Shared Genetic and Epigenetic Mechanisms between the Osteogenic Differentiation … · 2021. 2. 8. · are bone marrow stem cells (BMSCs), dental pulp stem cells (DPSCs), and adipose

Research ArticleShared Genetic and Epigenetic Mechanisms between theOsteogenic Differentiation of Dental Pulp Stem Cells and BoneMarrow Stem Cells

Sebastian Gaus ,1 Hanluo Li ,1 Simin Li ,2 Qian Wang ,3 Tina Kottek ,1

Sebastian Hahnel ,1 Xiangqiong Liu ,4 Yupei Deng ,4 Dirk Ziebolz ,2 Rainer Haak ,2

Gerhard Schmalz ,2 Lei Liu ,5 Vuk Savkovic ,1 and Bernd Lethaus 1

1Department of Cranio Maxillofacial Surgery, University Clinic Leipzig, Liebigstr. 12, Leipzig 04103, Germany2Department of Cariology, Endodontology and Periodontology, University Leipzig, Liebigstr. 12, Leipzig 04103, Germany3Department of Central Laboratory, Taian Central Hospital, Longtan Road No. 29, Taian, 271000 Shandong Province, China4Department of Molecular Cell Biology, Beijing Tibetan Hospital, China Tibetology Research Center, 218 Anwaixiaoguanbeili Street,Chaoyang, Beijing 100029, China5Department of Neurology, Shandong Provincial Third Hospital, Cheeloo Chollege of Medicine, Shandong University, Jinan,100191 Shandong Province, China

Correspondence should be addressed to Vuk Savkovic; [email protected]

Received 29 November 2020; Revised 4 January 2021; Accepted 20 January 2021; Published 8 February 2021

Academic Editor: Min Tang

Copyright © 2021 Sebastian Gaus 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.

Objective. To identify the shared genetic and epigenetic mechanisms between the osteogenic differentiation of dental pulp stem cells(DPSC) and bone marrow stem cells (BMSC).Materials and Methods. The profiling datasets of miRNA expression in the osteogenicdifferentiation of mesenchymal stem cells from the dental pulp (DPSC) and bone marrow (BMSC) were searched in the GeneExpression Omnibus (GEO) database. The differential expression analysis was performed to identify differentially expressedmiRNAs (DEmiRNAs) dysregulated in DPSC and BMSC osteodifferentiation. The target genes of the DEmiRNAs that weredysregulated in DPSC and BMSC osteodifferentiation were identified, followed by the identification of the signaling pathways andbiological processes (BPs) of these target genes. Accordingly, the DEmiRNA-transcription factor (TFs) network and theDEmiRNAs-small molecular drug network involved in the DPSC and BMSC osteodifferentiation were constructed. Results. 16dysregulated DEmiRNAs were found to be overlapped in the DPSC and BMSC osteodifferentiation, including 8 DEmiRNAs with acommon expression pattern (8 upregulated DEmiRNAs (miR-101-3p, miR-143-3p, miR-145-3p/5p, miR-19a-3p, miR-34c-5p,miR-3607-3p, miR-378e, miR-671-3p, and miR-671-5p) and 1 downregulated DEmiRNA (miR-671-3p/5p)), as well as 8DEmiRNAs with a different expression pattern (i.e., miR-1273g-3p, miR-146a-5p, miR-146b-5p, miR-337-3p, miR-382-3p, miR-4508, miR-4516, and miR-6087). Several signaling pathways (TNF, mTOR, Hippo, neutrophin, and pathways regulatingpluripotency of stem cells), transcription factors (RUNX1, FOXA1, HIF1A, and MYC), and small molecule drugs (curcumin,docosahexaenoic acid (DHA), vitamin D3, arsenic trioxide, 5-fluorouracil (5-FU), and naringin) were identified as commonregulators of both the DPSC and BMSC osteodifferentiation. Conclusion. Common genetic and epigenetic mechanisms areinvolved in the osteodifferentiation of DPSCs and BMSCs.

1. Introduction

Repairing bone defects remains a challenge for clinical prac-titioners to the present day. For the last decades, autologousbone transplantation has been a “gold standard” for treating

bone defects in the dental field, such as insufficient bone vol-ume for dental implants and maxillofacial defects [1, 2].Nonetheless, the conventional treatment involves drawbackssuch as donor site morbidity and limitation of bone volume[3], which calls for alternative approaches. Mesenchymal

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stem cells appear to be a good match to the unmet needs ofthe conventional autologous bone transplantation. They arecapable of acting in paracrine anti-inflammatory and trophicfashion, as well as of providing a cellular base for tissuereplacement by virtue of their self-renewal and multilineagedifferentiation capacity [4]. The most commonly used MSCsare bone marrow stem cells (BMSCs), dental pulp stem cells(DPSCs), and adipose tissue stem cells (ADSCs). BMSCshave been the most commonly used type of stem cells forosteogenesis and new bone formation due to their tissue ori-gin; however, BMSCs are obtained by means of invasive andpainful bone marrow aspiration [5]. This downside hasinspired the use of other less invasively obtained stem celltypes. Among those, DPSCs obtained from the extractedthird molar present a highly accessible alternative [6]. Inaddition, DPSCs have been demonstrated as highly capableof osteogenic differentiation under osteogenesis-inducingconditions [7], and they are therefore becoming a valuablealternative approach for transplantation-based bone regener-ation [8]. Nevertheless, critical preclinical data necessary forunderstanding the genetic and epigenetic mechanismsinvolved in the osteogenic differentiation of DPSCs andBMSCs are still modestly represented.

Stem cells derived from different tissues tend to respondto the same stimulus differently and differentiate towardsthe tissue of their origin [9]. Accordingly, BMSCs display ahigh predisposition to progress towards osteogenic differen-tiation [9]. It has been shown that the osteogenic differenti-ation capacity of the BMSCs is higher than that of ADSCs[10, 11] and comparable between the BMSCs and DPSCs[12]. Having tremendous BMSCs and DPSCs osteogenicpotential at disposal, it is necessary to gain a fuller under-standing of genetic and epigenetic processes that underlietheir differentiation capacity in order to utilize their osteo-genic ability.

Many genetic and epigenetic factors are involved in theosteogenic differentiation of stem cells, such as messengerRNAs (mRNAs), microRNAs (miRNAs), and signalingpathways. As a significant component of the epigeneticmodification, miRNAs are classified as short noncodingRNAs which can inhibit the expression of mRNAs by bind-ing the 3′-untranslated region (UTR) of target mRNAs [13,14]. The aberrant expression of many miRNAs (e.g., miR-16, miR-381, miR-20a, and miR-214) has been involved inthe osteogenic differentiation of stem cells by inducing thedysregulation of osteogenesis-related signaling pathways(e.g., Wnt, BMP, MAPK, RUNX2, and Notch pathways)[15–22]. Although some research using RNA-sequencingtechnique have investigated the miRNA expression alter-ations during the osteodifferentiation process of BMSCs[23] and DPSCs [24], respectively, there is still no reportwhich is aimed on identifying the genetic and epigeneticbiomarkers shared between the osteogenic differentiationof both types of stem cells.

The present study is aimed at identifying the overlappinggenetic and epigenetic mechanisms involved in the osteo-genic differentiation of DPSC and BMSC. To this purpose,a series of bioinformatics analyses (e.g., differential expres-sion analysis, DEmiRNA-target gene network construction,

DEmiRNA-transcription factor construction, and functionalenrichment analysis) were performed to investigate themajor common genetic and epigenetic mechanisms of DPSCosteogenesis and BMSC osteogenesis.

2. Materials and Methods

2.1. Data Acquisition. The miRNA expression profiling data-sets regarding the osteogenic differentiation of DPSC andBMSC were searched for in the Gene Expression Omnibus(GEO) database of NCBI [25]. The following inclusion cri-teria were defined for analyzing two study groups: an undif-ferentiated control group nominated as the day zero ofdifferentiation (d0), and the experimental group examinedafter differentiation on day 14, with matched examinationdays for the DPSC and BMSC experimental group (d14).The datasets with a sample size of more than three for eachgroup were included.

2.2. Analyzing Processes of the Present Research. Two datasets(GSE138180 and GSE107279), which investigated themiRNA expression profile of DPSC and BMSC, were selectedfor assessment. After selecting the corresponding datasets, aseries of bioinformatics analyses were performed accordingto the flowchart of this study (Figure 1).

Firstly, the differential expression analysis was per-formed to identify the DEmiRNAs which were aberrantlyexpressed during the osteodifferentiation process of DPSCsand BMSCs, in order to identify the overlapping DEmiR-NAs. Subsequently, the target genes of these commonDEmiRNAs that were singled out in the first step wereidentified by constructing a target gene network of 16overlapping DEmiRNAs. Furthermore, target genes ofDEmiRNAs involved in the DPSC osteogenesis and BMSCosteogenesis were, respectively, extracted by searchingmiRNA-target interaction databases. The functions (i.e., bio-logical processes and signaling pathways) of these targetgenes were identified by the means of functional enrichmentanalysis. In addition, transcription factors that potentiallytarget the DEmiRNAs were identified by constructing theDEmiRNAs-transcription factor interaction network. Con-clusively, the DEmiRNAs-small molecular drug targetsnetwork was constructed in order to identify the smallmolecular drugs that can influence the expression of DEmiR-NAs involved in DPSC and BMSC osteodifferentiation.

2.3. Differential Expression Analysis for IdentifyingDEmiRNAs. Differential expression analysis (DEA) was usedto identify the differentially expressed miRNAs (DEmiRNAs)of the two selected datasets. DEA was performed by usingdifferent packages in the R program depending on the differ-ent experimental types of datasets. The limma package wasused to analyze continuous data such as microarray data,whereas the edgeR/DESeq/DESeq2 was used for count datasuch as high-throughput sequencing. The experimental typeof the GSE138180 dataset presents the noncoding RNA pro-file analyzed by the means of microarray, whereas the exper-imental type of the GSE107279 dataset profiling of thenoncoding RNA has been attained by high-throughput

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sequencing. Based on this, the DEA of the GSE138180 data-set was carried out using the limma package of the Rprogram version 3.6.1 [26], whereas the DEA of theGSE107279 dataset was performed by using the DESeq2package [27]. The miRNAs with a p value < 0.05 and ∣logFC ∣ ≥1 were selected as differentially expressed. TheDEmiRNAs with log FC ≥ 1 was defined as upregulatedDEmiRNAs, while the DEmiRNAs with log FC ≤ −1 weredefined as downregulated DEmiRNAs. The overlappingDEmiRNAs expressed in the osteogenic differentiation ofDPSC and BMSC were found by uploading the list ofDEmiRNAs in the Venn web tool webpage (http://bioinformatics.psb.ugent.be/webtools/Venn/).

