PPP3R1 CDC27;DET1;FBXW7;HERC4;UBE2D3;UBE2J1;UBE2W;UBE2Z;WWP2 ACVR1C;APPL1;FZD3;FZD9;MSH2;PIK3R3;SMAD2 ADCY3;ADCY8;CAMK2A;FZD3;FZD9;GNAS;KIT COL1A2;ITGA5;ITGAV;KDR;PIK3R3;PTEN;VCL ADRB1;CHRM5;GABRA1;GABRB1;GLRA1;GRIA1;PTGER4 BMPR2;CCL1;CCL20;CXCL12;IL12A;KDR;KIT ACVR1C;BMPR2;GDF6;SMAD2;SMAD7;SP1 CAMK2A;CDKN1B;MAP2K4;NRG1;NRG3;PIK3R3 ADCY3;ADCY8;CAMK2A;GNAS;ITPR1;MAP2K4 CCNE2;CDC27;CDC7;CDKN1B;SMAD2;YWHAG ADCY3;ADCY8;NT5E;PDE10A;PDE7A;PRUNE CAMK2A;FZD3;FZD9;NLK;PPP3R1;SMAD2 GRIA1;NEFH;NEFL;NEFM;PPP3R1 ADCY8;CAMK2A;GRIA1;ITPR1;PPP3R1 ACVR1C;NLK;SMAD2;VCL;WASL CCNE2;CDKN1B;ITGAV;PIK3R3;PTEN ADCY3;ADCY8;ADRB1;GNAS;ITPR1
similar expression patterns of isomiRs can be detected in miRNAs between tumor and normal tissues, which suggest stable miRNA maturation and processing process. The relative stable isomiR expression patterns may contribute to regulatory networks. RT-qPCR results show consistent results with reported results and bioinformatics analysis of public database in BC and normal tissues (Figs. 1 and 2). These miRNAs have important roles in regulatory networks by regulating multiple target mRNAs. Functional enrichment analysis shows that they have important roles in some basic biological processes and some human cancers, which implies the important Table 3 GO analysis of target mRNAs of miRNAs in the study. GO enrichment
GO term
Biological process
GO:0006355 regulation of transcription, DNA-dependent GO:0006350 transcription GO:0007165 signal transduction GO:0007275 development GO:0006811 ion transport GO:0019941 modification-dependent protein catabolism GO:0015031 protein transport GO:0006468 protein amino acid phosphorylation GO:0007155 cell adhesion GO:0008150 biological_process GO:0005634 nucleus GO:0005737 cytoplasm GO:0016020 membrane GO:0016021 integral to membrane GO:0005886 plasma membrane GO:0005622 intracellular GO:0005794 Golgi apparatus GO:0005829 cytosol GO:0005576 extracellular region GO:0005783 endoplasmic reticulum GO:0005515 protein binding GO:0046872 metal ion binding GO:0008270 zinc ion binding GO:0000166 nucleotide binding GO:0003700 transcription factor activity GO:0005524 ATP binding GO:0003677 DNA binding GO:0016740 transferase activity GO:0005509 calcium ion binding GO:0016787 hydrolase activity
Cellular component
Molecular function
Count P-value 82
6.76E−81
67 41 30 20 19
1.05E−57 6.01E−22 2.22E−17 1.60E−18 2.27E−19
19 17
7.75E−17 3.33E−15
17 15 176 146 131 111 74 64 36 33 33 28 183 78 77 58 40 39 39 35 29 27
2.14E−14 0.9751598 1.49E−177 2.76E−114 4.40E−95 7.70E−86 2.36E−56 8.69E−19 3.48E−39 4.81E−33 2.77E−22 7.47E−27 1.18E−159 3.30E−57 2.24E−74 2.56E−52 3.65E−43 6.16E−36 5.45E−27 1.54E−27 6.14E−28 1.43E−15
roles of these miRNAs. Indeed, some specific miRNAs have been widely concerned and studied as a potential biomarker to diagnose disease, and even as a potential target for treatment. Our study has shown their expression and function in BC, and further study should be performed based on the larger samples, especially using miRNAs in serum. Simultaneously, miRNA study should also be performed at the isomiR level, although most isomiRs have the same 5′ ends and seed sequences with the canonical miRNA sequences. The stable isomiR expression can be detected between different samples, but diverse expression patterns can be detected based on the specific isomiR sequence (Fig. 1). The study at the isomiR level is quite necessary; especially if it may have versatile biological roles, such as influencing the miRNA stability. Collectively, based on several selected crucial miRNAs in BC, a series of isomiR sequences that have various sequences, length distributions, 5′ and 3′ ends, and expression levels can be detected. The canonical miRNA sequence is only a specific sequence in multiple isomiRs. Consistent results can be detected among literatures, public database and experimental validation, and these findings suggest the crucial biological roles of these abnormally expressed miRNAs. The study provides more insights in miRNAs, especially at the isomiR levels. Conflict of interests
Top ten in GO enrichment (biological process, cellular component, molecular function).
