BioMed Research International

BioMed Research International / 2016 / Article
Special Issue

Oral Biology, Oral Pathology, and Oral Treatments

View this Special Issue

Review Article | Open Access

Volume 2016 |Article ID 1027525 | 14 pages | https://doi.org/10.1155/2016/1027525

MicroRNAs as Salivary Markers for Periodontal Diseases: A New Diagnostic Approach?

Academic Editor: Kenji Yoshida
Received19 Jan 2016
Accepted20 Mar 2016
Published27 Jun 2016

Abstract

The aim of this review is to discuss current findings regarding the roles of miRNAs in periodontal diseases and the potential use of saliva as a diagnostic medium for corresponding miRNA investigations. For periodontal disease, investigations have been restricted to tissue samples and five miRNAs, that is, miR-142-3p, miR-146a, miR-155, miR-203, and miR-223, were repeatedly validated in vivo and in vitro by different validation methods. Particularly noticeable are the small sample sizes, different internal controls, and different case definitions of periodontitis in in vivo studies. Beside of that, the validated miRNAs are associated with inflammation and therefore with various diseases. Furthermore, several studies successfully explored the use of salivary miRNA species for the diagnosis of oral cancer. Different cancer types were investigated and heterogeneous methodology was used; moreover, no overlap of results was found. In conclusion, five miRNAs have consistently been reported for periodontitis; however, their disease specificity, detectability, and expression in saliva and their importance as noninvasive markers are questionable. In principle, a salivary miRNA diagnostic method seems feasible. However, standardized criteria and protocols for preanalytics, measurements, and analysis should be established to obtain comparable results across different studies.

1. Introduction

MicroRNAs (miRNAs) are endogenous ~22 nt RNAs that play important regulatory roles in animals and plants by targeting mRNAs for cleavage or translational repression [1]. Many multifarious investigations regarding miRNAs have demonstrated their essential roles in physiological and pathological processes in the immune response [2]. Additionally, miRNAs likely contribute to development and progression of systemic diseases, such as cancer [3] and vascular disease [4]. Consequently, there is considerable interest in use of miRNAs as not only diagnostic markers but also potential therapeutic targets for various diseases [5]. In particular, the roles of miRNAs in oral cancer and precancer have been investigated. MiRNA expression appears to differ between healthy tissue and squamous cell carcinoma tissues of the oral cavity, which is discussed in an existing review [6]. Furthermore, some investigations have linked precancerous lesions and their risk of becoming malignant to changes in miRNA expression [7].

Furthermore, miRNAs are associated with bacterial infections [8] and, thus, are most likely associated with infectious diseases of oral cavity, for example, dental caries, endodontic infections, and periodontitis. Kim et al. (2015), however, already give an overview of current findings regarding dental disease, including periodontal disease and oral cancer. Kim et al. (2015) also mentioned limitations of current diagnostic and potential benefit of salivary miRNA diagnostic [9]. This is the reason to discuss the roles of miRNAs in periodontal diseases. As of now, only a few in vitro and in vivo investigations regarding these roles are available. A recent review article demonstrated potential roles of miRNAs during periodontal inflammation, showing the considerable role of them in periodontitis [10]. Thereby, different roles and mechanisms are shown and a very comprehensive overview on molecular pathways is given; however, methodology was only discussed between selected studies.

As mentioned above, an interesting approach is the analysis of miRNA species in saliva. High quality miRNAs were shown to be detectable in saliva [11], and the possibility of their usage in oral cancer detection appears to have a high potential for future diagnostics [12]. This noninvasive approach could be relevant for further diseases of the oral cavity. Nevertheless, the potential usage of miRNA as salivary markers for periodontal diseases was already not discussed yet. As shown for oral cancer, using miRNA for noninvasive diagnostics seems feasible [12] and could therefore serve as a salivary marker for periodontitis. The potential is high, so maybe recent indispensable invasive diagnostics or X-ray could become avoided by salivary miRNA diagnostic in the future and an early diagnosis might help to prevent bone and, in conclusion, tooth loss.

Nevertheless, despite of the huge potential, many different results are available, both for salivary oral cancer diagnostics and for analysis of periodontal tissue. Accordingly, it is questionable if the reasons are methodological differences between the studies or maybe if the usage of miRNAs in general is unsuitable.

Therefore, this review article shows current results of in vitro and in vivo studies regarding periodontal diseases as well as results of selected current studies dealing with salivary miRNAs for oral cancer detection. The aim was to detect promising future perspectives, but also current challenges regarding this issue. In particular, methodological aspects are focused to detect potential limitations of miRNAs as noninvasive markers for periodontitis.

2. Methods

2.1. Search Strategy

Our literature research was performed using the online database PubMed (http://www.ncbi.nlm.nih.gov/pubmed). To obtain a broad overview of the available theme-specific publications, we used different keywords for our search. We used “miRNA AND periodontitis” as keywords to obtain results for periodontal diseases. We used “miRNA AND saliva AND oral disease” and “miRNA AND saliva AND cancer” as keywords to obtain relevant articles for noninvasive possibilities, that is, the use of saliva to investigate miRNAs in diseases of the oral cavity. Then, the reference lists of relevant articles were searched for further results. To interpret the results, relevant publications were searched and analyzed critically. Neither a meta-analysis nor other statistical comparisons of existing data were performed.

2.2. Selection Criteria

Only current full-length articles in English language were included. The results were verified for their relevance. The following selection criteria were defined: miRNA investigations for in vitro and in vivo studies examining periodontal disease. Additionally, in vivo human investigations regarding salivary miRNA analysis in oral cancer and precancer were included.

2.3. Selection Process

Following the literature search, all references were limited to relevant publications. In vivo periodontal disease investigations that did not address periodontal tissue were excluded. Salivary diagnostic studies that did not explicitly concentrate on miRNAs were excluded, and only investigations for oral cancer and precancer were included.

3. Results

3.1. Periodontal Diseases
3.1.1. In Vitro

Eight in vitro studies, which detected different miRNAs, were included for periodontal disease (Table 1). Nahid et al. (2011) examined the expression of cytokines associated with inflammation and differences in expression of cytokines and miRNA during infection with live and heat-killed bacteria in THP-1 monocytes. They demonstrated that expression of miR-146a is associated with infections caused by periodontal pathogenic bacteria in vitro [13]. Another study indicated that miR-146a is significantly overexpressed in THP-1 cells after stimulation with LPS from P.g. [14]. Furthermore, miR-146a was shown to be a negative regulator of TLR-NFκB pathway in human periodontal ligament cells after P. gingivalis LPS stimulation, therefore being involved in inflammatory response [15]. Moreover, expression of miR-146a and miR-146b-5p in human gingival fibroblasts after stimulation with P.g. LPS was also investigated in a study by Xie et al. (2013). They demonstrated that expression of these miRNAs significantly increased upon LPS stimulation and concluded that miR-146 could work as a negative regulator of inflammation in periodontal disease [16]. Differential expression of miR-146a and miR-155 in dental pulp and in gingival and periodontal fibroblasts after stimulation with LPS from Escherichia coli was also reported. The increased expression of miR-146a was the highest in gingival fibroblasts and decreased expression of miR-155 was only significant in gingival fibroblasts [17]. Naqvi et al. (2014) showed different expressions of miR-146a. In this in vitro study THP-1 macrophages that were stimulated with LPS from Aggregatibacter actinomycetemcomitans, P.g., and also P.g. grown on cigarette smoke extract were examined. The different LPS caused both some identical and also varied expressions of miRNAs in human macrophages. Moreover, LPS from P.g. grown on cigarette smoke extract compared to LPS from unaffected P.g. caused differential miRNA expression, particularly that of miR-29b in human macrophages [18].