2.4. Target Genes of the Overlapping DEmiRNAs in DPSC andBMSC Osteodifferentiation. After identifying the overlappedDEmiRNAs that were dysregulated in both DPSC and BMSCosteodifferentiation, their target genes were extracted bydownloading the human miRNA-target interaction pairsfrom three databases including miRDB Version 6.0 [28],miRWalk [29], and TargetScan v7.1 [30]. The overlappingDEmiRNA-target gene interaction network was thereforeconstructed, and the target genes with the top degree wereidentified.

2.5. Functional Enrichment Analysis of Target Genes ofDEmiRNAs. After obtaining the DEmiRNAs expressed dur-ing the osteogenic differentiation of DPSC and BMSC, targetgenes of DEmiRNAs involved in DPSC osteodifferentiation

and BMSC osteodifferentiation were, respectively, extractedby downloading the human miRNA-target interaction pairsfrom three databases mentioned earlier [28–30]. The func-tional enrichment analysis (FEA) was performed on thetarget genes of DEmiRNAs expressed in the osteogenic dif-ferentiation of DPSC and BMSC. This analysis was con-ducted by using the clusterProfiler package of the Rprogram [31]. The functions of the candidate target genesof the DEmiRNAs were explored by assessing their enrich-ment in Gene Ontology (GO) terms, in particular biologicalprocesses (BPs) and the pathway enrichment analysisaccording to the Kyoto Encyclopedia of Genes and Genomes(KEGG). The GO terms and KEGG pathways with a p value< 0.05 were considered to be significantly enriched. If thenumber of enriched BPs and pathways was greater than 30,only the top 30 with the highest p values were chosen to bevisualized in the bar plot. If the number of enriched BPsand pathways was lower than 30, all of the BPs and pathwayswere visualized in the bar plot.

2.6. Construction of DEmiRNA-Transcription Factor (TF)Interaction Network. Based on the DEmiRNAs obtained byDEA, the DEmiRNA-transcription factor (TF) interactionpairs were derived from the TransmiR database [32]. TheDEmiRNA-TF regulatory networks involved in the DPSCosteogenesis and BMSC osteogenesis were, respectively, plot-ted by using the Cytoscape software version 3.7.2. The topo-logical characteristics of the nodes in these two networkswere calculated. The top 30 TFs with the highest degree in

GSE138180miRNA expression profile in

DPSC osteodifferentiation

Functional enrichment analysis oftarget genes

DEmiRNAs-transcription factorsinteraction network

GSE107279miRNA expression profile inBMSC osteodifferentiation

DEmiRNAs dysregulated inDPSC osteodifferentiation

DEmiRNAs dysregulated inBMSC osteodifferentiation

Functional enrichment analysisof target genes

Overlapping DEmiRNAs

Overlapping biological processesand signaling pathways

Overlapping transcription factors

DEmiRNAs-small molecular druginteraction network Overlapping small molecular drugs

Overlapping processesDPSC

osteodifferentiationBMSC

osteodifferentiation

DEmiRNAs-transcription factorsinteraction network

DEmiRNAs-small molecular druginteraction network

Target genes of overlapping DEmiRNAs

Figure 1: The study flowchart.

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http://bioinformatics.psb.ugent.be/webtools/Venn/

http://bioinformatics.psb.ugent.be/webtools/Venn/

these two networks were selected, and their intersection wasobtained. The intersection between the top 30 TFs of thesetwo networks could be regarded as critical overlapping TFsthat targeted DEmiRNAs dysregulated in both the DPSCand BMSC osteodifferentiation.

2.7. Construction of DEmiRNA-Small Molecular Drug TargetInteraction Network. The SM2miR database provides infor-mation about experimentally validated linkage betweenmiRNAs and bioactive small molecules that can influenceexpression levels of the miRNAs [33]. This database contains2,925 relationship pairs between small molecule drugs andmiRNAs in 17 species, and only the data related to humanspecies were collected. A total of 2,756 human interactionpairs between miRNAs and small molecular drugs were col-lected from this database. The interaction pairs of (DEmiR-NAs (DPSC osteodifferentiation)-small molecule targets)and (DEmiRNAs (BMSC osteodifferentiation)-small mole-cule targets) were, respectively, extracted from databaseSM2miR v1.0 [33]. Subsequently, the DEmiRNAs-smallmolecule drug targets networks were constructed for DPSCand BMSC osteodifferentiation by the means of Cytoscapesoftware version 3.6. In these two networks, the expressionpatterns (up-/downregulation) of miRNAs were definedaccording to their expression in the DPSC and BMSCosteodifferentiation, rather than their expression patternsshown in the SM2miR database. Consequently, the inter-sections between these two networks were identified basedon the overlapping DEmiRNA-small molecule interactionpairs and the overlapping small molecules.

3. Results

3.1. Dataset Procurement. Preselection of data relevant to themiRNA expression profiling of DPSC and BMSC in thecourse of the osteogenic differentiation process brought abouttwo datasets (GSE138180 and GSE107279). The GSE138180dataset (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE138180) reported the miRNA expression alteration ofDPSC investigated by comparing the 14th day of postdifferen-tiation with the 14th day of culturing cells without differentia-tion. The GSE107279 dataset (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107279) addressed the miRNAexpression alteration of BMSC by comparing the 13th day ofpostdifferentiation with day 0 (nondifferentiated cells whileprior to differentiation).

3.2. The Overlapping DEmiRNAs during the OsteogenicDifferentiation between DPSC and BMSC. After performingDEA based on two datasets (GSE138180 and GSE107279),186 DEmiRNAs (122 upregulated and 64 downregulated)and 104 DEmiRNAs (52 upregulated and 52 downregulated)were identified as differentially expressed in the osteogenicdifferentiation processes of DPSC and BMSC, respectively(Figure 2. File S1 and S2 showed the dysregulation of allDEmiRNAs dysregulated in the osteodifferentiation ofDPSCs and BMSCs. The top 30 DEmiRNAs of GSE138180and GSE107279 were listed in Table 1, ranked in the ascend-ing order of their p value. The explanation of the abbreviated

parameters shown in Table 1 was listed as below: logFC:log2 fold change; AveExpr: average expression across allsamples; t: logFC divided by its standard error; p.value:raw p value (based on t) from the test that logFC differsfrom 0; adj.p.Val: Benjamini-Hochberg false discovery rateadjusted p value; B: log-odds that miRNA is DE; expres-sion patterns: DEmiRNA is upregulated or downregulated.

As shown in the Venn diagram (Figure 2), a total of 186DEmiRNAs (122 upregulated and 64 downregulated) and104 DEmiRNAs (52 upregulated and 52 downregulated)were identified to be involved in the osteodifferentiation ofDPSCs and BMSCs, respectively. 16 DEmiRNAs were identi-fied as relevant for the osteogenic differentiation of bothDPSCs and BMSCs. Among these 16 overlapped DEmiNAs,eight DEmiRNAs (i.e., miR-101-3p, miR-143-3p, miR-145(3p/5p), miR-19a-3p, miR-34c-5p, miR-3607-3p, miR-378e,and miR-671 (3p/5p)) were found to show the same expres-sion patterns in the osteodifferentiation course (2 weeks) ofboth DPSCs and BMSCs, while another eight DEmiRNAs(i.e., miR-1273g-3p, miR-146a-5p, miR-4508, miR-4516,miR-6087, miR-146b-5p, miR-337-3p, and miR-382-3p)were found to show the different expression patterns. Amongthe eight DEmiRNAs with the same expression patterns,seven DEmiRNAs were found to be upregulated in the oste-ogenic differentiation course (~2 weeks) of both DPSCs andBMSCs: miR-101-3p, miR-143-3p, miR-145(3p/5p), miR-19a-3p, miR-34c-5p, miR-3607-3p, and miR-378e; andanother one DEmiRNA (miR-671 (3p/5p)) was found to bedownregulated in the osteogenic differentiation course (2weeks) of both DPSCs and BMSCs. Another eight DEmiR-NAs were divergently expressed in DPSCs and BMSCsthroughout the osteogenic differentiation course (2 weeks),e.g., five miRNAs were found downregulated in DPSCs whileupregulated in BMSCs (i.e., miR-1273g-3p, miR-146a-5p,miR-4508, miR-4516, and miR-6087), as well as three miR-NAs upregulated in DPSCs while downregulated in BMSCs(i.e., miR-146b-5p, miR-337-3p, and miR-382-3p). Amongthese 16 DemiRNAs, 11 of them (i.e., miR-19a-3p, miR-3607-3p, miR-378e, miR-671 (3p/5p), miR-1273g-3p, miR-146b-5p, miR-337-3p, miR-4508, miR-4516, miR-6087, andmiR-382-3p) were not supported by previous evidence tobe involved in the osteodifferentiation of stem cells. Thefunctions of other five DEmiRNAs (i.e., miR-101-3p, miR-143-3p, miR-145 (3p/5p), miR-34c-5p, and miR-146a-5p)in the osteodifferentiaton of DPSCs and BMSCs were sum-marized in Table 2.