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Gene journal homepage: www.elsevier.com/locate/gene
Comprehensive expression analysis of miRNA in breast cancer at the miRNA and isomiR levels Xianjin Wu a,b,1, Rong Zeng c,1, Shaoke Wu c, Jixin Zhong d, Lawei Yang e, Junfa Xu f,g,⁎ a
The First Affiliated Hospital of Jinan University, Guangzhou 510630, China Department of Clinical Laboratory, Affiliated Hospital of Guangdong Medical College, Zhanjiang, Guangdong 524001, China Orthopedic Center, Affiliated Hospital of Guangdong Medical College, Zhanjiang, Guangdong 524001, China d Oncology Center, Affiliated Hospital of Guangdong Medical College, Zhanjiang, Guangdong 524001, China e Clinical Research Center, Guangdong Medical College, Zhanjiang, Guangdong 524001, China f Institute of Laboratory Medicine, Guangdong Medical College, Dongguan 523808, China g Guangdong Provincial Key Laboratory of Medical Molecular Diagnostics, Dongguan 523808, China b c
a r t i c l e
i n f o
Article history: Received 5 August 2014 Received in revised form 9 December 2014 Accepted 14 December 2014 Available online 16 December 2014 Keywords: Breast cancer (BC) MicroRNA (miRNA) IsomiR Expression
a b s t r a c t Breast cancer (BC) is the main factor that leads cause of cancer death in women worldwide. A class of small noncoding RNAs, microRNAs (miRNAs), has been widely studied in human cancers as crucial regulatory molecule. Recent studies indicate that a series of isomiRs can be yielded from a miRNA locus, and these physiological miRNA isoforms have versatile roles in miRNA biogenesis. Herein, we performed a comprehensive analysis of miRNAs at the miRNA and isomiR levels in BC using next-generation sequencing data from The Cancer Genome Atlas (TCGA). Abnormally expressed miRNA (miR-21, miR-221, miR-155, miR-30e and miR-25) and isomiR profiles could be obtained at the miRNA and isomiR levels, and similar biological roles could be detected. IsomiR expression profiles should be further concerned, and especially isomiRs are actual regulatory molecules in the miRNA–mRNA regulatory networks. The study provides a comprehensive expression analysis at the miRNA and isomiR levels in BC, which indicates biological roles of isomiRs. © 2014 Elsevier B.V. All rights reserved.