Author and yearObject of investigationRNA extraction methodDetection method for miRNA profileValidation of specific miRNAsNumber of study participantsInternal controlStatistical analysisInvestigated and/or deregulated miRNAs

In vitro human

Moffatt and Lamont 2011 [20]Gingiva epithelial cellsTRIzol (Invitrogen), miRNeasy kit (Qiagen)Microarray (LC Sciences)qRT-PCR TaqMan (Applied Biosystems)RNU-48ANOVA, -testmiR-203

Nahid et al. 2011 [13]Human THP-1 monocytesmirVana miRNA isolation kit (Ambion)TaqMan microRNA assay (Applied Biosystems)RNU44One-way analysis of variance followed by the two-sided, unpaired Student’s -testmiR-146a
miR-155
miR-132

Honda et al. 2012 [14]THP-1 cells and THP-1-derived macrophagesTRIzol reagent (Invitrogen)Agilent human miRNA microarrays (Release 12.0) (Agilent technologies)TaqMan microRNA Assay (Applied Biosystems)RNU44Unpaired -test, ANOVA-Williams testmiR-146a
miR-155

Xie et al. 2013 [16] Human gingival fibroblastsTRIzol reagent (Invitrogen)miRNA microarray analyses (Kangchen Bio-Tech)qRT-PCR analysis (SYBR Green qPCR Master Mix PA-112, SABiosciences, Qiagen)U6 small nuclear RNAStudent’s -testmiR-146a
miR-146b-5p

Sipert et al. 2014 [17] Human fibroblasts from dental pulps, gingivae, and periodontal ligamentsTRIzol (Invitrogen)NCode miRNA rapid labeling system (Cat. # MIRLSRPD-20) (Invitrogen) Ncode Multi-Species miRNA microarray kit V2, (Invitrogen)Taqman miRNA assays, (Applied Biosystems)U6BTwo-way ANOVA followed by Bonferroni post hoc testmiR-146a
miR-155

Naqvi et al. 2014 [18]Human THP-1-differentiated macrophagesmiRNeasy kit (Qiagen)NanoString nCounter miRNA assay (NanoString Technologies)Quantitative real-time PCR EvaGreen Master Mix (Biotium)RNU6BStudent’s -test (two-tailed)miR-29b
miR-32
miR-146a
miR-891

Ouhara et al. 2014 [19]Simian virus 40 antigen immortalized gingival epithelial cell line, OBA-9mirVana miRNA Isolation Kit (Applied Biosystem)miRCURY LNA microRNA Array, v.16.0 (Exiqo)TaqMan MicroRNA Assays System (Applied Biosystems)RNU48Student’s -test, Tukey honestly significant differencemiR-584

Jiang et al. 2015 [15]Human periodontal ligament cellsTRIzol reagent (Invitrogen)Quantitative RT-PCR analysis (RT SYBR® Green qPCR Master Mixes PA-112, SABiosciences, Qiagen)U6 small nuclear RNAANOVA and Student-Newman-Keuls testmiR-146a

In vivo animal

Nahid et al. 2011 [13]Maxillae and spleens from ApoE−/− micemirVana miRNA isolation kit (Ambion)TaqMan microRNA assay (Applied Biosystems)snoRNU202One-way analysis of variance followed by the two-sided, unpaired Student’s -testmiR-146a
miR-155
miR-132

In vivo human

Lee et al. 2011 [21]Gingival tissuemirVana miRNA Isolation kit (Ambion)RT2 miRNA PCR array system (SABiosciences)TaqMan miRNA assays (Applied Biosystems)n.i.RNU44Student’s -testmiR-181b
miR-19b
miR-23a
miR-30a
miR-let7a
miR-301a

Xie et al. 2011 [22]Gingival tissueTRIzol reagent (Invitrogen)miRNA microarray (Kangchen Bio-Tech)Quantitative RT-PCR analysis (RT SYBR Green qPCR Master Mixes PA-112, SABiosciences, Qiagen)10 periodontitis patients
10 healthy subjects
U6 small nuclear RNAUnpaired Student’s -testmiR-126
miR-20a
miR-142-3p
miR-19a
let-7f
miR-203
miR-17
miR-223
miR-146b
miR-146a
miR-155
miR-205

Stoecklin-Wasmer et al. 2012 [24]gingival tissueTRIzol (Invitrogen)
RNeasy (Qiagen,)
MicroarrayqRT-PCR198 gingival tissue samples, 158 diseased and 40 healthy samples from 86 patients with periodontitisn.i.R (the R Development Core Team, 2005) and bioconductor statistical frameworksmiR-451
miR-223
miR-486-5p
miR-1246
miR-1260
miR-141

Perri et al. 2012 [26]Gingival tissueTissueLyser LT and miRNeasy Mini Kit (Qiagen)Quantitative microRNA PCR array
miRNA PCR Array (SABiosciences)
10 nonobese patients and 10 obese patients each group with 5 periodontally healthy sites and 5 chronic periodontitis sitesSNORD48 and RNU6-2ANOVA and nonpaired Student’s -testmiR-142-3p
miR-15a
miR-30e
miR-30d
miR-22
miR-130a
miR-106b
miR-103
miR-185
miR-210
miR-18a

Ogata et al. 2014 [23] Gingival tissuemiRNeasy Mini Kit (Qiagen)Human miRNA microarray 8 × 15K kit (Agilent Technologies)Real-time PCR SYBR Advantage qPCR Premix (Clontec)3 chronic periodontitis patients and 3 edentulous residual ridgesU6One-way ANOVAmiR-150
miR-200b
miR-223
miR-144
miR-379
miR-222

Kalea et al. 2015 [27]Gingival tissuemirVana miRNA Isolation Kit (Ambion)Affymetrix GeneChip miRNA 3.0 arrays (Affymetrix)TaqMan MicroRNA expression assays (Applied Biosystems)36 eligible individualsU6snoRNA and RNU6BPartek 6.6 and 1-way analysis of variance, R-statistical environmentmiR-4721
miR-557
miR-196a
miR-323a-3p
miR-200b-5p
miR-188-5p

Motedayyen et al. 2015 [25]Gingival tissuemirVana miRNA isolation kit (Ambion)Real-time PCR (TaqMan Universal Master Mix II, no UNG, and hsa-miRNA146a kits, Applied Biosystems)10 healthy controls, 20 chronic periodontitis patientsn.i.Student’s -test or Mann-Whitney test; Pearson test or Spearman testmiR-146a

RNA extraction and isolation methods are listed. The proof of quality and quantity and quality assurance are shown as important quality criteria to draw conclusions regarding the reproducibility and standardization of the investigations. Furthermore, methods for miRNA profiling and miRNA validation are listed. In addition, the number of study participants is shown to draw conclusions regarding the validity of the results. n.i.: no information, only miRNAs which were validated by RT-PCR were considered, and Stoecklin-Wasmer et al. refer to an earlier report by Demmer et al. 2008 [62]. MiRNAs which were reported in more than one study are highlighted in bold type.