3.3. The Target Genes of the 16 Overlapped DEmiRNAs. Inorder to identify the target genes of the 16 overlappingDEmiRNAs, their DEmiRNA-target interaction networkwas constructed (Figure 3). The topological characteristicsof all nodes of this network were shown in File S3, and thetopological features of the top 30 gene nodes of this networkwere shown in Table 3. As shown in Table 3, genes CCND2(cyclin D2), THBS1 (thrombospondin-1), CCND1 (cyclinD1), IGF1R (insulin-like growth factor 1 receptor), REL(REL proto-oncogene, NF-KB subunit), and ELK4 (ETStranscription factor ELK4)) were identified as the targetgenes of 16 DEmiRNAs.


https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107279


3.4. The Overlapping Biological Processes and PathwaysInvolved in the Osteogenic Differentiation of DPSCs andBMSCs. Subsequently, by the means of the functional enrich-ment analysis, the significantly enriched biological processes(BPs) and signaling pathways in target genes of the DEmiR-NAs were identified for DPSCs and BMSCs (Figures 4 and 5).The overlapping BPs and pathways involved in the osteo-genic differentiation of DPSCs and BMSCs were singledout. As shown in Figure 4, several BPs were identified asoverlapping and therefore common for osteogenic differenti-ation of both DPSCs and BMSCs: p53 binding, protein het-erodimerization activity, ATPase activity, GTPase binding,cadherin binding, and histone binding DPSCs and BMSCs.As shown in Figure 5, a total of 12 signaling pathways wereidentified as overlapped between DPSCs and BMSCs: TNF,mTOR, Hippo, neutrophin, pathways regulating pluripo-tency of stem cells, cell cycle, MAPK, focal adhesion,ubiquitin-mediated proteolysis, viral carcinogenesis, autoph-agy, and protein processing in endoplasmic reticulum andendocytosis.

3.5. The Overlapping Transcription Factors Targeted byDEmiRNAs between DPSCs and BMSCs. As shown inFigure 6, the DEmiRNA-transcription factor (TF) interactionnetwork involved in both DPSCs and BMSCs were con-structed. The top 30 TFs with the highest degree in thesetwo networks were listed in Table 4 ranking in the descending

order of degree. By comparing the top 30 TFs with the highestdegree in these two networks shown in File S4 and File S5, atotal of 26 transcription factors were found overlapped, e.g.,TCF12, ERG, CEBPB, ELF1, TCF3, ARNTL, KDM2B, MYC,BRD4, CTCF, MAX, LARP7, HIF1A, E2F1, KDM5B, MAZ,PHF8, STAT1, EP300, AR, FOXA1, TFAP2C, RUNX1,ESR1, TRIM28, and SPI1.

3.6. The Overlapping Small Molecules Targeted by DEmiRNAsDysregulated in DPSCs and BMSCs Osteodifferentiation. TheDEmiRNA-small molecular drug target interaction network,respectively, involved in DPSCs and BMSCs osteodifferen-tiation were shown in Figures 7(a) and 6(b). In the SM2miRdatabase, only 40 DEmiRNAs of DPSC osteodifferentiationand 27 DEmiRNAs of BMSC osteodifferentiation werefound to be targeted and regulated by the small moleculardrugs. The small molecular drugs in this database were notfound to target and impact the expression of the otherDEmiRNAs that were also dysregulated in DPSC and BMSCosteodifferentiation. By assessing the interaction pairs shownin Figures 7(a) and 7(b), we identified 13 interaction pairsconsisting of four DEmiRNAs (hsa-miR-143-3p, hsa-miR-146b-5p, hsa-miR-34c-5p, and hsa-miR-671-5p). 13 smallmolecules were found to be shared between the two net-works that are displayed in Table 5. Additionally, a total of19 small molecule drugs were found to not only impact theexpression of DEmiRNAs in DPSC osteodifferentiation but

168 DEmiRNAs 86 DEmiRNAs16

DEmiRNAs

7 DEmiRNAsupregulated

hsa-miR-101-3phsa-miR-143-3p

hsa-miR-145 (3p/5p)hsa-miR-19a-3phsa-miR-34c-5p

hsa-miR-3607-3phsa-miR-378e

1 DEmiRNAsdownregulated hsa-miR-671 (3p/5p)

8 DEmiRNAssame expression pattern in

DPSC and BMSC osteodifferentiation

8 DEmiRNAsdifferent expression pattern in

DPSC and BMSC osteodifferentiation

DEmiRNAsStem cells DPSCs BMSCs

hsa-miR-1273g-3p down uphsa-miR-146a-5p down uphsa-miR-146b-5p up downhsa-miR-337-3p up downhsa-miR-382-3p up downhsa-miR-4508 down uphsa-miR-4516 down uphsa-miR-6087 down up

DPSCosteodifferentiation

BMSCosteodifferentiationOverlapping

UpregulatedDEmiRNAs

DownregulatedDEmiRNAs Total DEmiRNAs

GSE138180 (DPSC osteodifferentiation) 122 64 186GSE107279 (BMSC osteodifferentiation) 52 52 104

Datasets

Figure 2: 16 DEmiRNAs identified to be overlapped in the osteodifferentiation of DPSCs and BMSCs.


Table 1: The top 30 DEmiRNAs expressed in the osteogenic differentiation of DPSCs and BMSCs, ranked in the ascending order oftheir p value.

The top 30 DEmiRNAs dysregulated in DPSC osteodifferentiation

DEmiRNAs logFC p.value Adj.p.Val Expression pattern

hsa-let-7f-2-3p 4.542015233 1:45E − 06 0.000106517 Up

hsa-miR-1468-3p 4.542015233 1:45E − 06 0.000106517 Up

hsa-miR-153-3p 4.542015233 1:45E − 06 0.000106517 Up

hsa-miR-212-5p 4.542015233 1:45E − 06 0.000106517 Up

hsa-miR-2355-5p 4.542015233 1:45E − 06 0.000106517 Up

hsa-miR-342-5p 4.542015233 1:45E − 06 0.000106517 Up

hsa-miR-3658 4.542015233 1:45E − 06 0.000106517 Up

hsa-miR-450a-1-3p 4.542015233 1:45E − 06 0.000106517 Up

hsa-miR-450b-3p 4.542015233 1:45E − 06 0.000106517 Up

hsa-miR-4639-5p 4.542015233 1:45E − 06 0.000106517 Up

hsa-miR-4730 4.542015233 1:45E − 06 0.000106517 Up

hsa-miR-508-3p 4.542015233 1:45E − 06 0.000106517 Up

hsa-miR-548d-5p 4.542015233 1:45E − 06 0.000106517 Up

hsa-miR-588 4.542015233 1:45E − 06 0.000106517 Up

hsa-miR-6077 4.542015233 1:45E − 06 0.000106517 Up

hsa-miR-99a-3p 4.542015233 1:45E − 06 0.000106517 Up

hsa-miR-1203 4.1591475 2:09E − 06 0.000106517 Up

hsa-miR-1238-5p 4.1591475 2:09E − 06 0.000106517 Up

hsa-miR-128-2-5p 4.1591475 2:09E − 06 0.000106517 Up

hsa-miR-1288-5p 4.1591475 2:09E − 06 0.000106517 Up

hsa-miR-129-5p 4.1591475 2:09E − 06 0.000106517 Up

hsa-miR-138-1-3p 4.1591475 2:09E − 06 0.000106517 Up

hsa-miR-141-3p 4.1591475 2:09E − 06 0.000106517 Up

hsa-miR-1972 4.1591475 2:09E − 06 0.000106517 Up

hsa-miR-3074-5p 4.1591475 2:09E − 06 0.000106517 Up

hsa-miR-339-5p 4.1591475 2:09E − 06 0.000106517 Up

hsa-miR-33a-3p 4.1591475 2:09E − 06 0.000106517 Up

hsa-miR-34b-3p 4.1591475 2:09E − 06 0.000106517 Up

hsa-miR-369-3p 4.1591475 2:09E − 06 0.000106517 Up

hsa-miR-382-3p 4.1591475 2:09E − 06 0.000106517 Up

The top 30 DEmiRNAs dysregulated in BMSC osteodifferentiation

DEmiRNAs logFC p.value Adj.p.Val Expression pattern

hsa-miR-3182 -5.37979 5:96E − 105 3:54E − 102 Up

hsa-miR-182-5p 2.561101 1:58E − 69 4:67E − 67 Down

hsa-miR-335-3p 5.160868 3:61E − 59 7:13E − 57 Down

hsa-miR-4284 -5.15177 2:73E − 56 4:05E − 54 Up

hsa-miR-92b-3p 1.590835 1:49E − 45 1:76E − 43 Down

hsa-miR-21-5p -1.35202 5:02E − 44 4:96E − 42 Up

hsa-miR-101-3p -1.49927 2:63E − 43 2:23E − 41 Up

hsa-miR-181a-5p -1.3232 2:30E − 37 1:70E − 35 Up

hsa-miR-143-3p -1.96642 1:91E − 34 1:26E − 32 Up

hsa-miR-210 2.509065 8:42E − 34 4:99E − 32 Down


also that of DEmiRNAs in BMSC osteodifferentiation: 5-fluorouracil, anthocyanin, arsenic trioxide, ascorbate, ator-vastatin, bromocriptine, curcumin, docosahexaenoic acid,ginsenoside Rh2, glucose, hesperidin, hydroxycamptothecin(HCPT), microcystin-LR (MC-LR), mistletoe lectin-I, nar-angin, proanthocyanin, progesterone, vitamin D3, and vori-nostat (SAHA). Table 6 shows the targeting relationshipbetween 19 overlapping small molecule drugs and their reg-ulated DEmiRNAs, respectively, expressed in DPSC andBMSC osteodifferentiation process.

4. Discussion

This study identifies multiple genetic and epigenetic bio-markers common for osteogenic differentiation of DPSCsand BMSCs, including miRNAs, their target genes, transcrip-tion factors, signaling pathways, and small molecular drugsaffecting those mentioned. The overlapping miRNAs withthe same expression pattern in DPSC and BMSC osteodiffer-entiation were obtained by investigating the dysregulatedDEmiRNAs in both DPSC and BMSC osteogenesis. The

Table 1: Continued.

hsa-miR-146a-5p -3.4374 1:93E − 33 1:04E − 31 Up

hsa-miR-192-5p -1.78251 2:03E − 31 1:00E − 29 Up

hsa-miR-146b-5p 2.019632 4:61E − 30 2:10E − 28 Down

hsa-miR-335-5p 4.772695 3:12E − 28 1:32E − 26 Down

hsa-miR-382-5p 2.241351 1:20E − 25 4:76E − 24 Down

hsa-miR-4485 -6.6002 4:46E − 24 1:65E − 22 Up

hsa-miR-27b-5p 1.588671 2:77E − 21 9:68E − 20 Down

hsa-miR-10b-5p -1.21399 4:59E − 20 1:51E − 18 Up

hsa-miR-4532 -6.35341 5:95E − 19 1:86E − 17 Up

hsa-miR-34c-5p -1.82262 8:35E − 18 2:36E − 16 Up

hsa-miR-181c-5p -1.15476 1:18E − 17 3:19E − 16 Up

hsa-miR-409-3p 1.1162 1:06E − 15 2:73E − 14 Down

hsa-miR-218-5p 1.374343 2:30E − 15 5:61E − 14 Down

hsa-miR-22-5p 2.004899 2:36E − 15 5:61E − 14 Down

hsa-miR-133b -6.46427 4:93E − 14 1:08E − 12 Up

hsa-miR-3195 -5.55444 5:12E − 14 1:09E − 12 Up

hsa-miR-133a -6.42493 6:09E − 14 1:24E − 12 Up

hsa-miR-6723-5p -3.89682 7:78E − 12 1:44E − 10 Up

hsa-miR-4497 -3.78672 1:67E − 11 3:00E − 10 Up

hsa-miR-4488 -7.47261 2:43E − 11 4:11E − 10 Up

Table 2: The dysregulation and function of five overlapping DEmiRNAs (miR-101-3p, miR-143-3p, miR-145 (3p/5p), miR-34c-5p, and miR-146a-5p) in the osteodifferentiation of BMSCs and DPSCs, respectively.