1. Introduction MicroRNAs (miRNAs), a series of small non-coding RNAs, about 22 nts (nucleotides) in length, can negatively regulate gene expression at the post-transcriptional levels (Bartel, 2004). As phylogenetically wellconserved miRNAs, they have similar roles in the development of diverse species, especially in the animal kingdom (Bartel and Chen, 2004; Plasterk, 2006). Critical roles in various biological processes, including cell development, differentiation, proliferation, apoptosis and metabolism (Alvarez-Garcia and Miska, 2005), have been widely reported and identified. Some miRNAs are located at fragile sites or genomic regions, have been validated as crucial regulatory molecules in specific human diseases, including various cancers, and they are prone to be aberrantly expressed in cancers due to frequent deletion or amplification (Wang et al., 2009; Cho, 2010). The dysregulation of miRNAs is mainly derived from nucleotide deletion, mutation and methylation of miRNA genes in human disease. Indeed, a series of miRNAs have been Abbreviations: BC, breast cancer; KEGG, Kyoto Encyclopedia of Genes and Genomes; GO, geneontology; BRCA, breastcancer tissue; BRCA-NT, breast cancer-normaltissue; TCGA,The Cancer Genome Atlas. ⁎ Corresponding author at: Institute of Laboratory Medicine, Guangdong Medical College, Dongguan 523808, China. E-mail address: [email protected] (J. Xu). 1 X. Wu and R. Zeng contributed equally to this work.
http://dx.doi.org/10.1016/j.gene.2014.12.030 0378-1119/© 2014 Elsevier B.V. All rights reserved.
characterized as potential tumor suppressors or oncomiRs, and have potential biological roles in the occurrence and development of cancer. More recently, polymorphisms in miRNAs themselves or in their binding sites in target genes have been identified to incur increased risk of breast cancer in certain populations (Mulrane et al., 2013). The small RNAs are quite stable and are not degraded, and emerging evidence suggests that the small RNAs may be potential biomarkers, especially for circulating miRNAs (Ji et al., 2009; Huang et al., 2010; Tsujiura et al., 2010; Brase et al., 2011; Madhavan et al., 2012; Redova et al., 2013). Some miRNAs were identified to be associated with human tumors, such as ovarian cancer and colon cancer. Thus, miRNA expression profile can classify different human cancers (Lu et al., 2005). Breast cancer is the most common cancer in women worldwide (Lacey et al., 2002). Patients have a very poor prognosis. A major reason of BC is BRCA1 mutation that plays an important role in DNA doublestrand break repair, contributing to the maintenance of DNA stability (Pongsavee et al., 2009). In recent decades, miRNAs have been involved in the study of the human diseases, including BC (Kondo et al., 2008; Miller et al., 2008; Valastyan et al., 2009; Yang et al., 2009; Png et al., 2011; Augoff et al., 2012). By applying miRNA microarrays and high throughput sequencing technologies, a series of miRNAs have been reported to be associated with BC. For example, dysregulation of miR210 is correlated with tumor aggressiveness and poor prognosis (Madhavan et al., 2012; Volinia et al., 2012), while miR-355 inhibits
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tumor reinitiation (Hongay et al., 2006). Most current studies only focus on single miRNA sequence from miRBase database, and the specific sequence is canonical miRNA sequences. However, recent studies have indicated that a series of multiple variants, termed as isomiRs (Borel and Antonarakis, 2008), can be yielded from a miRNA locus, and these physiological miRNA isoforms have versatile roles in miRNA biogenesis (Guo et al., 2011, 2013b; Guo and Chen, 2014). In the study, we attempted to investigate expression of some miRNAs in BC, especially at the miRNA and isomiR levels. Firstly, a series of associated BC miRNAs (miR-21 (Qian et al., 2009; Selcuklu et al., 2009; Wickramasinghe et al., 2009; Yang et al., 2009; Madhavan et al., 2012; Volinia et al., 2012), miR-221 (Zhao et al., 2011; Dentelli et al., 2014), miR-155 (Sun et al., 2012; Wang and Wu, 2012; Zhang et al., 2013; Dinami et al., 2014), miR-30e (Ouzounova et al., 2013) and miR-25 (Wu et al., 2012; Guo et al., 2013a)) are collected according to published literatures. These miRNAs have been reported as crucial regulatory molecules in occurrence and development of BC. Secondly, expression profiles at the miRNA and isomiR levels are analyzed using public small RNA database. Thirdly, these miRNAs are validated by RTqPCR method. Finally, functional analysis of KEGG/GO pathways of these miRNAs is performed based on predicted target mRNAs. The study will provide new sights for miRNAs, especially at the isomiR levels. 