Results reported in other two studies were more heterogenous: Ouhara et al. (2014) demonstrated upregulated miR-584 in human gingival epithelial cells after stimulation with P.g. [19]. Furthermore, Moffat and Lamont (2011) focused on miR-203 expression in gingival epithelial cells stimulated with P.g. In this study, 14 miRNAs displayed significant changes in expression after exposure to P.g.; of these miRNAs, miR-203 was examined in detail and showed higher expression in tissues after P.g. stimulation [20].

3.1.2. In Vivo Animal

Nahid et al. (2011) investigated expression of miR-146a, miR-132, and miR-155 in spleens and maxillae of ApoE−/− mice after infection with periodontal pathogenic bacteria P.g., Treponema denticola and Tannerella forsythia. MiR-146a primarily showed a significant increase in both maxillae and spleens, while miR-132 and miR-155 showed only minor changes [13].

3.1.3. In Vivo Human

Seven in vivo studies investigating differential expression of miRNAs in human tissue samples were included (Table 1). In particular, Lee et al. (2011) compared the expression of inflammatory miRNAs in healthy and inflamed periodontal tissue. Microarray analysis indicated that expression of six miRNAs was upregulated more than eightfold and that expression of 22 miRNAs increased more than fourfold in periodontal disease tissue compared with healthy tissue. Of these miRNAs, six could be validated by qRT-PCR [21]. A similar investigation considered miRNA profiles of healthy and inflamed gingival tissues. Microarray analysis of healthy and inflamed gingival tissues indicated that expression of five miRNAs was upregulated more than fivefold, 85 miRNAs, twofold to fivefold. Moreover, expression of 34 miRNAs was downregulated twofold to fivefold in inflamed tissue. 12 miRNAs were validated by qRT-PCR [22]. A study of Japanese patients identified 17 upregulated and 22 downregulated miRNAs; six were selected for validation [23]. A further investigation also detected differential miRNA expression by microarray analysis, wherein 91 upregulated and 68 downregulated miRNAs were found. Six miRNAs were validated, and potential target genes were investigated [24]. Furthermore, Motedayyen et al. (2015) showed a positive relationship between miR-146a and clinical parameters in patients with chronic periodontitis [25]. Thus, many miRNAs with differential expression as detected by microarray analysis have not been validated by qRT-PCR; these miRNAs will not be discussed (Table 1).

Additionally, two studies investigated the roles of miRNAs in periodontal disease in association with systemic factors and disease; thus, differential expression of miRNAs between obese periodontitis patients and nonobese periodontitis patients was examined. However, different, nonoverlapping miRNAs were reported in each investigation [26, 27].

Notably, criteria for patient selection and for classification of healthy and diseased patients were similar across all studies. However, differences exist between investigations in defining periodontal health and periodontitis (Table 2). Additionally the number of study participants for in vivo investigations varied enormously between studies with ten patients or less for each group in most cases (Table 1). Likewise, methodological approach was similar across studies: microarray based technology was often used to screen and identify miRNAs with differential expression, and qRT-PCR was used for subsequent validation of top-hits. However, detailed methods were different; thus, for example, different miRNA isolation methods were used. Also differences in statistical analysis are conspicuous, especially internal controls that distinguish between the studies (Table 1).


Author and yearPDCALBOPRadiographic bone loss
HealthyPeriodontitisHealthyPeriodontitisHealthyPeriodontitisHealthyPeriodontitis

Stoecklin-Wasmer et al. 2012 [24]≤4 mm>4 mm≤2 mm≥3 mmnegativepositiven.i.n.i.
Xie et al. 2011 [22]<3 mm≥5 mm<1 mm≥3 mmn.i.NoYes
Lee et al. 2011 [21]≤3 mm>5 mmnone>3 mmn.i.NoYes
Perri et al. 2012 [26]≤4 mm>5 mmn.i.n.i.NegativePositiveNoYes
Ogata et al. 2014 [23]n.i.≥6 mmn.i.>6 mmn.i.Positiven.i.n.i.
Motedayyen et al. 2015 [25]<3 mmn.i.<3 mmn.i.n.i.n.i.Non.i.
Kalea et al. 2015 [27]n.i.>5 mmn.i.n.i.n.i.n.i.

PD: pocket depth; CAL: clinical attachment loss; BOP: bleeding on probing; n.i.: no information. GI > 1; BOP in whole gingiva < 10%, bone loss > 30%.
3.2. MiRNA Detection in Saliva as a Noninvasive Diagnostic Tool

Nine investigations were included that illustrate the potential of saliva as noninvasive diagnostic tool for miRNA analyzes. We focused on salivary miRNA species analysis as a diagnostic method for oral cancer and precancer detection, because no results of appropriate dental and periodontal disease investigations could be found. Six of included studies examined oral squamous cell carcinoma, one precancerous lesions, one esophageal cancer, and one tumor of parotid gland. Park et al. (2009) showed presence of miRNA species in whole saliva and in saliva supernatants and described differential expression of miR-125a and miR-200a between cases and controls. Besides that stability of exogenous (miR-124a) and endogenous (miR-191) miRNA in saliva was also examined in this study, and endogenous miRNA was shown to have higher stability than exogenous miRNA [28]. Another investigation found that miR-9, miR-191, and miR-134 appeared to be potential markers for noninvasive diagnosis of oral squamous cell carcinoma using saliva. Additionally, this study describes a reliable isolation method for miRNAs from even small volumes of saliva [29]. In a study by Hung et al. (2016) salivary miRNAs, specifically miR-31 and miR-21 were investigated in oral premalignant disorders, particularly showing miR-31 to be a sufficient marker for high risk disorders and malignant transformation [30]. Also Liu et al. (2012) examined miR-31, and its expression in saliva was compared with its expression in plasma; thereby, a correlation could be shown. These authors also observed a decrease in expression of miR-31 after surgical resection of primary tumor [31]. Similarly, Duz et al. (2016) reduced miR-139-5p expression in patients with tongue carcinoma and normalization after surgical treatment [32]. In a study investigating expression of salivary miRNAs in premalignant lesions of oral cavity, a correlation was found between deregulated miRNA expression in tissue and saliva, although miRNA concentrations in saliva were lower [33]. A further investigation compared expression of miRNA in saliva between patients with oral squamous cell carcinoma, patients with oral squamous cell carcinoma in remission, patients with oral lichen planus, and a healthy control group. In addition to differences in miRNA expression between the groups, miR-27b was significantly overexpressed in saliva of patients with oral squamous cell carcinoma. Furthermore, completely different profiles of miRNAs could be found in cancerous tissues compared to biological fluids [34]. Additionally, another study found miRNA-184 to have the potential to distinguish between OSCC and potentially malignant disorders [35].