BMSC osteodifferentiation DPSC osteodifferentiation

miR-101-3p

The overexpression of miR-101 promoted the osteogenic differentiationof BMSCs by targeting EZH2/Wnt/β-catenin signaling [34].

No evidence.

miR-143-3p

The downregulation of miR-143 promoted the osteogenic differentiationof BMSCs by being competitively combined with lncRNAMALAT1 and

upregulating Osterix (Osx) [35].

The downregulation of miR-143 promoted theosteogenic differentiation of DPSCs by activating the

NF-κB [36] and OPG/RANKL signaling [37].

miR-145(3p/5p)

The downregulation of miR-145 promoted the osteogenic differentiationof BMSCs by targeting semaphorin3A (SEMA3A) [38].

The downregulation of miR-145 promoted theodontoblast differentiation of DPSCs by targeting

KLF4 and OSX [39].

miR-34c-5p

The upregulation of miR-34c inhibited osteoblast differentiation ofBMSCs by targeting the Notch signaling [40].

No evidence.

miR-146a-5p

The overexpression of miR-146a inhibited the osteogenic ability ofBMSCs by targeting Smad4 gene [41].

The overexpression of miR-146a-5p promotedosteodifferentiation of DPSCs by suppressing Notch

signaling [42].


target genes of those shared DEmiRNAs were identified byconstructing the shared DEmiRNA-target gene network.The TFs among those genes, signaling pathways involved,and small molecule drugs that predictively affect those path-ways were identified as highly plausible common regulatorsof the osteodifferentiation process in both DPSCs andBMSCs. Their involvement in DPSC and BMSC osteodiffer-entiation will be discussed here.

This discussion addresses several of the eight miRNAsthat were found to be differentially expressed, with the sameexpression pattern in the course of osteogenic differentiationof DPSCs and BMSCs (miR-101-3p, miR-143-3p, miR-145(-3p/-5p), miR-19a-3p, miR-34c-5p, miR-3607-3p, miR-378e, and miR-671 (-3p/-5p)). Since there has not been anyevidence showing the involvement of miR-19a, miR-3607,miR-378e, and miR-671 in osteogenesis of stem cells, weexcluded them from further discussion in order to avoidspeculation. The possible role of the other four miRNAs(miR-101, miR-143, miR-145, and miR-34 family (miR-34a/b/c)) will be interpreted in the following part of this sec-tion. Overexpression of miR-101 was shown to targetEZH2/Wnt/β-Catenin signaling, hereby promoting the oste-ogenic differentiation in general [34]. Nevertheless, no evi-dence has been produced to corroborate the expressionpattern and either promoting or an inhibiting role of miR-101 during the osteogenesis of DPSCs. The miR-143 has been

designated with an evident inhibiting role in osteogenesisand odontogenesis. Downregulation of miR-143 has beenshown to promote the osteogenic and odontogenic differen-tiation of DPSCs by activating the NF-κB [36] andOPG/RANKL signaling [37]. The decreased expression ofmiR-143 was also shown to promote the osteogenic differen-tiation of BMSCs by being competitively combined withlncRNA MALAT1 and further upregulating the expressionof Osterix (Osx), suggesting that MALAT1-miR-143-Osxcould be an integrative element in the ceRNA network ofBMSC osteogenesis [35]. Opposite to the results shown inthese previous studies, the present study shows an upregula-tion of miR-143 during the osteogenic differentiation in bothBMSCs and DPSCs. miR-145 (-3p/-5p) appears to functionthe same way as miR-143. The downregulation of miR-145can apparently promote the odontoblast differentiation ofDPSC by targeting transcriptional factor KLF4 and OSX[39]. Also, the downregulation of miR-145 can promote oste-ogenic differentiation of BMSC by targeting semaphorin3A(SEMA3A), a known positive regulator of osteogenesis [38].Similarly to the miR-143, the expression pattern of miR-145 shown in the previous work of others is not in agreementwith the in silico data derived from the datasets analyzed inthis study, which show that miR-145 is overexpressed inthe course of osteodifferentiation of both DPSCs and BMSCs.The miR-34 family (miR-34a/b/c) has so far not been

hsa-miR-671-3p

hsa-miR-6087

hsa-miR-4516

GIGYF1

MDM2

BTG2

hsa-miR-4508hsa-miR-382-3p

hsa-miR-378e

hsa-miR-143-3p

hsa-miR-3607-3p

hsa-miR-34c-3p

hsa-miR-337-3p

hsa-miR-101-3phsa-miR-19a-3p

hsa-miR-146b-5p

hsa-miR-146a-5p

hsa-miR-145-5p

hsa-miR-145-3p

hsa-miR-671-5p

CCND1

CCND2

IGF1R

IREB2

NUFIP2

REL

THBS1

TNRC6A

UBN2

UHMK1

EIF4G2 ELK4ETNK1

HNRNPU

HNRNPUL1

LRRC58

MAP1B

NACC1

PANK3

PRDM2

PURB

REV3LRREB1SFT2D2TET3

TMBIM6

TNPO1

ZNF264

ZNF678

ALDOA

CCDC80

NF2

CBX6

DDX21

ADAM10CDKN1A

Figure 3: The overlapping 16 DEmiRNA-target gene network. The top 30 target genes with the highest degree were displayed enlarged in thenetwork.


designated as categorically pro- or counterosteogenic inDPSCs. Two surveys have shown the involvement of themiR-34 family in the osteogenic differentiation of BMSC[43, 44], however, with quite contradictory results about itsexpression pattern. Chen et al. showed that miR-34a couldinhibit osteogenesis by suppressing regulators cell cycle andcell proliferation cyclin D1, CDK4, and CDK6 [43] and thatthe inhibition of miR-34a could facilitate osteogenesis of

BMSCs. Contrary to that, Xin et al. showed that the upregu-lation of miR-34a could promote osteogenesis of BMSCs andreverse proinflammatory cytokine influence by targetingtumor necrosis factor-alpha (TNF-α) [45]. Altogether, theosteogenesis-relevant DEmiRNAs that were found overlap-ping in DPSCs and BMSCs are involved in signaling path-ways that regulate differentiation and inflammatoryprocesses by targeting their major regulators.

Table 3: The topological characteristics of the top 30 target genes with the highest degree in the 16 overlapping DEmiRNA-target genenetwork. Typically, this table would be displaying only the top 30 target genes with the highest degree; since 26 target genes were rankedwith the degree of 6, a total of 39 target genes with a degree ≥ 6 were finally listed in this table.

Name Degree Average shortest path length Betweenness centrality Closeness centrality Topological coefficient

BTG2 8 2.431705 0.003363 0.411234 0.18598065

CCND2 8 2.517604 0.003716 0.397203 0.16845654

NUFIP2 8 2.449032 0.003768 0.408325 0.18394988

THBS1 8 2.231521 0.005344 0.448125 0.17855649

UBN2 8 2.587281 0.004042 0.386506 0.17526212

GIGYF1 8 2.589493 0.003609 0.386176 0.17635862

CCND1 7 2.485899 0.002815 0.402269 0.19450361

IGF1R 7 2.426175 0.003724 0.412171 0.19710456

IREB2 7 2.631152 0.00312 0.380062 0.20047142

REL 7 2.838341 0.002574 0.352318 0.19393939

TNRC6A 7 2.514286 0.002822 0.397727 0.20702541

UHMK1 7 2.499171 0.002866 0.400133 0.20764488

MDM2 7 2.519816 0.003737 0.396854 0.19915693

ADAM10 6 2.52682 0.001899 0.395754 0.24168969

CDKN1A 6 2.667281 0.001979 0.374914 0.2337037

EIF4G2 6 2.655853 0.001796 0.376527 0.23616084

ELK4 6 2.542304 0.001911 0.393344 0.24100872

ETNK1 6 2.726636 0.001859 0.366752 0.23112339

HNRNPU 6 2.652903 0.001945 0.376946 0.23472566

HNRNPUL1 6 2.610876 0.001817 0.383013 0.23927525

LRRC58 6 2.652903 0.001945 0.376946 0.23472566

MAP1B 6 2.741382 0.001822 0.364779 0.21069923

NACC1 6 2.780092 0.002673 0.3597 0.22723133

PANK3 6 2.901382 0.002215 0.344663 0.20067454

PRDM2 6 2.437235 0.002245 0.410301 0.22983744

PURB 6 2.785622 0.002027 0.358986 0.2084477

REV3L 6 2.652166 0.001623 0.37705 0.23674815

RREB1 6 2.823594 0.002115 0.354159 0.20654912

SFT2D2 6 2.652166 0.001623 0.37705 0.23674815

TET3 6 2.52682 0.001899 0.395754 0.24168969

TMBIM6 6 2.52682 0.001899 0.395754 0.24168969

TNPO1 6 2.567373 0.002674 0.389503 0.23314389

ZNF264 6 2.627834 0.001775 0.380542 0.23815304

ZNF678 6 2.57106 0.001949 0.388945 0.23931624

ALDOA 6 2.781198 0.002859 0.359557 0.21913299

CCDC80 6 2.662488 0.00286 0.375588 0.20698404

NF2 6 3.205161 0.002464 0.311997 0.2200685

CBX6 6 2.693456 0.001811 0.37127 0.2316048

DDX21 6 2.772719 0.001683 0.360657 0.22691611


Transcription coregulator activityUbiquitin−like protein ligase binding

Ubiquitin protein ligase bindingCadherin binding

Ubiquitin−like protein transferase activityUbiquitin−protein transferase activity

GTPase bindingCell adhesion molecule binding

Transcription coactivator activityProtein serine/threonine kinase activity

Chromatin bindingProximal promoter sequence−specific DNA binding

Transcription corepressor activityAmall GTPase binding

Ras GTPase bindingProtein C−terminus binding

Helicase activityProtein heterodimerization activity

ATPase activity, coupledProtein N−terminus binding

ATPase activityUbiquitin−like protein ligase activity

Ubiquitin protein ligase activityHistone binding

DNA−dependent ATPase activityGDP binding

Ribonucleoprotein complex bindingNuclear hormone receptor binding

Phosphatidylinositol bindingp53 binding

0.0e+00 5.0e−08 1.0e−07 1.5e−07

Biol

ogic

al p

roce

ss

Count100

200

10

15

20

25

−1⁎log10 (p value)

300

400

p value

(a)

Figure 4: Continued.