2. Methods and material 2.1. Source data from public database miRNA expression data were collected from public database of small RNA sequencing data in The Cancer Genome Atlas (TCGA) pilot project which is established by the National Cancer Institute (NCI) and National Human Genome Research Institute (NHGRI) (https://tcga-data.nci.nih. gov/tcga/dataAccessMatrix.htm). A total of 683 breast cancer tissue (BRCA) and 87 normal tissues (breast cancer-normal tissue, BRCA-NT) were obtained from TCGA database. Expression data of several specific miRNAs at the miRNA and isomiR levels were further extracted using self-developed scripts. The miRNA sequences were obtained from the canonical public miRBase database (Release 20.0, http://www. mirbase.org/), and isomiR sequences were identified based on the miRNA sequences on pre-miRNAs (precursor miRNAs). 2.2. Sample collection and RT-qPCR confirmation A total of 10 paired BC tumor and adjacent normal tissues were obtained from 10 patients. The institutional review board of Guangdong Medical College approved this study, and written informed consent was obtained from each participant prior to tissue acquisition. Bulge-loop miRNA qRT-PCR Primer Sets (one RT primer and a pair of qPCR primers for each set) specific for miR-21, miR-221, miR-155, miR30e and miR-25 were designed by RiboBio (Guangzhou, China). Total RNA from these tissues was respectively extracted with TRIzol Reagent (Invitrogen Corp., Carlsbad, CA), and miRNA bulge-loop was then reverse transcribed with the PrimeScript RT reagent kit (Takara Bio, Tokyo, Japan). According to the indicated manufacturer's instructions, miRNA was quantified by qPCR using SYBR Premix Ex TaqTM II (Takara Bio, Tokyo, Japan), and miRNA expression was normalized to snRNA U6. Three independent experiments were performed, and mean with standard errors were presented. 2.3. Functional analysis Target mRNAs of these miRNAs were predicted using the TargetScan program (http://www.targetscan.org/) (the cutoff of total context score was ≤−0.30) (Lewis et al., 2003). These mRNAs were analyzed Gene Ontology and KEGG pathway Enrichment categories using the CapitalBio
Molecule Annotation System V4.0 (MAS, http://bioinfo.capitalbio.com/ mas3/). 2.4. Statistical analysis Firstly, the relative expression level of isomiR was described using expression rate in the miRNA locus. According to the expression rates in different individuals, isomiRs were described using x ± sd (mean ± standard deviation) based on the relative expression rates. A t-test was used to estimate the difference between isomiR expression profiles using public data, and a paired t-test was used to estimate the difference using confirmed data. P value b 0.05 was considered statistically significant, and all tests were conducted using Stata software (Version 11.0). 3. Results 3.1. Obtained miRNAs and expression patents According to collected miRNAs from the published literatures, we found that they were abundantly expressed in BC and normal tissues in TCGA database. In each miRNA locus, a series of isomiRs could be detected (Fig. 1). In some miRNA loci, there was only one specific dominantly expressed isomiR, for example, in miR-25 and miR-30e (Fig. 1). These isomiRs always had the same 5′ positions on human chromosomes, which leaded to the same 5′ ends. The annotated miRNA sequences in miRBase database were always dominant sequences. Compared to the canonical miRNA sequences, other isomiRs had the same 5′ ends. Statistical analysis showed that no significant difference could be detected between BC and normal tissues based on the isomiR expression profiles (Table 1). 3.2. Validation of the differentially expressed miRNAs (miR-21, miR-221, miR-155, miR-30e, miR-25) by RT-qPCR Similar to literatures and bioinformatics analysis from the public database, these miRNAs (miR-21, miR-221, miR-155, miR-30e, miR-25) showed diverse deregulated expression patterns. Except for miR-221, other miRNAs were up-regulated and had higher expression levels in BC (especially for miR-30e and miR-155), while miR-221 was downregulated (Fig. 2). Over-expression of miRNAs would lead to down-regulation of target mRNAs, whereas down-expression of miRNAs would lead to over-regulation of target mRNAs. Deregulated miRNAs would play an important role in biological process, which might lead to a series of abnormal biological pathways. 