In addition, altered miRNA expression in saliva was also verified for esophageal cancer [36] and parotid gland tumors [37]. Their methodologies are shown in Table 3. In principle, methods of measurement (microarray, qRT-PCR) are similar between the studies. Remarkable differences could be found regarding form of saliva, extraction methods, statistical analysis, and internal controls. The number of study participants was already higher than for periodontitis. However, heterogeneous groups sizes with partly seven or eight patients each group [33, 34] and partly 50 patients and more each group [28, 29] were investigated (Table 3).


Author and yearNumber of study participantsForm of salivamiRNA extraction methodDetection of miRNA profileValidationInternal controlStatistical analysisPotential marker for carcinoma

Park et al. 2009 [28]50 oral squamous cell carcinoma (OSCC) patients and 50 healthy matched control subjectsUnstimulated whole saliva and saliva supernatantmirVana miRNA Isolation Kit (Ambion)
DNA-free (Ambion)
RT-preamp-qPCR (Applied Biosystems)(i) RT-preamp-qPCR (Applied Biosystems)
(ii) Four-plex RT-preamp-qPCR for miR-142-3p, miR-200a, miR-125a, and miR-93.
U6 snRNAMann-Whitney testmiR-125a
miR-200a

Liu et al. 2012 [31]45 patients with OSCC and 10 patient with oral verrucous leukoplakia
24 healthy individuals
Unstimulated saliva supernatantmirVana PARIS Isolation kit (Ambion)
DNase digestion
TaqMan miRNA assay system (Applied Biosystems)TaqMan miRNA assay system (Applied Biosystems)miR-16Mann-Whitney test, Wilcoxon matched pairs test, and linear regression analysis, receiver-operating characteristics ROC analysismiR-31

Yang et al. 2013 [33]8 progressing LGD leukoplakias
7 nonprogressing LGD leukoplakias
7 healthy volunteers
Unstimulated salivaRNeasy Micro Kit (Qiagen)TaqMan® low density array (TLDA) qRT-PCR system (Applied Biosystems) were used for global miR expression analysis in tissue samplesTaqMan MicroRNA Assay (Applied Biosystems)RNU6Random variance -test, Benjamini-Hochberg false discovery rate (FDR) method, Mann-Whitney test, Student’s -tests (two-sided)miR-10b, miR-145, miR-99b, miR-708, miR-181c, miR-30e, miR-660, miR-197

Xie et al. 2013 [36]39 patients with esophageal cancer and 19 healthy controlsStimulated whole saliva and supernatantmirVana PARIS Kit (Ambion)7 whole saliva samples for EC group and 3 for healthy group for Agilent microarray 11.0 (Agilent Technologies)RT-qPCR SYBR Premix Ex Taq (TaKaRa)miR-16Mann-Whitney test or the Kruskall-Wallis test, test, receiver-operating characteristics ROC curves, Spearman’s correlation testmiR-10b, miR-144, miR-451 (in whole saliva)
miR-10b, miR-144, miR-21, miR-451 (in saliva supernatant)

Matse et al. 2013 [37]38 patients with malignant and 29 with benign parotid gland tumorsWhole saliva and supernatantmirVana Paris kit (Ambion)
DNase I (Qiagen)
TaqMan Human MicroRNA Cards (Applied Biosystems)
TaqMan MicroRNA assays (Applied Biosystems)
TaqMan microRNA assays (Applied Biosystems)U6 snRNAWilcoxon rank-sum test, ROC curveshsa-miR-374, hsa-miR-222, hsa-miR-15b, hsa-let-7g, hsa-miR-132, mmu-miR-140-5p

Momen-Heravi et al. 2014 [34]9 OSCC patients before treatment, 8 patients with OSCC in remission, 8 patients with OLP, and 9 healthy controlsUnstimulated whole salivaRNeasy kit (Qiagen)multiplexed NanoString nCounter
miRNA expression assay (NanoString Technologies)
TaqMan MicroRNA assay (Applied Biosystems)miRNA-1911-way analysis of variance, followed by a 2-tailed Mann-Whitney test or Student’s -test, ROC curves analysismiR-27b

Salazar et al. 2014 [29]5 HNSCC patients, 5 healthy controls for expression analysis
56 HNSCC patients, 56 healthy controls for validation
Unstimulated whole salivaQIAzol lysis reagent (Qiagen)
NucleoSpin miRNA kit (Macherey-Nagel)
miScript miRNA PCR arrays (Qiagen)RT-qPCR miScript SYBR green PCR master mix (Qiagen)SNORD96AMann Withney -test, ROC curves, Wilcoxon rank sum test, Bonferroni methodmiR-9, miR-134, miR-191

Zahran et al. 2015 [35]20 healthy controls, 40 potentially malignant disorders, 20 OSCC, 20 recurrent aphthous stomatitisUnstimulated saliva supernatantmiRNeasy serum/plasma extraction kit (Qiagen)RT-qPCR SYBR green PCR kit (Qiagen)SNORD68One-way ANOVA, -test, Dunnett -test, Scheffe’s multiple comparison, two-tailed testsmiR-21, miR-184, miR-145

Duz et al. 2016 [32]50 saliva samples from 25 TSCC patients (once prior to and once after surgical treatment)Unstimulated saliva supernatantmirVana PARIS kit (Ambion)8 samples (4 TSCC patients 4 healthy control) using Agilent 8 × 60K human V19 miRNA microarraysTaqMan MicroRNA assay (Applied Biosystems)RNU6bTwo-sided Student’s -test, Receiver operating characteristic (ROC) curves, 95% confidence interval (CI)miR-139-5p

Hung et al. 2016 [30]20 patients with oral potentially malignant disorders, 24 healthy individualsUnstimulated saliva supernatantmirVana PARIS isolation kit (Ambion)TaqMan microRNA assay (Applied Biosystems)miR-16Unpaired test, ROC curves, Kaplan-Meier method, log-rank test, Cox proportional hazard modelmiR-21
miR-31

RNA extraction and isolation methods are listed. The proof of quality and quantity and quality assurance are shown as important quality criteria to draw conclusions regarding the reproducibility and standardization of the investigations. Furthermore, methods for miRNA profiling and miRNA validation are listed. In addition, the number of study participants is provided to draw conclusions regarding the validity of the results. The form of saliva is also listed.

4. Discussion

Several studies investigating putative role of miRNAs in periodontal diseases have been performed; however, spectrum of miRNAs identified was substantially heterogeneous. Both in vitro and in vivo investigations were performed for periodontal disease, and five miRNAs, that is, miR-142-3p, miR-146a, miR-155, miR-203, and miR-223, were validated in more than one study. Accordingly, we can conclude that these miRNAs may play important role and thus could become potential markers for periodontal disease. However, majority of identified miRNA species differed significantly across studies (Table 1).

