Literature DB >> 26124927

Systematic enrichment analysis of microRNA expression profiling studies in endometriosis.

Shiyang Wei1, Hong Xu1, Yan Kuang1.   

Abstract

OBJECTIVES: The purpose of this study was to conduct a meta-analysis on human microRNAs (miRNAs) expression data of endometriosis tissue profiles versus those of normal controls and to identify novel putative diagnostic markers.
MATERIALS AND METHODS: PubMed, Embase, Web of Science, Ovid Medline were used to search for endometriosis miRNA expression profiling studies of endometriosis. The miRNAs expression data were extracted, and study quality of each article was assessed. The frequently reported miRNAs with consistent regulation were screened out by a meta-profiling algorithm. The putative targets of consistently expressed miRNAs were predicted by using four target prediction tools (TargetScan, PicTar, miRanda, miRDB), and gene ontology pathway enrichment analysis (KEGG and Panther pathways) of the miRNA targets were carried out with GeneCodis web tool.
RESULTS: A total of 194 related literatures were retrieved in four databases. One hundred and thirty four differentially expressed miRNAs were found in the 12 microRNA expression profiling studies that compared endometriosis tissues with normal tissues, with 28 miRNAs reported in at least two studies, and 9882 candidate genes retrieved for 13 consistently expressed miRNAs. Kyoto encyclopedia of genes and genomes (KEGG) and Panther pathways enrichment analysis showed that endometriosis related differently expressed miRNA targets were mainly enriched in cancer, endocytosis, Wnt signalling pathway, and angiogenesis. It showed that these differently expressed miRNAs and gene are potential biomarkers of endometriosis.
CONCLUSION: miRNAs appear to be potent regulators of gene expression in endometriosis and its associated reproductive disorders, raising the prospect of using miRNAs as biomarkers and therapeutic agent in endometriosis.

Entities:  

Keywords:  Endometriosis; MicroRNAs; Pathway analysis; Profiling; Target prediction

Year:  2015        PMID: 26124927      PMCID: PMC4475649     

Source DB:  PubMed          Journal:  Iran J Basic Med Sci        ISSN: 2008-3866            Impact factor:   2.699


Introduction

MicroRNAs (miRNAs), a class of short noncoding RNA molecules, are proposed as promising biomarkers for early cancer detection and accurate prognosis, as well as targets for efficient treatment. Some miRNAs are post-transcriptional regulators of gene expression and implicated in central biological processes such as cell proliferation, differentiation and apoptosis (1, 2). Endometriosis is a common disease of reproductive-age women, which has complex pathogenesis. The lesions are extensive, highly invasive and recu-rrent, presenting malignant clinical behavior (3, 4). With the development of antisense technology and gene therapy, miRNA is expected to become a new strategy in endometriosis diagnosis and treatment (5, 6). It has been proved presently that miRNAs reside widely in eukaryotes, and are the largest gene family, participating and regulating various important life processes including cell differentiation, prolife-ration and apoptosis (7). As a method and result of the epigenetic modifications, latest research indicates that miRNA may play important role in the occurrence, development and prognosis of endometriosis, thus providing novel approach for the diagnosis and therapy of endometriosis. MiRNAs are key regulatory elements that control many genes expression and play crucial roles in many biological processes (8). Meta-analysis of mass miRNA expression profiling may uncover potential regulatory mechanisms by which microRNAs result in endometriosis.