3.3. Analysis of KEGG/GO pathways Based on predicted mRNAs of miRNAs, functional analysis was performed. Although there were a series of isomiRs that could be detected from the miRNA locus, due to the same 5′ ends between them, the common targets could be obtained. The main reason was that the prediction of target mRNAs was performed based on the seed sequences of miRNAs. Functional enrichment analysis showed that these miRNAs had important roles in basic biological regulatory network (Fig. 3). miRNAs contributed to biological processes via regulating directly or indirectly mRNAs in networks. Simultaneously, we found that involved KEGG/GO pathways included some basic biological processes, such as calcium signaling pathway, regulation of actin cytoskeleton, and MAPK signaling pathway. KEGG pathways suggested that they also contributed to the occurrence and development of some human cancers, including colorectal cancer and small cell lung cancer (Tables 2 and 3). 4. Discussion As a class of single-stranded non-coding-RNA regulatory molecules, miRNAs have been largely concerned. They can control gene expression
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Fig. 1. IsomiR expression profiles from miRNA loci. Only those dominant isomiRs (N5%) are presented here.
in many cellular processes by reducing the stability of mRNAs, including those of genes that mediate processes in tumorigenesis, such as inflammation, cell cycle regulation, stress response, differentiation, apoptosis and invasion. miRNAs target mRNAs through specific base-pairing interactions between the 5′ end (“seed” region) of the miRNA and sites within coding and untranslated regions (UTRs) of mRNAs. Target sites in the 3′ UTR would lead to more effective mRNA destabilization. Prediction analysis shows that miRNAs can target hundreds of mRNAs, and vice versa. These results reveal a quite complex regulatory pathway or network. Simultaneously, accumulating reports suggest that miRNA sequence is not only a single sequence, but also a series of isomiR sequences (Guo and Chen, 2014). A miRNA locus can generate a series of multiple sequences with various lengths, 5′ and 3′ ends, and these sequences also have various expression levels. However, fewer studies are involved in the isomiRs, although some isomiRs have been identified as potential regulatory molecules with versatile biological roles (Guo et al., 2013b; Kozlowska et al., 2013). More and more researches showed that the miRNAs were related with tumor metastasis in BC. Expression of miR-126 and miR-335 is lost in the majority of primary breast tumors from patients who relapse, and the loss of expression of either microRNA is associated with poor distal metastasis-free survival. miR-335 and miR-126 are thus identified as metastasis suppressor microRNAs in human breast cancer (Tavazoie et al., 2008). Herein, based on the selected important miRNAs in BC, we found that these miRNAs have various isomiR expression profiles as expected (Fig. 1), suggesting the widespread phenomenon of multiple isomiRs in miRNAs. Indeed, in animal and plant miRNAs, almost all the miRNA loci have detected the multiple isomiRs, despite the fact that the types of
these isomiRs may be different, especially those dominantly expressed isomiRs. In the involved miRNA loci, we found that although a series of isomiRs are detected, only 1–3 of them are dominantly expressed, and only one specific isomiR is quite dominantly expressed in the specific miRNA locus. Indeed, most of these isomiRs have the same 5′ ends, and therefore they are prone to have the same seed sequences. Generally, the same seed sequences can be found between isomiRs and their canonical miRNA sequences, which reveal that they possessed the same target mRNAs using the TargetScan program and function analysis showed that they were involved in the same biological pathways. According to the current studies, these isomiRs are mainly derived from the imprecise and alternative cleavage of Drosha and Dicer in pre-miRNA processing and miRNA maturation processes (Cloonan et al., 2011; Neilsen et al., 2012; Guo and Chen, 2014). The interesting distributions of 5′ ends and seed sequences suggest that these isomiRs can co-coordinately regulate the same target mRNAs and contribute to the same biological pathways. isomiRs may be the extension of the miRNAs, which will contribute to flexible and robust coding– non-coding RNA regulatory network. Moreover, we found that the
Table 1 Statistical analysis of isomiR expression between tumor and control tissues. miRNA
Tumor vs. control
Mean
t value
P value
miR-21 miR-221 miR-155 miR-30e miR-25
BRCA vs. BRCA-NT BRCA vs. BRCA-NT BRCA vs. BRCA-NT BRCA vs. BRCA-NT BRCA vs. BRCA-NT
0.193 0.786 −0.068 0.304 0.094
0.101 0.527 −0.067 0.102 0.057
0.923 0.614 0.950 0.923 0.958
Fig. 2. RT-qPCR validation of typical deregulated miRNAs in BC tissues.