MiR-146a and miR-155 were dominant in in vitro studies. Otherwise, these miRNAs have also been identified in other inflammatory diseases and various cancers. MiR-146a seems to play a role in multifarious diseases and its function in bacterial infections has already been discussed [38]. MiR-155 has also been mentioned [39]. LPS may have a substantial effect on the expression of miR-146a and miR-155 [40]. Consequently, their altered expression during periodontal disease is not surprising because bacterial virulence factors such as LPS are relevant in pathogenesis of periodontitis [41]. These miRNAs are associated with many other inflammatory diseases, which might be indicative of a limited specificity. Additionally, miR-142-3p is associated with inflammation and LPS exposure [42, 43]. MiR-203 may also play an important role in inflammation and correlate with LPS exposure [44]. Interestingly, miR-203 expression is associated with immune reaction of skin [45, 46]. MiR-203 expression in keratinocytes is important; therefore, this miRNA may also be involved in gingivitis and periodontitis as determined by its effect on gingival keratinocytes. Finally, miR-223 also plays an important role in inflammation and LPS exposure [47]. Accordingly, correlations between these five miRNAs and periodontal disease are possible. Interestingly, these miRNAs appear to play a role in oral cancer. Thus, their roles in periodontal disease should be further examined (Table 4) as it might indicate a link between periodontitis and head and neck squamous cell carcinoma (HNSCC). Figure 1 shows a summary of the interactions between periodontitis and HNSCC [48], and some potentially involved miRNAs. In this context, miR-29b, which showed an in vitro correlation with LPS from P.g. grown on cigarette smoke extract [18], has also been examined for oral cancer [49]. These findings raise the question if these miRNAs could serve as diagnostic markers for periodontal diseases or simply reflect an increased inflammatory state associated with various diseases.


Kozaki et al. 2008 [63]Park et al. 2009 [28]Cervigne et al. 2009 [64]Scapoli et al. 2010 [65]Lajer et al. 2011 [66]Lundegard et al. 2015 [56]

miR-146aXXXX
miR-155XXX
miR-203XX
miR-142-3pXX
miR-223XX

Each miRNA that was validated in the context of periodontal disease was also mentioned in investigations for cancer and precancer of the oral cavity. This table provides a small exemplary overview. Consequently, even more studies with similar results are not shown here.

Another problem is the great diversity of results. Although many miRNAs were found, convergence between the investigations, particularly in vivo, is small, resulting in conflicting conclusions. Reasons for differences between investigations of periodontal disease may differ. On the one hand, small variety in patient selection and different clinical procedures potentially causes these differences (Table 2). For future studies an evident graduation, for example, Page and Eke 2007, should be used for standardization [50]. On the other hand, variations in methods used for miRNA detection could play a crucial role (Table 3). A comparison of methods used suggests that miRNA detection procedures were quite similar. However, many differences in detailed procedures are evident. Using microarray and quantitative RT-PCR for analyzing and validating miRNAs are essential components of most investigations. However, detailed procedures for methods primarily differ, so several arrays from different manufacturing companies were performed. Importantly, differences in all of chosen criteria can be found between the investigations. Besides variations in statistical analyses it is important that internal controls differed in most cases.

Another aspect that could be crucial for the varying results is the small number of study participants. One study even investigated only three healthy and three diseased individuals [23]. A large group of 86 patients was selected only once [24]. The use of small sample sizes increases vulnerability to a range of errors and biases and may be a major reason for heterogeneous study results and potential false-positive findings. Similar issues were faced in early human genetic association studies, where many of reported genotype-phenotype associations could not be replicated in subsequent studies [51, 52]. Today, replication of initial findings in second cohort is considered essential for establishing the credibility of a genotype-phenotype association [53] and similar approaches could be adopted for studies reporting associations between miRNAs and diseases. Clearly, complex reason for differences in results exists. Different methods, clinical criteria, small groups of patients, and small specificity of miRNAs for periodontal disease could be causal complex.

In summary, comparability of results for the roles of miRNAs in periodontal disease is questionable. Potential candidate miRNAs as promising markers of periodontal disease do not appear to be specific for periodontitis.

Use of salivary miRNAs as noninvasive diagnostic markers has been studied in context of oral cancer, precancer, esophageal cancer, and parotid gland cancer so far. Again, reported results of these studies were quite divergent with little overlap in identified miRNA species. Importantly, these investigations used similar methods for miRNA detection in periodontal tissue and saliva; however, detailed methods are quite different (Tables 1 and 3).

In principle, detectability of miRNAs in saliva seems certainly possible, so, for example, a current study was able to detect noncoding RNAs in saliva: 127 to 418 miRNAs could be detected in each sample of human cell free saliva, with miR-223-3p being most abundant [54]. Interestingly, miR-223 is also found in periodontal tissue. Different studies have examined saliva to identify miRNAs as potential markers for oral cancer and precancer and report remarkably diverse results (Table 3). Strangely, basic principles of investigations were similar, but different internal controls, methods for miRNA isolation, statistical analysis, and forms of saliva (stimulated/unstimulated, whole saliva/supernatant) were chosen. Notably, number of study participants is already higher in these investigations than in studies of periodontitis, but also heterogeneous with partly small group sizes (Tables 1 and 3). In addition, form of saliva may play an important role, especially whether stimulated or unstimulated saliva is used may be relevant as well as exact procedure for obtaining saliva and criteria for patient selection. Furthermore, lack of stability of exogenous miRNAs in saliva may result in quick changes of miRNA concentrations from bacteria and inflammatory reactions [28]. Potential concentrations of miRNAs in body fluids in exosomes could also affect their detectability in human saliva samples [55]. Beside of that, however, it was mentioned that there are vesicle-free noncoding RNAs in saliva [54]. Furthermore, it is questionable whether identified miRNAs from tissue investigations are also potential markers for salivary diagnostic methods. The finding of completely different miRNA expression between cancerous tissue and body fluids [34] could be similar for periodontitis.

Detailed procedures of miRNA extraction and detection could also be relevant. In a recent study by Lundegard et al. (2015) expression of miR-203 was examined in whole saliva using two different PCR methods. The study concluded that detecting low levels of miRNA in saliva is difficult; more efficient extraction methods and more sensitive PCR techniques are necessary to use saliva as a reproducible source of miRNAs [56]. Because of differences in methods used, it is questionable if investigations are comparable at all. Some miRNAs may have variable expression between different microarray, PCR, and preparation methods [57]. Reproducibility and standardization of procedure appear relevant. Validated protocols such as those already described [58] may help to standardize the procedures. This would allow better reproducibility and provide more meaningful and more comparable results. This is supported by results of Hung et al. and Liu et al. both showing miR-31 to be a potential marker for malignant tumor [30, 31]. As shown in Table 3, both studies used same form of saliva, extraction, and validation methods as well as internal controls (Table 3). Accordingly, use of saliva for diagnosis of periodontal disease under condition of uniform methods seems conceivable.

However, the mechanism of miRNA infiltration in saliva during periodontal diseases must be considered. Thereby, exosomes might play a key role in miRNA transport from different cells into saliva [59]. In periodontal tissue, the junctional epithelial layers might be of highest relevance in this context. The junctional epithelium contains only few desmosomes and has therefore widened intercellular spaces [60]. Accordingly, this epithelium allows transport of several molecules between tissue and gingival crevicular fluid (GCF) [61]. Additionally, an enlarged permeability with an increase of GCF flow is observed during gingival and periodontal inflammation [61]. Consequently, high amounts of miRNA might pass the junctional epithelium, arriving GCF and thus saliva.