After identifying 16 overlapping DEmiRNAs, the targetgenes of these 16 DEmiRNAs were also identified by con-structing the corresponding DEmiRNA-target gene net-work. Among the top 30 target genes of 16 overlappingDEmiRNAs, only some typical examples of genes will bediscussed based on the previous literature evidence regard-ing their involvement in the osteodifferentiation of DPSCsand BMSCs (e.g., REL, CCND1/2, IGF1R, THBS1, andELK4). REL gene family consists of RelA (p65), RelB, andc-Rel, subunits of NF-KB. Activation of NF-KB subunitRelA (p65) was shown to significantly promote inflamma-tion and inhibit osteodifferentiation of BMSCs by promot-ing the ubiquitination and degradation of beta-catenin,indicating that inhibitors of RelA (p65) could be a novel

therapeutic target for inhibiting inflammation and enhanc-ing osteogenesis [46]. In accordance with the findingsshown in BMSCs, studies investigating DPSCs also showedthat the downregulation of NF-KB subunit RelA (p65)enhanced the odontogenic/osteogenic differentiation ofDPSCs [47, 48]. Cyclin D genes are involved in cell cycleregulation. Silencing of cyclin D genes (CCND1/2) wasshown to arrest the cell cycle, and its overexpression hasbeen connected to the progression of the cell cycle [49].That the data regarding the effects of cell cycle regulatorson osteodifferentiation have so far been insufficiently coher-ent, CCND1/2 expression was significantly upregulated inthe course of DPSC osteodifferentiation [50, 51], whereasduring BMSC differentiation the genes involved in the cell

Cadherin bindingCell adhesion molecule binding

Ubiquitin−like protein ligase bindingUbiquitin protein ligase binding

Transcription coregulator activityChromatin binding

RNA polymerase II proximal promoter sequence−specific DNA bindingProximal promoter sequence−specific DNA binding

GTPase bindingTranscription coactivator activity

Small GTPase bindingUbiquitin−like protein transferase activity

Ras GTPase bindingUbiquitin−protein transferase activity

Protein serine/threonine kinase activityProtein C−terminus binding

ATPase activity, coupledTranscription corepressor activity

ATPase activityRibonucleoprotein complex binding

Histone bindingActin binding

Protein heterodimerization activityTranslation factor activity, RNA binding

p53 bindingPhosphatase binding

Helicase activityNuclear hormone receptor binding

Enhancer sequence−specific DNA bindingPhosphoric ester hydrolase activity

Biol

ogic

al p

roce

ss

0e+00 1e−07 2e−07 3e−07 4e−07p value

−1⁎log10 (p value)

Count100

200

300

400

10

15

20

(b)

Figure 4: The enriched biological processes involved in the osteogenic differentiation of DPSC (a) and BMSC (b).


Proteoglycans in cancer

Endocytosis

Protein processing in endoplasmic reticulum

Chronic myeloid leukemia

EGFR tyrosine kinase inhibitor resistance

Human papillomavirus infection

Viral carcinogenesis

Ubiquitin mediated proteolysis

Focal adhesion

Hippo signaling pathway

Hepatocellular carcinoma

Colorectal cancer

Yersinia infection

Signaling pathways regulating pluripotency of stem cells

Neurotrophin signaling pathway

Pancreatic cancer

Renal cell carcinoma

MAPK signaling pathway

Breast cancer

Spliceosome

Herpes simplex virus 1 infection

Cell cycle

Prostate cancer

ErbB signaling pathway

mTOR signaling pathway

Axon guidance

TNF signaling pathway

Shigellosis

FoxO signaling pathway

Path

way

0.0e+00 5.0e−09 1.0e−08 1.5e−08

8

10

12

14

−1 ⁎log10 (p value)

Count100200300

p value

Autophagy – animal

(a)



cycle were significantly downregulated [52]. IGF1R (insu-lin-like growth factor 1 receptor) can bind IGF1 with a highaffinity [53]. The previous studies regarding BMSCs alsoshowed that IGF1 promoted osteodifferentiation of BMSCsand could even be regarded as an alternative biomarker tobone morphogenetic protein-7 [54, 55]. In addition, theIGF axis (e.g., IGF-2 and IGFBP-2) was activated underosteogenic conditions in DPSCs, indicating its promotingrole in DPSC osteodifferentiation [56]. THBS1 (thrombos-pondin-1) is a major regulator of latent TGF-β activation[57], which can inhibit osteoblast differentiation in BMSCs.Accordingly, THBS1 was found to inhibit the osteodifferen-

tiation of BMSCs by activating the TGF-β pathway [58].An analogue involvement of THBS1 in osteodifferentiationof DPSCs has not been reported yet. Another modulator ofosteogenic differentiation ELK4 (ETS transcription factorELK4) was also predicted to be among the target genes of16 DEmiRNAs. Ets trasnscription factor consisting of Ets1and Ets2 targets several osteogenic markers (e.g., osteocal-cin, osteopontin, bone sialoprotein, and osteonectin) inBMSCs [59]. However, the evidence regarding the regula-tion of Ets transcription factor in the osteodifferentiationof DPSC is still lacking and thus could be a novel topicfor future research.

Proteoglycans in cancerMAPK signaling pathway

Herpes simplex virus 1 infectionHuman papillomavirus infection

Cellular senescencemTOR signaling pathway

Protein processing in endoplasmic reticulumBreast cancer

Ubiquitin mediated proteolysisRNA transport

Focal adhesionCell cycle

Hippo signaling pathwayChronic myeloid leukemia

Pancreatic cancerSignaling pathways regulating pluripotency of stem cells

EndocytosisColorectal cancer

Human T−cell leukemia virus 1 infectionp53 signaling pathway

Non−small cell lung cancerProstate cancer

Viral carcinogenesisRegulation of actin cytoskeleton

Neurotrophin signaling pathwayGastric cancer

TNF signaling pathwayHepatocellular carcinomaAMPK signaling pathway

Path

way

0e+00 2e−07 4e−07 6e−07 8e−07p value

8

10

12

−1 ⁎ log10 (p value)

Count100

200

300

Autophagy – animal

(b)

Figure 5: The enriched signaling pathway involved in the osteogenic differentiation of DPSC (a) and BMSC (b).


hsa-miR-5703hsa-miR-1471 hsa-miR-4487

hsa-miR-4429

hsa-miR-4530

hsa-miR-3610

hsa-miR-630

hsa-miR-5684

hsa-miR-520b

hsa-miR-6088

hsa-miR-3197

hsa-miR-4267

hsa-miR-4767

hsa-miR-4522

hsa-miR-4259hsa-miR-4253

hsa-miR-6076

hsa-miR-9500

hsa-miR-4519

hsa-miR-8063

hsa-miR-4516

hsa-miR-662

hsa-miR-4642

hsa-miR-5787

hsa-miR-6321

hsa-miR-4508

hsa-miR-3164


hsa-miR-640

hsa-miR-588

hsa-miR-378e

hsa-miR-4730

hsa-miR-378i

hsa-miR-6077

hsa-miR-4436a

hsa-miR-4421

hsa-miR-4293

hsa-miR-6134

hsa-miR-4282

hsa-miR-1203

CTCFLSTAT3

BRD4

SPI1

SUMO2

ERG

CHD8 JUND

CREB1

MXI1

SUPT5H LARP7

ETS1GABPA

SMC1A

NOTCH1

ZBTB7A

NR3C1

KLF1

RUNX3

CNOT3

KDM5BGATA3

MAX

SP1

ESR1

CEBPB

TFAP2A

MYCN

TAF1

PHF8TAL1

TCF3

MYC

MAZ

E2F6

FOXA1GATA1

TFAP2CTRIM28

MED1

H1F1A

RUNX1

RAD21CTCF

TCF12

KDM2B

HEY1

ELF1

AR

STAT1

EGR1

ARNTL EP300

E2F1ZNF143

MYB

YY1

DEmiRNA_up

DEmiRNA_down

TF

(a)



Among the 13 transcription factors found to be over-lapped between the top nodes of the DPSC and BMSC oste-ogenesis DEmiRNA-TF network, four TFs (RUNX1,FOXA1, HIF1A, and MYC) have been reported relevant forosteodifferentiation of stem cells. Upregulation of Runt-related transcription factor 1 (RUNX1) was shown to pro-mote osteogenesis of BMSCs by activating the canonicalWnt/β-catenin pathway [60]. RUNX1 involvement in DPSCosteogenesis has not been shown; nevertheless, anothermember of the RUNX family (RUNX2) could enhance bonedeposition and facilitate novel bone formation after trans-plantation of RUNX2-transfected DPSCs [61]. Forkheadbox protein A1/2 (FOXA1/2) has been reported as hyper-methylated in the course of BMSC osteogenesis [62] and itsknockdown promoted BMSC osteodifferentiation [63],which has still not been reported in DPSCs. Hypoxic condi-tions are known to promote cell proliferation and enhancethe osteogenic differentiation of both BMSC and DPSC byinducing the expression of HIF1A (hypoxia-inducible factor1-alpha) and upregulating the osteogenic-related genes(e.g., Oct-4, Sox2, c-Myc, RUNX2, and PPARγ2) [64–66].HIF1A overexpression in BMSC can induce the overexpres-sion of proosteogenic genes and enhance the ALP activityeven in normoxic conditions [67]. However, there is still nodirect evidence on the regulating role of HIF1A in the osteo-differentiation process of DPSC. Overexpressed c-MYC wasmainly shown to inhibit osteogenic differentiation of bothBMSC [68] and DPSC [69]. In DPSCs, stably expressed c-MYC inhibited cell growth during osteogenic differentiationand also impaired the osteogenic phenotypes (i.e., ALP activ-ity and expression of osteogenic marker genes) [69]. On the

other hand, a microarray study of gene expression in BMSCsindicated that c-MYC mediated an upregulation of dexa-methasone (DEX) expression and of the bone morphogeneticprotein 2- (BMP2-) induced osteoblast differentiation [70].Involvement of other overlapping TFs (e.g., CTCF, BRD4,MAX, ERG, KDM5B, MAZ, EP300, AR, and ESR1) in theosteogenic differentiation of BMSC and DPSC has not beenreported yet; thus, these TFs could present novel investigat-ing markers for future research.