Materials and Methods

Search strategies and study selection

PubMed (http://www.ncbi.nlm.nih.gov/pubmed), Embase (http://www.elsevier.com/online-tools/-embase), Web of Science (http://thomsonreuters.com/thomson-reuters-web-of-science/), Ovid Med-line (http://gateway.ovid.com) were used to search for endometriosis miRNA expression profiling studies published from January 2003 to October 2014 (last accessed on 20 October 2014), by means of the key words: endometriosis AND microRNA. Eligible studies had to meet the following criteria: (a) they were miRNA expression profiling studies in endometriosis patients; (b) they used tissue samples obtained from surgically resected endometriosis and corresponding eutopic or normal tissues for comparison; (c) use of miRNA microarray methods; (d) publishing a cut-off criteria of differentially expressed miRNAs. Therefore, the miRNA profiling studies using the serum samples of endometriosis patients or endometriosis cells in vitro were excluded. Review articles of miRNA expression profiles in endometriosis were also excluded. As repeated efforts can improve reliability and reduce error, valuable candidate miRNAs in this paper are defined as those validated and consistently reported by at least two studies.

Data abstraction

Two investigators (SW and YK) independently evaluated and extracted the data with the standard protocol and with all the discrepancies resolved by a third investigator (HX). From the full text and corresponding supplement information, the following eligibility items were collected and recorded for each study: author, journal and year of publication, location of study, selection and characteristics of recruited endometriosis patients, platform of miRNA expression profiling, author defined cut-off criteria of statistically differentially expressed miRNAs and the list of up- and down-regulated miRNA features, and their corresponding fold change. Each included studies comparing miRNA expression between surgically resected endometriosis tissues and eutopic endometrium or normal tissues provided a list of differentially expressed miRNAs.

MiRNA target prediction and pathway enrichment analysis

Consensus targets were defined as genes predicted by at least two algorithms of four target prediction tools, including TargetScan, PicTar, miRanda, and miRDB. Although all three of these articles described the expression profile of miRNAs in endometriosis, they did not systematically predict the biological process and pathway of the identified miRNAs. Therefore, we used GeneCodis web tool (http://genecodis.dacya.ucm.es/)(9, 10) to predict the biological process (GO process) and to perform pathway enrichment analysis (KEGG and Panther pathways) of all miRNAs that were identified as consistently expressed miRNAs in the eligible references.

Results

Selection and overview of the datasets

A total of 194 related literatures were indexed in PubMed, Embase, Web of Science and Ovid database. According to the inclusion criteria and identification of duplicate publication, only 12 publications seemed to meet all of the inclusion criteria and none of the exclusion criteria (Figure 1). The characteristics of these studies are listed in Table 1 in chronological order of the published time (Table 1).
Figure 1

A flow diagram of the literature search and study selection used in this study

Table 1

Twelve microarray-based human endometriosis miRNA expression profiling studies

First author (reference)YearRegionAssay typeNumber of samples*Cut-off criteriaUp-regulated miRNAsDown-regulated miRNAs
Pan Q (2)2007USAMirVana RNA isolation and enrichment kits4 pairs+4 NP<0.054817
Toloubeydokhti T (11)2008USATaqMan MicroRNA Array5 pairs+5 N+4 E5 pairs + 5 N+4 E12
Ohlsson Teague EM (12)2009AustraliaqRT-PCR7 pairsP<0.05 FC>1.5148
Filigheddu N (8)2010ItalyTaqMan MicroRNA Array y13 pairsP<0.01 FC>22723
Ramon’ LA (13)2011SpainTaqMan assay58 pairs+38 NP<0.0533
Hawkins SM (14)2011USATaqMan assay9 N and 10 EP<0.01 FC>1.51012
Petracco R (15)2011USAqRT-PCR50 N+32 EP<0.0520
Dai L (16)2012ChinaqRT-PCR12 pairs+12 NP<0.0110
Liu S (17)2012ChinaTaqMan MicroRNA Array31 pairs+27 NP<0.0501
Lin SC (18)2012ChinaqRT-PCR10 pairs+37 N+17 EP<0.0510
Shen L (19)2013ChinaqRT-PCR23 pairs+15 NP<0.0502
Laudanski P (20)2013PolandTaqMan MicroRNA Array21E+25NP<0.05 FC>2213
A flow diagram of the literature search and study selection used in this study Twelve microarray-based human endometriosis miRNA expression profiling studies