If comparable results can be achieved, further investigations will be of interest. For example, changes in miRNA expression after surgical resection of a tumor, as already described [3, 32], could become clinically useful by demonstrating improved periodontal conditions after therapy as well. Therefore, it could be assessed whether periodontitis therapy was successful by analyzing expression of specific miRNAs. Additionally, correlation between periodontitis and systemic diseases could be illustrated by altered miRNA expression [26, 27]. Although this topic seems to have great potential to provide further insights regarding oral disease, a critical view is needed. Currently, we have insufficient knowledge regarding oral disease and the roles of miRNAs in pathological processes. At present it is impossible to provide a clear statement regarding real relevance and possibilities of miRNA analysis. Nevertheless, using miRNAs to understand oral diseases, particularly periodontitis, and potential use of miRNAs as noninvasive markers or as therapeutic targets could be a great approach, which justifies basic research in any case. In conclusion, we can confirm unequivocally that salivary miRNA diagnosis for periodontal disease is a revolutionary idea. However, considering that additional investigations and standardized methods are required, possibilities of exploiting potential could be estimated only in the future.

5. Conclusion

Besides similar methods regarding miRNA extraction, profiling, and validation, there are methodical differences between studies, especially in internal controls and sample size, resulting in heterogeneous results. In principle, salivary miRNA diagnostic methods seem feasible. However, in our opinion, standardized criteria and protocols should be established and followed exactly to obtain comparable results. Five miRNAs related to inflammation are available, which may be used as potential markers for periodontitis. However, their detectability and expression in saliva and, accordingly, their importance as noninvasive markers are questionable.

Competing Interests

The authors declare that they have no conflict of interests.

Acknowledgments

The authors acknowledge support from the German Research Foundation (DFG) and Universität Leipzig within the program of Open Access Publishing.