A total of 12 overlapping signaling pathways were foundto be enriched by the target genes of DEmiRNAs that areinvolved in the DPSC osteogenesis and BMSC osteogenesis.Among these 12 signaling pathways, five were selected ashighly relevant (i.e., TNF, mTOR, Hippo, neutrophin, andsignaling pathways regulating pluripotency of stem cells), asthe most thoroughly researched and recognized as classicpathways in the osteogenesis of stem cells. Tumor necrosisfactor (TNF) signaling cascade has been shown to affect oste-ogenic differentiation in DPSCs in a dose-dependent man-ner: proosteogenic at lower doses via activating NF-κBsignaling pathway [71] and osteosuppressing at higher dosesby modulating the Wnt/β-catenin signaling [72]. In BMSCs,the osteosuppressing effect of TNF-α is exerted through thedownregulation of miR-34a and miR-21 expression [73],which are listed among the top 30 dysregulated DEmiRNAsin osteodifferentiation of BMSCs. The mTOR signaling path-way is activated by stimulation with dexamethasone andkaempferol in DPSCs and BMSCs, respectively, suggestingmTOR as a common pathway in the course of their osteogen-esis [74, 75]. Hippo signaling pathway promotes osteogenicdifferentiation in DPSCs upon regulation by SOX2 and the

hsa-miR-3178

TAF7

NFKB1

hsa-miR-3196

hsa-miR-378e


hsa-miR-133a hsa-miR-421 hsa-miR-4516 hsa-miR-4492 hsa-miR-3195hsa-miR-3141

hsa-miR-3182

hsa-miR-184

hsa-miR-4488

hsa-miR-1248

ETS1

hsa-miR-4791

hsa-miR-4497

NIPBLSP2

SRF JUND

MYOG FOXO1

TNFSF12hsa-miR-133b

CTCF

PHF8

KLF4hsa-miR-134hsa-miR-1246

hsa-miR-1468

hsa-miR-543hsa-miR-487a

calcineurin

ERGCNOT3 RING1

TCF3PIAS1

CHD8

KDM4A

GATA1

ESR1

ZNF384

TRIM24CDK9

CHD2

RAD21

SIN3ARBBP5

ZBTB7A

HAND2HOXB13

STAG1KAT7

KDM4C IRF4

TAF3OTX2NELFA

TRIM25

ATF2KLF6

NR2F1

EOMES

RELA

KDM1A

E2F1

TBP

CEBPD

GATAD1

MYCN

BRD3 POU5F1

TET2TP73

CTCFLCEBPA

MAX

GTF2F1GABPA

MYH11

CSNK2A1NR2F2

TP63MAZ

BRPF3ESR2

ZMIZ1

GATA2KMT2A

FOXA1GTF2IMAFF

TP53

HNF4AREST

GATA3CREB1

ARCEBPB

E2F4

STAT3MAFK

MYOD1TEAD4

WDR5ELF1

BCORCDK8DNMT3A

HNF4GFOSL2 EBF1

LARP7TFAP2AJUN

SIX5SFPQ

CDK7NFATC1

BRD1

TLE3

CCND2

CBFB

FOXP1

HDAC1

PRDM1BCL3

RARAVDR FOXM1

KDM2B NR1H3EGR1

CXXC1

PBX1ZBTB33HOXA4

INTS11ING5 ELL2 NRF1

INTS3E2F3SREBF2ASCL1

CHD1

MYBL2

SP1 NFE2L2

CCNT2

ASXL1ZEB1

ING2SOX9

hsa-mir-4284

NFYA HEY1

ETV1SMARCB1

KMT2D

PRDM11UBTF

BACH2ZBTB17

AHR

AFF4ZNF750

DNMT1 SPI1

MBD3

STAT1

MXI1

E2F6MED1

LMO2

XBP1

LEO1

PML

ELK1MECP2MYC

PAX5

MED26

STAT5A

TCF12

BCL6

BRF1

USF1

BATF

NOTCH1GATA4KDM5B

JMJD6

HOXA6BPTF

SMAD4

PGRSUMO1

SUMO2SMAD1

SMC1APBX3

ZNF263ZNF143

MYB

FLI1SNAI2

EZH2SMC3

DAXXTFAP2C

RUNX2TCF4CREBBP

FOSL1

SUPT5HHSF1ELF3

hsa-mir-370

hsa-miR-4521hsa-miR-4323hsa-miR-326

hsa-miR-665

hsa-mir-4485NFIC

FOXA2RUNX1

NFE2FOS

YAP1PAF1ICE1

SETD1A

EP300

RBPJ

RUNX3

EPAS1

MITF NANOG

GTF2BBCLAF1

BHLHE40

NCOR1SMAD3 USF3

LYL1SUZ12

TFAP4

KLF5HDAC2NCOA1

NR1H2

MEF2A

KLF11GRHL2

hsa-miR-210

hsa-miR-1180

IRF1JARID2

ARNTTHAP1

ZMYND8 BRD2SREBF1 YY1

TBL1XR1

NR3C1HIF1A

TAL1

TAF1NELFE

KLF1PPARG

CBX3 HCFC1

POU2F2IKZF1

GATA6HMGN3

ZNF83

RFX5PRDM5

LMNA

HIRA

WWTR1 STAR5B

RBL1 CUX1KDM3BSIX2

BRCA1JUNBRCOR1RUNX1T1

SOX2

ARNTL

NFYB FGFR1

TRIM28ATF3TCF7L2

DEmiRNA_upDEmiRNA_downTF

(b)

Figure 6: The DEmiRNA-TF interaction network involved in the osteogenic differentiation of DPSC (a) and BMSC (b).


Table 4: DEmiRNA-transcription factor (TF) interaction network involved in DPSC and BMSC osteodifferentiation. The top 30 TFs with thehighest degree of difference in the DEmiRNA-TF network of DPSCS and BMSCS osteodifferentiation were, respectively, ranked in thedescending order of degree.

The top 30 TFs with the highest degree in DEmiRNAs-TF network of DPSC osteodifferentiationName Degree Average shortest path length Betweenness centrality Closeness centrality Topological coefficient

FOXA1 30 1.954545 0.015768 0.511628 0.223996

BRD4 29 2.008021 0.009367 0.498003 0.244796

AR 29 2.029412 0.012695 0.492754 0.226894

MAX 29 1.997326 0.009458 0.500669 0.245836

EP300 28 1.981283 0.010644 0.504723 0.248155

ESR1 27 2.024064 0.01016 0.494055 0.226708

HIF1A 27 1.986631 0.01079 0.503365 0.245075

ERG 26 2.008021 0.008387 0.498003 0.265101

KDM5B 26 1.986631 0.008951 0.503365 0.259557

CTCF 25 2.034759 0.009876 0.491459 0.25205

MYC 25 2.013369 0.008083 0.49668 0.27092

RUNX1 24 2.034759 0.006933 0.491459 0.277477

SPI1 23 2.072193 0.00707 0.482581 0.250994

ZNF143 22 2.066845 0.00628 0.483829 0.255913

MAZ 22 2.050802 0.006421 0.487614 0.279362

ELF1 22 2.05615 0.005904 0.486346 0.298782

ARNTL 22 2.109626 0.005538 0.474018 0.27185

SP1 22 2.061497 0.007389 0.485084 0.278977

TCF3 21 2.088235 0.005238 0.478873 0.281495

PHF8 21 2.136364 0.004093 0.468085 0.295021

CEBPB 21 2.125668 0.006218 0.47044 0.272461

TCF12 21 2.114973 0.005147 0.472819 0.289542

TFAP2C 21 2.136364 0.006262 0.468085 0.266791

E2F1 20 2.040107 0.006168 0.49017 0.295552

TAF1 20 2.141711 0.004164 0.466916 0.29772

CTCFL 20 2.131016 0.004453 0.46926 0.301133

MED1 19 2.195187 0.003279 0.455542 0.301484

JUND 19 2.18984 0.005712 0.456654 0.264742

NOTCH1 19 2.088235 0.004576 0.478873 0.309831

KDM2B 19 2.147059 0.003495 0.465753 0.310989

LARP7 19 2.104278 0.004425 0.475222 0.316458

STAT1 19 2.125668 0.004486 0.47044 0.303774

E2F6 19 2.088235 0.00484 0.478873 0.274578

GATA3 19 2.163102 0.004673 0.462299 0.286357

TRIM28 19 2.147059 0.004839 0.465753 0.297788

The top 30 TFs with the highest degree in DEmiRNA-TF network of BMSC osteodifferentiation

Name Degree Average shortest path length Betweenness centrality Closeness centrality Topological coefficient

MAX 20 2.021505 0.003652 0.494681 0.161047

AR 20 2.010753 0.010422 0.497326 0.149037

MYC 18 2.032258 0.002722 0.492063 0.175405

ESR1 18 2.02509 0.004109 0.493805 0.154739

MAZ 17 2.050179 0.003885 0.487762 0.163923

FOXA1 17 2.057348 0.004905 0.486063 0.139836

ERG 17 2.039427 0.002605 0.490334 0.182422

HIF1A 16 2.035842 0.00274 0.491197 0.186531

CREB1 16 2.046595 0.003777 0.488616 0.172636


downstream BMP signaling [76]. In murine BMSCs, theactivation of this pathway was induced by calcitoningene-related peptide (CGRP) and it promoted osteogenicdifferentiation. Neurotrophin-mediated signaling pathwaywith rain-derived neurotrophic factor (BDNF) as a keymediator is primarily active in neurogenesis [77] but alsointensively involved in osteogenesis of both DPSCs andBMSCs. In DPSCs, the upregulation of BDNF was shownto promote the odontogenic differentiation of DPSCstowards odontoblast-like cells [78] and to indirectly pro-mote osteogenesis in BMSCs [79]. In addition, a plethoraof signaling pathways that regulate the pluripotency of stemcells provides the basic framework for any differentiation,including the endpoint bone. Among several key mediators,transforming growth factor-beta (TGF-β) signaling is ofparticular importance, being implicated in regulatory path-ways relevant for osteodifferentiation as well. The activationof the TGF-β pathway promotes osteogenesis in DPSCs byupregulating osteoblast marker genes type I collagen, alka-line phosphatase (ALP), osteocalcin (OCN), and RUNX2[80], whereas in BMSCs, its function regarding osteogenesishas been reported in controversial contexts [81, 82].