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Fig. 3. Gene pathway of KEGG. Functional enrichment analysis of miRNAs in this study showed important roles in basic biological regulatory network.
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Table 2 Enriched KEGG pathways based on involved miRNAs. Pathway
Count
P-value
Gene
Calcium signaling pathway Regulation of actin cytoskeleton MAPK signaling pathway Ubiquitin mediated proteolysis Colorectal cancer Melanogenesis Focal adhesion Neuroactive ligand–receptor interaction Cytokine–cytokine receptor interaction TGF-beta signaling pathway ErbB signaling pathway GnRH signaling pathway Cell cycle Purine metabolism Wnt signaling pathway Amyotrophic lateral sclerosis (ALS) Long-term potentiation Adherens junction Small cell lung cancer Gap junction
11 10 10 9 7 7 7 7 7 6 6 6 6 6 6 5 5 5 5 5
1.30E−07 5.28E−06 3.91E−05 9.34E−07 2.88E−06 1.19E−05 8.19E−04 0.002896 0.003289 4.42E−05 4.42E−05 1.40E−04 2.50E−04 9.14E−04 9.14E−04 5.63E−05 2.27E−04 2.90E−04 4.30E−04 6.15E−04
ADCY3;ADCY8;ADRB1;ATP2A2;CACNA1I;CAMK2A;CHRM5;GNAS;ITPR1;PPP3R1;SLC8A3 ARHGEF7;CHRM5;FGF18;ITGA5;ITGAV;PIK3R3;PIP5K3;TIAM1;VCL;WASL ACVR1C;CACNA1I;CACNB4;DUSP10;DUSP5;FGF18;MAP2K4;NLK;NTF3;PPP3R1 CDC27;DET1;FBXW7;HERC4;UBE2D3;UBE2J1;UBE2W;UBE2Z;WWP2 ACVR1C;APPL1;FZD3;FZD9;MSH2;PIK3R3;SMAD2 ADCY3;ADCY8;CAMK2A;FZD3;FZD9;GNAS;KIT COL1A2;ITGA5;ITGAV;KDR;PIK3R3;PTEN;VCL ADRB1;CHRM5;GABRA1;GABRB1;GLRA1;GRIA1;PTGER4 BMPR2;CCL1;CCL20;CXCL12;IL12A;KDR;KIT ACVR1C;BMPR2;GDF6;SMAD2;SMAD7;SP1 CAMK2A;CDKN1B;MAP2K4;NRG1;NRG3;PIK3R3 ADCY3;ADCY8;CAMK2A;GNAS;ITPR1;MAP2K4 CCNE2;CDC27;CDC7;CDKN1B;SMAD2;YWHAG ADCY3;ADCY8;NT5E;PDE10A;PDE7A;PRUNE CAMK2A;FZD3;FZD9;NLK;PPP3R1;SMAD2 GRIA1;NEFH;NEFL;NEFM;PPP3R1 ADCY8;CAMK2A;GRIA1;ITPR1;PPP3R1 ACVR1C;NLK;SMAD2;VCL;WASL CCNE2;CDKN1B;ITGAV;PIK3R3;PTEN ADCY3;ADCY8;ADRB1;GNAS;ITPR1
similar expression patterns of isomiRs can be detected in miRNAs between tumor and normal tissues, which suggest stable miRNA maturation and processing process. The relative stable isomiR expression patterns may contribute to regulatory networks. RT-qPCR results show consistent results with reported results and bioinformatics analysis of public database in BC and normal tissues (Figs. 1 and 2). These miRNAs have important roles in regulatory networks by regulating multiple target mRNAs. Functional enrichment analysis shows that they have important roles in some basic biological processes and some human cancers, which implies the important Table 3 GO analysis of target mRNAs of miRNAs in the study. GO enrichment
GO term
Biological process