References

  1. D. P. Bartel, “MicroRNAs: genomics, biogenesis, mechanism, and function,” Cell, vol. 116, no. 2, pp. 281–297, 2004. View at: Publisher Site | Google Scholar
  2. R. M. O'Connell, D. S. Rao, A. A. Chaudhuri, and D. Baltimore, “Physiological and pathological roles for microRNAs in the immune system,” Nature Reviews Immunology, vol. 10, no. 2, pp. 111–122, 2010. View at: Publisher Site | Google Scholar
  3. J. Hao, S. Zhao, Y. Zhang et al., “Emerging role of MicroRNAs in cancer and cancer stem cells,” Journal of Cellular Biochemistry, vol. 115, no. 4, pp. 605–610, 2014. View at: Publisher Site | Google Scholar
  4. S. Qin and C. Zhang, “MicroRNAs in vascular disease,” Journal of Cardiovascular Pharmacology, vol. 57, no. 1, pp. 8–12, 2011. View at: Publisher Site | Google Scholar
  5. R. Maqbool and M. U. Hussain, “MicroRNAs and human diseases: diagnostic and therapeutic potential,” Cell and Tissue Research, vol. 358, no. 1, pp. 1–15, 2014. View at: Publisher Site | Google Scholar
  6. D. Chen, R. J. Cabay, Y. Jin et al., “MicroRNA deregulations in head and neck squamous cell carcinomas,” Journal of Oral & Maxillofacial Research, vol. 4, no. 1, article e2, 2013. View at: Publisher Site | Google Scholar
  7. R. Roy, N. De Sarkar, S. Ghose et al., “Association between risk of oral precancer and genetic variations in microRNA and related processing genes,” Journal of Biomedical Science, vol. 21, article 48, 2014. View at: Publisher Site | Google Scholar
  8. C. Staedel and F. Darfeuille, “MicroRNAs and bacterial infection,” Cellular Microbiology, vol. 15, no. 9, pp. 1496–1507, 2013. View at: Publisher Site | Google Scholar
  9. S. H. Kim, S. Y. Lee, Y. M. Lee, and Y. K. Lee, “MicroRNAs as biomarkers for dental diseases,” Singapore Dental Journal, vol. 36, pp. 18–22, 2015. View at: Publisher Site | Google Scholar
  10. M. Kebschull and P. N. Papapanou, “Mini but mighty: microRNAs in the pathobiology of periodontal disease,” Periodontology 2000, vol. 69, no. 1, pp. 201–220, 2015. View at: Publisher Site | Google Scholar
  11. R. S. Patel, A. Jakymiw, B. Yao et al., “High resolution of microRNA signatures in human whole saliva,” Archives of Oral Biology, vol. 56, no. 12, pp. 1506–1513, 2011. View at: Publisher Site | Google Scholar
  12. X. Lin, H.-C. Lo, D. T. W. Wong, and X. Xiao, “Noncoding RNAs in human saliva as potential disease biomarkers,” Frontiers in Genetics, vol. 6, article 175, 2015. View at: Publisher Site | Google Scholar
  13. M. A. Nahid, M. Rivera, A. Lucas, E. K. L. Chan, and L. Kesavalu, “Polymicrobial infection with periodontal pathogens specifically enhances microRNA miR-146a in ApoE-/- mice during experimental periodontal disease,” Infection and Immunity, vol. 79, no. 4, pp. 1597–1605, 2011. View at: Publisher Site | Google Scholar
  14. T. Honda, N. Takahashi, S. Miyauchi, and K. Yamazaki, “Porphyromonas gingivalis lipopolysaccharide induces miR-146a without altering the production of inflammatory cytokines,” Biochemical and Biophysical Research Communications, vol. 420, no. 4, pp. 918–925, 2012. View at: Publisher Site | Google Scholar
  15. S.-Y. Jiang, D. Xue, Y.-F. Xie et al., “The negative feedback regulation of microRNA-146a in human periodontal ligament cells after Porphyromonas gingivalis lipopolysaccharide stimulation,” Inflammation Research, vol. 64, no. 6, pp. 441–451, 2015. View at: Publisher Site | Google Scholar
  16. Y. F. Xie, R. Shu, S. Y. Jiang, D. L. Liu, J. Ni, and X. L. Zhang, “MicroRNA-146 inhibits pro-inflammatory cytokine secretion through IL-1 receptor-associated kinase 1 in human gingival fibroblasts,” Journal of Inflammation, vol. 10, article 20, 2013. View at: Publisher Site | Google Scholar
  17. C. R. Sipert, A. C. Morandini, T. J. Dionísio, A. J. Trachtenberg, W. P. Kuo, and C. F. Santos, “MicroRNA-146a and microRNA-155 show tissue-dependent expression in dental pulp, gingival and periodontal ligament fibroblasts in vitro,” Journal of Oral Science, vol. 56, no. 2, pp. 157–164, 2014. View at: Publisher Site | Google Scholar
  18. A. R. Naqvi, J. B. Fordham, A. Khan, and S. Nares, “MicroRNAs responsive to Aggregatibacter actinomycetemcomitans and Porphyromonas gingivalis LPS modulate expression of genes regulating innate immunity in human macrophages,” Innate Immunity, vol. 20, no. 5, pp. 540–551, 2014. View at: Publisher Site | Google Scholar
  19. K. Ouhara, I. J. Savitri, T. Fujita et al., “MiR-584 expressed in human gingival epithelial cells is induced by porphyromonas gingivalis stimulation and regulates interleukin-8 production via lactoferrin receptor,” Journal of Periodontology, vol. 85, no. 6, pp. e198–e204, 2014. View at: Publisher Site | Google Scholar
  20. C. E. Moffatt and R. J. Lamont, “Porphyromonas gingivalis induction of microRNA-203 expression controls suppressor of cytokine signaling 3 in gingival epithelial cells,” Infection and Immunity, vol. 79, no. 7, pp. 2632–2637, 2011. View at: Publisher Site | Google Scholar
  21. Y. H. Lee, H. S. Na, S. Y. Jeong, S. H. Jeong, H. R. Park, and J. Chung, “Comparison of inflammatory microRNA expression in healthy and periodontitis tissues,” Biocell, vol. 35, no. 2, pp. 43–49, 2011. View at: Google Scholar
  22. Y. F. Xie, R. Shu, S. Y. Jiang, D. L. Liu, and X. L. Zhang, “Comparison of microRNA profiles of human periodontal diseased and healthy gingival tissues,” International Journal of Oral Science, vol. 3, no. 3, pp. 125–134, 2011. View at: Publisher Site | Google Scholar
  23. Y. Ogata, S. Matsui, A. Kato, L. Zhou, Y. Nakayama, and H. Taka, “MicroRNA expression in inflamed and noninflamed gingival tissues from Japanese patients,” Journal of Oral Science, vol. 56, no. 4, pp. 253–260, 2014. View at: Publisher Site | Google Scholar
  24. C. Stoecklin-Wasmer, P. Guarnieri, R. Celenti, R. T. Demmer, M. Kebschull, and P. N. Papapanou, “MicroRNAs and their target genes in gingival tissues,” Journal of Dental Research, vol. 91, no. 10, pp. 934–940, 2012. View at: Publisher Site | Google Scholar
  25. H. Motedayyen, S. Ghotloo, M. Saffari, M. Sattari, and R. Amid, “Evaluation of MicroRNA-146a and its targets in gingival tissues of patients with chronic periodontitis,” Journal of Periodontology, vol. 86, no. 12, pp. 1380–1385, 2015. View at: Publisher Site | Google Scholar
  26. R. Perri, S. Nares, S. Zhang, S. P. Barros, and S. Offenbacher, “MicroRNA modulation in obesity and periodontitis,” Journal of Dental Research, vol. 91, no. 1, pp. 33–38, 2012. View at: Publisher Site | Google Scholar
  27. A. Z. Kalea, R. Hoteit, J. Suvan et al., “Upregulation of gingival tissue miR-200b in obese periodontitis subjects,” Journal of Dental Research, vol. 94, pp. 59–69, 2015. View at: Publisher Site | Google Scholar
  28. N. J. Park, H. Zhou, D. Elashoff et al., “Salivary microRNA: discovery, characterization, and clinical utility for oral cancer detection,” Clinical Cancer Research, vol. 15, no. 17, pp. 5473–5477, 2009. View at: Publisher Site | Google Scholar
  29. C. Salazar, R. Nagadia, P. Pandit et al., “A novel saliva-based microRNA biomarker panel to detect head and neck cancers,” Cellular Oncology, vol. 37, no. 5, pp. 331–338, 2014. View at: Publisher Site | Google Scholar
  30. K.-F. Hung, C.-J. Liu, P.-C. Chiu et al., “MicroRNA-31 upregulation predicts increased risk of progression of oral potentially malignant disorder,” Oral Oncology, vol. 53, pp. 42–47, 2016. View at: Publisher Site | Google Scholar
  31. C.-J. Liu, S.-C. Lin, C.-C. Yang, H.-W. Cheng, and K.-W. Chang, “Exploiting salivary miR-31 as a clinical biomarker of oral squamous cell carcinoma,” Head and Neck, vol. 34, no. 2, pp. 219–224, 2012. View at: Publisher Site | Google Scholar
  32. M. B. Duz, O. F. Karatas, E. Guzel et al., “Identification of miR-139-5p as a saliva biomarker for tongue squamous cell carcinoma: A Pilot Study,” Cellular Oncology, vol. 39, no. 2, pp. 187–193, 2016. View at: Publisher Site | Google Scholar
  33. Y. Yang, Y. X. Li, X. Yang, L. Jiang, Z. J. Zhou, and Y. Q. Zhu, “Progress risk assessment of oral premalignant lesions with saliva miRNA analysis,” BMC Cancer, vol. 13, article 129, 2013. View at: Publisher Site | Google Scholar
  34. F. Momen-Heravi, A. J. Trachtenberg, W. P. Kuo, and Y. S. Cheng, “Genomewide study of salivary MicroRNAs for detection of oral cancer,” Journal of Dental Research, vol. 93, supplement 7, pp. 86S–93S, 2014. View at: Publisher Site | Google Scholar