Determination of the consistently reported miRNAs

A total of 134 differentially expressed miRNAs were obtained in the 12 miRNAs expression profiling studies that compared endometriosis tissues with normal tissues, with 28 miRNAs reported in at least two studies, including 4 consistently reported up-regulated miRNAs(mir-202, mir-365, mir-1 and mir-150), 9 consistently reported down-regulated miRNAs (mir-23b, mir-200a, mir-200b, mir-200c,mir- 15b, mir-106b, mir-196b, mir-141, mir-375) (Table 2). And 15 inconsistently reported direction miRNA (Table 3).
Table 2

Consistently reported miRNAs (n = 13) in profiling studies (endometriosis tissues versus eutopic tissues or normal tissues)

Direction of expressionmiRNA nameNumber of studies with same directionTotal number of tissue samplesP-value
mir-202232<0.001
mir-365220<0.05
mir-1220<0.05
mir-150220<0.001
mir-23b340<0.001
mir-200b339<0.05
mir-200a339<0.05
mir-200c232<0.05
mir-141226<0.05
mir-375232≤0.01
mir-106b234<0.05
mir-196b220≤0.05
mir-15b264<0.05
Table 3

Inconsistently reported miRNAs (n=15) in profiling studies (endometriosis tissues versus normal tissues)

Direction of expressionmiRNA nameNumber of studies with same directionTotal number of tissue samplesP-value
mir-100339≤0.01
mir-10018<0.05
mir-17-5p19<0.05
mir-17-5p379<0.05
mir-29c339<0.01
mir-29c18<0.05
mir-20a149<0.05
mir-20a378≤0.05
mir-126220<0.05
mir-126239<0.001
mir-145220<0.05
mir-145229<0.05
mir-125a265<0.001
mir-125a18<0.05
mir-99a220<0.001
mir-99a18<0.05
mir-143220<0.001
mir-14318<0.05
mir-23a190.006
mir-23a2310.006
mir-222141<0.001
mir-222229<0.05
mir-199a113≤0.01
mir-199a220<0.05
mir-125b131<0.05
mir-125b18<0.05
mir-21158<0.01
mir-2118<0.01
mir-221113≤0.01
mir-22118<0.05
Consistently reported miRNAs (n = 13) in profiling studies (endometriosis tissues versus eutopic tissues or normal tissues) Inconsistently reported miRNAs (n=15) in profiling studies (endometriosis tissues versus normal tissues)

Pathway analysis of miRNA targets

By using four target prediction tools (TargetScan, PicTar, miRanda, and miRDB), 9882 candidate genes were predicted for 13 inconsistently reported miRNAs. And all the predicted candidate genes were analyzed by pathways enriched analysis. KEGG and Panther pathways enrichment analysis showed that 9882 endometriosis-related miRNA targets were mainly cancer-related pathways, endocytosis, Wnt signalling pathway, and angiogenesis (Table 4).
Table 4

Top ten of the significant GO processes, KEGG pathways and Panther pathways enriched with miRNA targets involved in endometriosis

GO processesProcess FDR Target number
GO:0006355Regulation of transcription, DNA-dependent5.55032e-182963
GO:0007165signal transduction2.72922e-125694
GO:0007275Multicellular organismal development7.66 e -100557
GO:0045944Positive regulation transcription of from RNA polymerase II promoter4.43532e-86378
GO:0007399Nervous system development3.20348e-70280
GO:0007155Cell adhesion8. 37777e-68342
GO:0045893Positive regulation of transcription, DNA dependent3.78756e -66301
GO:0007268Transmission synaptic6.22556e-57250
GO:0055085Transmembrane transport9. 4472e-56353
GO:0000122Negative regulation transcription of from RNA polymerase II promoter1. 0109e-55263
Top ten of the significant GO processes, KEGG pathways and Panther pathways enriched with miRNA targets involved in endometriosis