GO:0006355 regulation of transcription, DNA-dependent GO:0006350 transcription GO:0007165 signal transduction GO:0007275 development GO:0006811 ion transport GO:0019941 modification-dependent protein catabolism GO:0015031 protein transport GO:0006468 protein amino acid phosphorylation GO:0007155 cell adhesion GO:0008150 biological_process GO:0005634 nucleus GO:0005737 cytoplasm GO:0016020 membrane GO:0016021 integral to membrane GO:0005886 plasma membrane GO:0005622 intracellular GO:0005794 Golgi apparatus GO:0005829 cytosol GO:0005576 extracellular region GO:0005783 endoplasmic reticulum GO:0005515 protein binding GO:0046872 metal ion binding GO:0008270 zinc ion binding GO:0000166 nucleotide binding GO:0003700 transcription factor activity GO:0005524 ATP binding GO:0003677 DNA binding GO:0016740 transferase activity GO:0005509 calcium ion binding GO:0016787 hydrolase activity
Cellular component
Molecular function
Count P-value 82
6.76E−81
67 41 30 20 19
1.05E−57 6.01E−22 2.22E−17 1.60E−18 2.27E−19
19 17
7.75E−17 3.33E−15
17 15 176 146 131 111 74 64 36 33 33 28 183 78 77 58 40 39 39 35 29 27
2.14E−14 0.9751598 1.49E−177 2.76E−114 4.40E−95 7.70E−86 2.36E−56 8.69E−19 3.48E−39 4.81E−33 2.77E−22 7.47E−27 1.18E−159 3.30E−57 2.24E−74 2.56E−52 3.65E−43 6.16E−36 5.45E−27 1.54E−27 6.14E−28 1.43E−15
roles of these miRNAs. Indeed, some specific miRNAs have been widely concerned and studied as a potential biomarker to diagnose disease, and even as a potential target for treatment. Our study has shown their expression and function in BC, and further study should be performed based on the larger samples, especially using miRNAs in serum. Simultaneously, miRNA study should also be performed at the isomiR level, although most isomiRs have the same 5′ ends and seed sequences with the canonical miRNA sequences. The stable isomiR expression can be detected between different samples, but diverse expression patterns can be detected based on the specific isomiR sequence (Fig. 1). The study at the isomiR level is quite necessary; especially if it may have versatile biological roles, such as influencing the miRNA stability. Collectively, based on several selected crucial miRNAs in BC, a series of isomiR sequences that have various sequences, length distributions, 5′ and 3′ ends, and expression levels can be detected. The canonical miRNA sequence is only a specific sequence in multiple isomiRs. Consistent results can be detected among literatures, public database and experimental validation, and these findings suggest the crucial biological roles of these abnormally expressed miRNAs. The study provides more insights in miRNAs, especially at the isomiR levels. Conflict of interests
Top ten in GO enrichment (biological process, cellular component, molecular function).
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