  35. F. Zahran, D. Ghalwash, O. Shaker, K. Al-Johani, and C. Scully, “Salivary microRNAs in oral cancer,” Oral Diseases, vol. 21, no. 6, pp. 739–747, 2015. View at: Publisher Site | Google Scholar
  36. Z. Xie, G. Chen, X. Zhang et al., “Salivary microRNAs as promising biomarkers for detection of esophageal cancer,” PLoS ONE, vol. 8, no. 4, Article ID e57502, 2013. View at: Publisher Site | Google Scholar
  37. J. H. Matse, J. Yoshizawa, X. Wang et al., “Discovery and prevalidation of salivary extracellular microRNA biomarkers panel for the noninvasive detection of benign and malignant parotid gland tumors,” Clinical Cancer Research, vol. 19, no. 11, pp. 3032–3038, 2013. View at: Publisher Site | Google Scholar
  38. Z. Liu, B. Xiao, B. Tang et al., “Up-regulated microRNA-146a negatively modulate Helicobacter pylori-induced inflammatory response in human gastric epithelial cells,” Microbes and Infection, vol. 12, no. 11, pp. 854–863, 2010. View at: Publisher Site | Google Scholar
  39. L. N. Schulte, A. J. Westermann, and J. Vogel, “Differential activation and functional specialization of miR-146 and miR-155 in innate immune sensing,” Nucleic Acids Research, vol. 41, no. 1, pp. 542–553, 2013. View at: Publisher Site | Google Scholar
  40. Y. Cheng, W. Kuang, Y. Hao et al., “Downregulation of miR-27a and miR-532-5p and upregulation of mir-146a and mir-155 in LPS-induced RAW264.7 Macrophage cells,” Inflammation, vol. 35, no. 4, pp. 1308–1313, 2012. View at: Publisher Site | Google Scholar
  41. D. Mayrand and S. C. Holt, “Biology of asaccharolytic black-pigmented Bacteroides species,” Microbiological Reviews, vol. 52, no. 1, pp. 134–152, 1988. View at: Google Scholar
  42. S. A. Moschos, A. E. Williams, M. M. Perry, M. A. Birrell, M. G. Belvisi, and M. A. Lindsay, “Expression profiling in vivo demonstrates rapid changes in lung microRNA levels following lipopolysaccharide-induced inflammation but not in the anti-inflammatory action of glucocorticoids,” BMC Genomics, vol. 8, article 240, 2007. View at: Publisher Site | Google Scholar
  43. G. Xu, Z. Zhang, J. Wei et al., “MicroR-142-3p down-regulates IRAK-1 in response to Mycobacterium bovis BCG infection in macrophages,” Tuberculosis, vol. 93, no. 6, pp. 606–611, 2013. View at: Publisher Site | Google Scholar
  44. X.-F. Ke, J. Fang, X.-N. Wu, and C.-H. Yu, “MicroRNA-203 accelerates apoptosis in LPS-stimulated alveolar epithelial cells by targeting PIK3CA,” Biochemical and Biophysical Research Communications, vol. 450, no. 4, pp. 1297–1303, 2014. View at: Publisher Site | Google Scholar
  45. M. N. Primo, R. O. Bak, B. Schibler, and J. G. Mikkelsen, “Regulation of pro-inflammatory cytokines TNFα and IL24 by microRNA-203 in primary keratinocytes,” Cytokine, vol. 60, no. 3, pp. 741–748, 2012. View at: Publisher Site | Google Scholar
  46. T. Wei, N. Xu, F. Meisgen, M. Ståhle, E. Sonkoly, and A. Pivarcsi, “Interleukin-8 is regulated by miR-203 at the posttranscriptional level in primary human keratinocytes,” European Journal of Dermatology, 2013. View at: Publisher Site | Google Scholar
  47. M. Haneklaus, M. Gerlic, L. A. J. O'Neill, and S. L. Masters, “MiR-223: infection, inflammation and cancer,” Journal of Internal Medicine, vol. 274, no. 3, pp. 215–226, 2013. View at: Publisher Site | Google Scholar
  48. Y. W. Han, W. Houcken, B. G. Loos, H. A. Schenkein, and M. Tezal, “Periodontal disease, atherosclerosis, adverse pregnancy outcomes, and head-and-neck cancer,” Advances in Dental Research, vol. 26, no. 1, pp. 47–55, 2014. View at: Publisher Site | Google Scholar
  49. C. N. Yang, Y. T. Deng, J. Y. Tang et al., “MicroRNA-29b regulates migration in oral squamous cell carcinoma and its clinical significance,” Oral Oncology, vol. 51, no. 2, pp. 170–177, 2016. View at: Publisher Site | Google Scholar
  50. R. C. Page and P. I. Eke, “Case definitions for use in population-based surveillance of periodontitis,” Journal of Periodontology, vol. 78, no. 7, pp. 1387–1399, 2007. View at: Publisher Site | Google Scholar
  51. J. N. Hirschhorn, K. Lohmueller, E. Byrne, and K. Hirschhorn, “A comprehensive review of genetic association studies,” Genetics in Medicine, vol. 4, no. 2, pp. 45–61, 2002. View at: Publisher Site | Google Scholar
  52. A. T. Hattersley and M. I. McCarthy, “What makes a good genetic association study?” The Lancet, vol. 366, no. 9493, pp. 1315–1323, 2005. View at: Publisher Site | Google Scholar
  53. S. J. Chanock, T. Manolio, M. Boehnke et al., “Replicating genotype-phenotype associations,” Nature, vol. 447, no. 7145, pp. 655–660, 2007. View at: Publisher Site | Google Scholar
  54. J. H. Bahn, Q. Zhang, F. Li et al., “The landscape of microRNA, piwi-interacting RNA, and circular RNA in human saliva,” Clinical Chemistry, vol. 61, no. 1, pp. 221–230, 2015. View at: Publisher Site | Google Scholar
  55. A. Gallo, M. Tandon, I. Alevizos, and G. G. Illei, “The majority of microRNAs detectable in serum and saliva is concentrated in exosomes,” PLoS ONE, vol. 7, no. 3, article e30679, 2012. View at: Publisher Site | Google Scholar
  56. M. Lundegard, K. Nylander, and K. Danielsson, “Difficulties detecting miRNA-203 in human whole saliva by the use of PCR,” Medicina Oral, Patologia Oral y Cirugia Bucal, vol. 20, no. 2, pp. e130–e134, 2015. View at: Publisher Site | Google Scholar
  57. R. A. Ach, H. Wang, and B. Curry, “Measuring microRNAs: comparisons of microarray and quantitative PCR measurements, and of different total RNA prep methods,” BMC Biotechnology, vol. 8, article 69, 2008. View at: Publisher Site | Google Scholar
  58. J. M. Yoshizawa and D. T. W. Wong, “Salivary microRNAs and oral cancer detection,” Methods in Molecular Biology, vol. 936, pp. 313–324, 2013. View at: Publisher Site | Google Scholar
  59. V. Palanisamy, S. Sharma, A. Deshpande, H. Zhou, J. Gimzewski, and D. T. Wong, “Nanostructural and transcriptomic analyses of human saliva derived exosomes,” PLoS ONE, vol. 5, article e8577, 2010. View at: Publisher Site | Google Scholar
  60. S. Hatakeyama, T. Yaegashi, Y. Oikawa et al., “Expression pattern of adhesion molecules in junctional epithelium differs from that in other gingival epithelia,” Journal of Periodontal Research, vol. 41, no. 4, pp. 322–328, 2006. View at: Publisher Site | Google Scholar
  61. D. D. Bosshardt and N. P. Lang, “The junctional epithelium: from health to disease,” Journal of Dental Research, vol. 84, no. 1, pp. 9–20, 2005. View at: Publisher Site | Google Scholar
  62. R. T. Demmer, J. H. Behle, D. L. Wolf et al., “Transcriptomes in healthy and diseased gingival tissues,” Journal of Periodontology, vol. 79, no. 11, pp. 2112–2124, 2008. View at: Publisher Site | Google Scholar
  63. K. Kozaki, I. Imoto, S. Mogi, K. Omura, and J. Inazawa, “Exploration of tumor-suppressive microRNAs silenced by DNA hypermethylation in oral cancer,” Cancer Research, vol. 68, no. 7, pp. 2094–2105, 2008. View at: Publisher Site | Google Scholar
  64. N. K. Cervigne, P. P. Reis, J. Machado et al., “Identification of a microRNA signature associated with progression of leukoplakia to oral carcinoma,” Human Molecular Genetics, vol. 18, no. 24, pp. 4818–4829, 2009. View at: Publisher Site | Google Scholar
  65. L. Scapoli, A. Palmieri, L. Lo Muzio et al., “MicroRNA expression profiling of oral carcinoma identifies new markers of tumor progression,” International Journal of Immunopathology and Pharmacology, vol. 23, no. 4, pp. 1229–1234, 2010. View at: Google Scholar
  66. C. B. Lajer, F. C. Nielsen, L. Friis-Hansen et al., “Different miRNA signatures of oral and pharyngeal squamous cell carcinomas: a prospective translational study,” British Journal of Cancer, vol. 104, no. 5, pp. 830–840, 2011. View at: Publisher Site | Google Scholar

Copyright © 2016 Gerhard Schmalz et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


More related articles

1941 Views | 802 Downloads | 15 Citations
 PDF  Download Citation  Citation
 Download other formatsMore
 Order printed copiesOrder

Related articles

We are committed to sharing findings related to COVID-19 as quickly and safely as possible. Any author submitting a COVID-19 paper should notify us at help@hindawi.com to ensure their research is fast-tracked and made available on a preprint server as soon as possible. We will be providing unlimited waivers of publication charges for accepted articles related to COVID-19. Sign up here as a reviewer to help fast-track new submissions.