Apart from the genetic and epigenetic biomarkers, thisresearch also identified 19 small molecular drugs with asimultaneous predictive impact on the DEmiRNAs that aredysregulated in both DPSC and BMSC osteodifferentiation.This section will focus on several of those small moleculesthat exhibit clear anti-inflammatory or proosteogenic effectin BMSCs: curcumin, docosahexaenoic acid (DHA), vitaminD3, arsenic trioxide, 5-fluorouracil (5-FU), and naringin.Curcumin, a natural phenolic biphenyl compound derivedfrom the plant Curcuma longa, is an antioxidant with anti-inflammatory and osteogenesis-regulating effects [83, 84].In BMSCs, curcumin facilitates differentiation towards oste-oblasts by activating Akt/GSK3β and Wnt/β-catenin path-ways [85]. Docosahexaenoic acid (DHA) belongs to theomega-3 polyunsaturated fatty acids, and it is well-knownfor being protective against inflammation. DHA promotesthe osteodifferentiation of BMSCs by leading to the upregula-tion of proosteogenic proteins bone-sialoprotein 2 (BSP2),ALP, and RUNX2 [86]. The 1α,25-dihydroxyvitamin D3, anactive metabolite of vitamin D, is crucial for the maintenanceof calcium homeostasis and balance of bone remodeling. Itinduces differentiation of human BMSCs and dental bud

Table 4: Continued.

The top 30 TFs with the highest degree in DEmiRNAs-TF network of DPSC osteodifferentiationName Degree Average shortest path length Betweenness centrality Closeness centrality Topological coefficient

EP300 15 2.050179 0.00182 0.487762 0.20078

CTCF 15 2.043011 0.002819 0.489474 0.177864

FLI1 14 2.057348 0.001999 0.486063 0.19308

BRD4 14 2.050179 0.001697 0.487762 0.205114

TP53 13 2.064516 0.002431 0.484375 0.200512

TFAP2C 13 2.071685 0.002276 0.482699 0.183618

TCF12 13 2.060932 0.001517 0.485217 0.214543

RUNX1 13 2.071685 0.001542 0.482699 0.210065

RAD21 13 2.0681 0.002309 0.483536 0.174057

KDM5B 13 2.057348 0.001707 0.486063 0.211276

CEBPB 13 2.071685 0.003446 0.482699 0.156718

TRIM28 12 2.0681 0.001403 0.483536 0.222766

TEAD4 12 2.064516 0.001834 0.484375 0.212077

STAT1 12 2.0681 0.001237 0.483536 0.229126

SPI1 12 2.075269 0.004133 0.481865 0.206451

PHF8 12 2.071685 0.001465 0.482699 0.222712

E2F1 12 2.0681 0.001526 0.483536 0.215917

TCF3 11 2.082437 0.001244 0.480207 0.225841

REST 11 2.057348 0.00601 0.486063 0.207061

NFE2 11 2.071685 0.00123 0.482699 0.231276

MYCN 11 2.071685 0.001787 0.482699 0.231098

LARP7 11 2.082437 0.001129 0.480207 0.235147

KDM2B 11 2.075269 0.00107 0.481865 0.23975

HEY1 11 2.078853 0.001289 0.481034 0.231113

ELF1 11 2.089606 0.001158 0.478559 0.227812

EBF1 11 2.075269 0.001284 0.481865 0.220856

ARNTL 11 2.082437 0.001177 0.480207 0.22781


stem cells (DBSCs) towards osteoblasts by increasing theexpression levels of osteogenic markers (RUNX2, collagenI (Coll I), ALP, osteopontin, and osteocalcin) [87, 88]. Arse-nic trioxide (ATO) is a drug which has been commonlyused in treating acute promyeloid leukemia (APL) [89].Additionally, ATO was shown to promote the osteogenicdifferentiation of BMSC while inhibiting their adipogenic

differentiation [90, 91]. The 5-fluorouracil (5-FU) is a com-monly used drug in cancer treatment based on inducing thecell death of cycling cells [92]. BMSCs treated with 5-FUexhibited an enhanced osteodifferentiation [93]. Naringin isa dihydrotestosterone flavonoid compound known to pro-mote osteodifferentiation of BMSCs by downregulatingexpression levels of peroxisome proliferator-activated

hsa-miR-630

hsa-miR-450b-3p

GinsenosideRh2

Dihydrotestosterone (DHT)

hsa-miR-483-3p

Microcystin-LR(MC-LR)

Hesperidin

Formaldehyde

hsa-miR-188-5p

hsa-miR-17-3p

hsa-miR-135a-3p

Ascorbatehsa-miR-10a-5p

Narangin

hsa-miR-1972Hydroxycamptothecin

(HCPT)

hsa-miR-181a-2-3p

hsa-miR-224-3p

hsa-miR-671-5p

Proanthocyaninhsa-miR-423-5p

hsa-miR-574-3p

Ferulicacid

Vorinostat(SAHA)

17beta-estradiol(E2)

Medroxyprogesteroneacetate

hsa-miR-542-3p Ethanol

hsa-miR-450a-5p

Anthocyanin

Curcumin

hsa-miR-378i

hsa-miR-339-5p

Bromocriptine

hsa-miR-3658

5-Fluorouracil

hsa-miR-140-3p

hsa-miR-193b-3p

hsa-miR-143-3p

Docosahexaenoicacid

VitaminD3

hsa-miR-191-5p

hsa-miR-141-3p

hsa-miR-342-3p

Glucocorticoid

hsa-miR-4639-5p hsa-miR-4668-5phsa-miR-4767

Floxuridine(FdU)

hsa-miR-455-3p

FdUMP[10]

Cisplatin

hsa-miR-224-5phsa-miR-548d-5p

hsa-miR-525-5p

Atorvastatin

hsa-miR-146b-5p Progesterone

Arsenictrioxide

hsa-miR-34c-5p

Glucose

hsa-miR-129-5p

hsa-miR-508-3p

hsa-miR-342-5p Mistletoelectin-I

hsa-miR-491-3p

hsa-miR-369-3p

hsa-miR-520b

hsa-miR-199b-5p

Imatinibmesylate

TrichostatinA

(TSA)

DEmiRNA_upDEmiRNA_down

Small_molecule

(a)

hsa-miR-1283

hsa-miR-143-3p

Docosahexaenoicacid

hsa-miR-181a-5p

hsa-miR-3195Oleicacid

GinsenosideRh2

hsa-miR-3656

hsa-miR-487ahsa-miR-146b-5phsa-miR-370

hsa-miR-4284

Berbaminederivative (BBMD3)

hsa-miR-335-5p hsa-miR-34c-5p

Anthocyaninhsa-miR-331-3p

Curcumin

Trastuzumab

Vincristine

Bicalutamide

Lenalidomide

5-aza-2′-deoxycytidine(5-Aza-CdR)

Goserelin

Aidiinjection

Oleaeuropaea

leafextract

Trastuzumab

GinsenosideRh2

hsa-miR-210

Atorvastatin Diethylstilbestrol

Progesterone

Hydroxycamptothecin(HCPT)

hsa-miR-335-3p

hsa-miR-1973Bromocriptine

hsa-miR-671-5pNarangin

Testosterone

Ascorbatehsa-miR-1246


Marinefungal

metabolite1386A

5-Fluorouracil

has-miR-4791has-miR-184

has-miR-543Arsenictrioxide

Temozolomidehas-miR-133b

Ibandronate

Proanthocyanin

Benzenehas-miR-133a

has-miR-134

has-miR-409-3p

has-miR-329has-miR-326 Testosterone

+1,25-Dihydroxyvitamin

D3Gemcitabine

Mistletoelectin-I

has-miR-615-3p

Glucose

Hesperidin

MorphineCatechinVitamin

D3 1,2,6-Tri-O-galloyl-beta-D-glucopyranose

Gefitinib

Vorinostat(SAHA)

5-aza-2′-deoxycytidine(5-Aza-CdR)

+4-phenylbutyric

acid(PBA)

DEmiRNA_upDEmiRNA_down

Small_molecule

(b)

Figure 7: The DEmiRNA-small molecular drug targets the interaction network involved in the osteogenic differentiation of DPSC (a) andBMSC (b).


receptor γ (PPARγ) [94]. It has still not been demonstrated ifthe proosteogenic or anti-inflammatory effects of the men-tioned small molecular drugs found in BMSCs exert the sameimpact in DPSCs. Nevertheless, since the selection of candi-dates is a result of multiply derived and highly overlappingcalculations and predictions employed in this study, we areleaving room for a confident extrapolation of the drug effectson the DPSCs as well.

Apart from discussing the main outcomes, it is notewor-thy to mention the limitations of this study. Although mRNAand lncRNA expression profiles related to the osteodifferen-tiation of DPSCs and BMSCs were available in public data-bases, they were not included in the analysis. Undoubtedlyuseful raw data from these datasets did not apply to the com-mon differentially expressed miRNAs in DPSC and BMSCosteodifferentiation. Also, analyzing mRNA and lncRNAexpression profiles would have required an entirely different,amiss the scope of the intended study.