Discussion

In this paper, we adopt a meta-analysis to screen endometriosis-related miRNAs from miRNA expression profile data of independent profiling studies, and to obtain conservative target predictions for all miRNAs lists of interest using four up-to-date prediction algorithms (TargetScan, PicTar, PicTar, miRanda and miRDB). And pathway enrichment analysis using different target prediction algorithms were concordant for all of the consistently expressed miRNAs. We found out a meta-signature of four up-regulated and nine down-regulated miRNAs. Although the selected method for miRNA expression meta-analysis relates to analysis of the primary expression parameters, such method was often not possible due to the unavailability of the primary data. A great number of miRNAs known in the present and different technical platforms adopted in certain study make the appropriate synthesis of primary data very complex. Moreover, the relatively small sample sizes of microarray data may have resulted in inconformity of biological consequences. A meta-analysis method could eliminate these disadvantages and directly compare original data extracted from different technical platforms (21). All the data from the 12 published studies consisted of more than 317 endometriosis and eutopic or normal tissue samples were analyzed directly, and a series of early researches (2, 11, 12, 14) were analyzed with less than ten specimens, which may have unreliable results. Ohlsson Teague et al (22) assessed miRNA expression by microarray analysis in seven paired ectopic and eutopic endometrial tissues and identified 14 up-regulated and eight down-regulated miRNAs in endometriosis tissues. Pan et al (2) identified 48 differently expressed miRNAs in a microarray analysis of endometrium of women with and without endometriosis, and mir-23b down-regulation. Compared with nonendometriosis control endometrium, mir-200b expression level decreased obviously in endometriosis (14). Angiogenesis is the basis of the occurrence and development in endometriosis. Just as tumor, implantation metastasis of endometriosis is based on new neurovascular formation and proliferation, invasion of extracellular matrix, and lesion formation. Recent studies revealed that miRNA may involve in regulation of angiogenesis, and some miRNAs have the distinction of anti-vasoformation, such as mir-15b, mir-16, mir-221, and mir-222. Interestingly, the results suggest that mir-200 family members (mir-200a, mir-200b, mir-200c, mir-141, which were known to be cancer-related miRNAs down-regulated, while expression of some others (mir-21 (2, 13), mir-199a (2, 13, 16)) were inconsistently reported in the selected studies. Some miRNAs which have been specifically investigated in several studies (such as miR-17-5p, mir-23a,mir-23b (19, 23); mir-20a(18); mir-126(17); mir-135a, mir-135b (15)) were found among both up-regulated and down-regulated. All mirRNA-200 family members (miR-200a, miR-200b, miR-200c, miR-141, miR-429) were found down-regulated, and reached the statistical significance in our analysis, of course, mir-429 was only reported in just one study. Currently, our analysis is limited to comparison of endometriosis and eutopic or normal control tissue. The miR-200 family has been reported to be a fundamental regulator of epithelial-mesenchymal transition, thus enhancing their roles in cancer progression. As a founding member in miR-200 family, miR-200b attracts much focus in carcinogenesis in recent years. Down-regulation of miR-200b has been detected in several malignancies (24-26) and in endometriosis (27). The set of miRNAs with significantly decreased expression levels include all members of the miR-200 family known to be involved in the epithelial to mesenchymal transition process (28). From the clinical viewpoint, it would be meaningful if the discovery of targets correlated with patient diagnosis, therapy and prognosis. These meta-signature miRNAs and gene-to-behavior pathway affected by them are potential candidates as diagnostic and therapeutic agents in endometriosis. Our analysis also concentrated on the challenges connected with the development of miRNA-based tests and emphasizes to the importance of strict inspection of the results before conducting clinical trials. Perez-Iratxeta et al (29) applied a combination of data mining and gene ontology to develop a scoring system for discovering disease-associated genes based on text descriptions of genetically inherited diseases and functional annotations of genes. The scoring showed that the chance of validating potential gene is high for some diseases. Mohammadi et al (30) used microarray data mining and gene ontology to identify disease-causing genes, and predicted marker genes with high accuracy. It indicates that the above method of comparing data is derived from different organisms in studies of disease and human health. Here we showed some familiar and novel pathways for endometriosis, including the pathways in cancer, endocytosis and axon guidance. New visions were also provided into Wnt signaling, angiogenesis, and integrin signaling pathway. These pathways that regulate stem cell transformation indicate the role of miRNAs in endometriosis cell deregulation and development. Therefore, some of these miRNAs may be selected as diagnostic index or acted as therapeutic agent for endometriosis. MiRNAs appear to be potent regulators of gene expression in endometriosis and its associated reproductive disorders, raising the prospect of using miRNAs as biomarkers and therapeutic agent in endometriosis. It should be emphasized that there were some limitations in our analysis. In this study, the inclusion of researches was based on different assay types. The total number of tissues from available data was relatively small, and tissues included endometriosis tissue, eutopic endometrium, and normal tissue. We extracted data retrieved from different studies, and. published large prospective researches were unattainable for endometriosis. In addition, there were only 12 eligible studies in our meta-analysis, which may also lead to a bias in the results.