The study design of the two analyzed datasets varied interms of experimental conditions. The experimental groupused to generate that the GSE138180 dataset was treatedby odontogenic differentiation medium, whereas the controlgroup was cultured in the nondifferentiating medium fortwo weeks. Even though the DPSCs in control were notstimulated to differentiate and they were therefore regardedas naive in the original study that generated GSE138180,the culturing conditions may have still left room for sponta-neous differentiation [24]. The authors interpreted theabsence of mineral nodes in the control group, which is astandard sign of the absence of osteogenic differentiation,as an absence of spontaneous differentiation altogether. Byall means, this presents sufficient evidence that no osteodif-ferentiation took place in the control group [24]. Neverthe-less, BMSCs can spontaneously differentiate to osteoblasts[95], which imposes a question if the DPSCs can do it too.

The experimental design of the study generated theGSE107279 compared the two weeks of post-differentiationwith day 0, hereby ensuring that the control group did notspontaneously differentiate. Hereby, the control groups inthe two datasets ‘nondifferentiated while not stimulated’ inGSE138180 and ‘nondifferentiated while prior to differentia-tion’ in GSE107279 were compared as peer groups. In thelack of further osteogenesis-relevant datasets for BMSCsand DPSCs and considering the argument on the nondiffer-entiated control group provided by the authors ofGSE138180, we carried out the comparative analysis of thetwo mentioned datasets. Optimally though, experimentalset up should be established with a control group at d0(without culturing and prior to any differentiation) and theexperimental group on d14 (after culturing in the osteodif-ferentiation medium).

In addition, it is important to mention that the osteogenicinduction media (50mg/mL ascorbic acid, 100 nmol/L dexa-methasone, and 10mmol/L β-glycerolphosphate) used forGSE138180 could either induce DPSCs towards the osteo-genic differentiation and form osteoblasts, or towards theodontogenic differentiation, hereby forming odontoblasts.The authors of GSE138180 regarded the odontogenic andosteogenic differentiation as the same process and reportedan odontogenic differentiation of DPSCs in their publication[24] and osteogenic differentiation in the resulting GEOdataset summary (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE138180). In the future, potential confusionin investigating the osteogenic/odontogenic differentiationcould easily be resolved by assessing odontogenic biomarkerssuch as dentin matrix acid phosphoprotein 1 (DMP1), dentinsialophosphoprotein (DSPP), and matrix extracellular phos-phoglycoprotein (MEPE) [96]. To this day, much of theinterpretation of previous work has been limited by notassessing those differential markers [97–102]. Except for thisdifference, the genetic and epigenetic mechanisms involvedin the osteodifferentiation and odontodifferentiation ofDPSCs are common [96]. For the purpose of this study, weadopted the reported statement that DPSCs underwent oste-ogenic differentiation that was comparable to the osteogenicdifferentiation of BMSCs.

Availibility of only one time point—2 weeks of osteodif-ferentiation—for analysis of the DPSC-endpoint-bone inGSE138180 presents another limitation in assessing the grad-ual process of differentiation. Assessing genetic and epige-netic status over several time points could be crucial forunderstanding the DPSC differentiation dynamics [103].Analyzing further data points of the DPSC osteodifferentia-tion could be extremely helpful for their comparison withthe already available multiple time points of the BMSCosteodifferentiation.

Last but not least, this study presents computational pre-dictions based on the reported existing raw data. The predic-tive data have not been directly experimentally validated.Further validation of the biomarkers predicted in thisresearch could be performed by polymerase chain reaction(PCR) and western blotting assays. Despite the stated limita-tions, the biomarkers identified in the study provide potentialdirections for future surveys of genetic and epigenetic

Table 5: The 13 overlapping DEmiRNA-small molecular drugtarget interaction pairs between the DEmiRNA-small molecularinteraction networks of DPSC and BMSC osteodifferentiation.

DEmiRNAs dysregulated in both DPSCand BMSC osteodifferentiation

Small moleculartargets

hsa-miR-143-3pDocosahexaenoic

acid

hsa-miR-146b-5p

5-fluorouracil

Arsenic trioxide

Atorvastatin

Progesterone

hsa-miR-34c-5p

Arsenic trioxide

Curcumin

Glucose

hsa-miR-671-5p

5-fluorouracil

Bromocriptine


Narangin

Proanthocyanin




Table 6: The targeting relationship between 19 overlapping small molecule drugs and their regulated DEmiRNAs, respectively, expressed inDPSC and BMSC osteodifferentiation process. These 19 overlapping small molecular drugs can not only regulate the DEmiRNAsdysregulated in DPSC osteodifferentiation but also regulate the DEmiRNAs dysregulated in BMSC osteodifferentiation.

Small moleculeRegulated DEmiRNAs involved in DPSC

osteodifferentiationRegulated DEmiRNAs involved in BMSC


5-fluorouracil

hsa-miR-1246 hsa-miR-140-3p

hsa-miR-146b-5p hsa-miR-146b-5p


hsa-miR-210 hsa-miR-3658

hsa-miR-4791 hsa-miR-378i

hsa-miR-671-5p hsa-miR-423-5p

hsa-miR-574-3p

hsa-miR-671-5p

Anthocyanin hsa-miR-335-5p hsa-miR-450a-5p

Arsenic trioxide

hsa-miR-133b hsa-miR-146b-5p

hsa-miR-146b-5p hsa-miR-34c-5p

hsa-miR-184

hsa-miR-210

hsa-miR-34c-5p

Ascorbate


hsa-miR-134

hsa-miR-1973

Atorvastatin

hsa-miR-146b-5p hsa-miR-146b-5p

hsa-miR-487a hsa-miR-224-5p

hsa-miR-548d-5p

Bromocriptine hsa-miR-671-5p hsa-miR-671-5p

Curcumin

hsa-miR-210 hsa-miR-34c-5p

hsa-miR-335-5p hsa-miR-450a-5p

hsa-miR-34c-5p

Docosahexaenoic acid



hsa-miR-181a-5p hsa-miR-191-5p

hsa-miR-193b-3p

Ginsenoside Rh2




hsa-miR-370

hsa-miR-4284

Glucose


hsa-miR-133b hsa-miR-199b-5p


hsa-miR-34c-5p hsa-miR-34c-5p


hsa-miR-508-3p

hsa-miR-520b

hsa-miR-525-5p

hsa-miR-548d-5p

Hesperidinhsa-miR-133b hsa-miR-188-5p

hsa-miR-450b-3p

Hydroxycamptothecin(HCPT)

hsa-miR-1246 hsa-miR-10a-5p

hsa-miR-1973 hsa-miR-135a-3p


biomarkers as well as regulatory mediators involved in oste-ogenic differentiation of DPSCs.

Eventually, the DPSCs and BMSCs appear to sharecommon DEmiRNAs and their targets, with cohesive out-comes on the genetic and epigenetic levels in terms of theosteodifferentiation process. This places them among com-mon targets that could be directly or indirectly influencedby the mentioned selected small molecule drug candidates.The established correlations provide a base for a betterunderstanding of the common molecular alterations duringthe osteogenic differentiation of DPSCs and BMSCs. Thosecould present an immense potential if used for tissue engi-neering purposes, especially drug delivery, herewith puta-tively contributing to the future therapeutical trends inbone regeneration.

5. Conclusions

Several miRNAs (miR-101-3p, miR-143-3p, miR-145-3p,miR-145-5p, miR-19a-3p, miR-34c-5p, miR-3607-3p, miR-378e, miR-671-3p, and miR-671-5p, miR-671-3p, and miR-671-5p), genes (REL, CCND1/2, IGF1R, THBS1, and ELK4),signaling pathways (TNF, mTOR, Hippo, neutrophin, and sig-naling pathways regulating pluripotency of stem cells), tran-scription factors (RUNX1, FOXA1, HIF1A, and MYC), andsmall molecular drugs (curcumin, docosahexaenoic acid(DHA), vitamin D3, arsenic trioxide, 5-fluorouracil (5-FU),and naringin) emerged as shared regulating factors duringthe osteogenic differentiation of DPSCs and BMSCs. The bio-markers and small molecular drugs identified in this studycould be used for the genetic/epigenetic manipulation and

drug delivery of DPSCs and therefore result in novel strategiesfor bone tissue engineering.

Data Availability

The data used to support the findings of this study are avail-able from the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare that they have no conflict of interest.

Authors’ Contributions

Sebastian Gaus and Hanluo Li contributed equally as the firstauthor. Vuk Savkovic and Bernd Lethaus contributed equallyas the senior author. These three authors contributed equallyas the corresponding author: Dr. Lei Liu, Dr. Vuk Savkovic,and Prof. Dr. Bernd Lethaus.

Acknowledgments

Simin Li (CSC No.: 201608080010) and Hanluo Li (CSC No.:201308080064) were supported by the China ScholarshipCouncil (CSC) for doctor study at University Leipzig.

Supplementary Materials

Supplementary 1. File S1 The DEmiRNAs dysregulated in theosteodifferentiation of DPSC.

Supplementary 2. File S2 The DEmiRNAs dysregulated in theosteodifferentiation of BMSC.

Table 6: Continued.

Small moleculeRegulated DEmiRNAs involved in DPSC

osteodifferentiationRegulated DEmiRNAs involved in BMSC


hsa-miR-335-3p hsa-miR-181a-2-3p



Microcystin-LR (MC-LR) hsa-miR-671-5p hsa-miR-671-5p

Mistletoe lectin-Ihsa-miR-331-3p hsa-miR-369-3p


Naranginhsa-miR-671-5p hsa-miR-188-5p

hsa-miR-671-5p

Proanthocyanin


hsa-miR-133b

hsa-miR-671-5p

Progesteronehsa-miR-146b-5p hsa-miR-146b-5p


Vitamin D3

hsa-miR-133b hsa-miR-339-5p

hsa-miR-331-3p

hsa-miR-543

Vorinostat (SAHA)hsa-miR-134 hsa-miR-542-3p



http://downloads.hindawi.com/journals/bmri/2021/6697810.f1.pdf


Supplementary 3. File S3 The topological characteristics of allnodes in the 16 shared DEmiRNAs-target gene network.

Supplementary 4. File S4 The topological characteristics of allnodes in the DEmiRNAs-transcription factor interactionnetwork of DPSCs osteodifferentiation.

Supplementary 5. File S5 The topological characteristics of allnodes in the DEmiRNAs-transcription factor interactionnetwork of BMSCs osteodifferentiation.

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Shared Genetic and Epigenetic Mechanisms between the Osteogenic Differentiation … · 2021. 2. 8. · are bone marrow stem cells (BMSCs), dental pulp stem cells (DPSCs), and adipose