Conclusion

By systematic enrichment analysis, we found that these differently expressed miRNAs and gene are potential biomarkers of endometriosis. Our analysis also highlights the challenges connected with the development of miRNA-based tests and emphasizes the need for rigorous evaluation of the results before proceeding to clinical trials.
  30 in total

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4.  c-Myc-regulated microRNAs modulate E2F1 expression.

Authors:  Kathryn A O'Donnell; Erik A Wentzel; Karen I Zeller; Chi V Dang; Joshua T Mendell
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5.  Functional microRNA involved in endometriosis.

Authors:  Shannon M Hawkins; Chad J Creighton; Derek Y Han; Azam Zariff; Matthew L Anderson; Preethi H Gunaratne; Martin M Matzuk
Journal:  Mol Endocrinol       Date:  2011-03-24

6.  Identification of disease-causing genes using microarray data mining and Gene Ontology.

Authors:  Azadeh Mohammadi; Mohammad H Saraee; Mansoor Salehi
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7.  Epithelial-mesenchymal transition-related microRNA-200s regulate molecular targets and pathways in renal cell carcinoma.

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Journal:  J Hum Genet       Date:  2013-05-02       Impact factor: 3.172

8.  GeneCodis: interpreting gene lists through enrichment analysis and integration of diverse biological information.

Authors:  Ruben Nogales-Cadenas; Pedro Carmona-Saez; Miguel Vazquez; Cesar Vicente; Xiaoyuan Yang; Francisco Tirado; Jose María Carazo; Alberto Pascual-Montano
Journal:  Nucleic Acids Res       Date:  2009-05-22       Impact factor: 16.971

9.  MicroRNA-200 family modulation in distinct breast cancer phenotypes.

Authors:  María Ángeles Castilla; Juan Díaz-Martín; David Sarrió; Laura Romero-Pérez; María Ángeles López-García; Begoña Vieites; Michele Biscuola; Susana Ramiro-Fuentes; Clare M Isacke; José Palacios
Journal:  PLoS One       Date:  2012-10-24       Impact factor: 3.240

10.  MicroRNAs expression profiling of eutopic proliferative endometrium in women with ovarian endometriosis.

Authors:  Piotr Laudanski; Radoslaw Charkiewicz; Mariusz Kuzmicki; Jacek Szamatowicz; Alicja Charkiewicz; Jacek Niklinski
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3.  A Multi-Step miRNA-mRNA Regulatory Network Construction Approach Identifies Gene Signatures Associated with Endometrioid Endometrial Carcinoma.

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4.  MicroRNA expression analysis in endometriotic serum treated mesenchymal stem cells.

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