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Expression Profile of Long Noncoding RNAs in Human Earlobe Keloids: A Microarray Analysis.

1. Introduction

Keloids are defined as pathologically formed scars that exceed the boundary of the original wound [1]. They are also deemed as benign dermal tumors that are unique to humans. Etiologically, keloids may occur because of minor skin injury, such as body piercing and insect bites. In addition, it is widely agreed that the incidence rate of keloid is significantly higher in populations with darker skin, such as Africans and Asians. The external ear is one of the most common sites for keloid formation [2]. Many different treatment modalities such as surgical excision, intralesional corticosteroids, radiotherapy, and pressure earrings have been used for keloids [3, 4]. Although it has unclear etiology, the development of keloid could be considered as a process of abnormal wound healing, during which redundant extracellular collagen fibers as well as proteoglycans are deposited [5]. It is known that various molecular factors contribute to this process, for example, growth factors [6,7], cytokines [8], and related gene pathways [9]. Some among them maybe the key points that could stop or reverse this pathologic process. For example, transforming growth factor-[beta] (TGF-[beta]) receptor was recently reported to be a potential target in treating keloid [10]. However, deeper understanding of the molecular mechanism of keloid formation is still required for detecting critical biological factors and for the further development of effective therapies.

It is known that 90% of the human genome is transcribed to RNAs that do not code proteins (noncoding RNAs). A lot of evidence suggests that long noncoding RNA (lncRNA; >200 nucleotides) regulates protein-coding genes at the transcriptional and posttranscriptional levels, as well as transcription control [11, 12]. It is known that lncRNAs play important roles in cellular differentiation, development, and disease [11, 12]. However, for earlobe keloids, the expression or function of lncRNAs has not been studied to date.

It the present study, global expression profiles of the lncRNAs and the mRNAs from 3 pairs of earlobe keloid specimens and normal skin tissues were detected using a microarray technique, from which significantly dysregulated lncRNAs and mRNAs were screened. These results indicated that the aberrant expression levels of lncRNAs may have important roles in the development of earlobe keloid and that knowing the differently expressed lncRNAs might provide useful biomarkers for earlobe keloid therapy and diagnosis.

2. Materials and Methods

2.1. Patients and Specimens. The study procedures were approved by the Ethics Review Board of Wuhan General Hospital of Guangzhou Military Command of the People's Liberation Army and it was carried out in accordance with the Declaration of Helsinki (2008) of the World Medical Association. Keloid was diagnosed by the overgrowth of a scar that obviously exceeded the boundary of the original wound. Demographic and clinical characteristics of the patients were extracted from their medical records. Earlobe keloid specimens were obtained from the resected keloid at our outpatient clinic. The normal skin specimens were obtained from the ear of the same patient. All patients were fully informed of the aim and protocol of the study and gave written informed consent to participate in the study.

2.2. RNA Isolation, Quantification, and Quality Control. Total RNA was extracted with the mirVana miRNA Isolation Kit (Applied Biosystems) and then eluted with 100 mL of nuclease-free water. Total RNA was quantified using a NanoDrop ND-2000 spectrophotometer (Thermo Fisher Scientific) and the integrity of RNA was determined using an Agilent 2100 bioanalyzer and RNA 6000 Nano Kit (Agilent Technologies).

2.3. RNA Labeling and Array Hybridization. RNA sample preparation and microarray hybridization were performed according to Agilent One-Color Microarray-Based Gene Expression Analysis Protocol (Agilent Technologies, Santa Clara, CA, USA) with minor modifications. RNA was purified from 100 pg total RNA after removal of rRNA using RNeasy Mini Kit (Qiagen). After that, specimens were amplified and transcribed into cRNA, and cyanine-3-CTP was applied to label the cRNA (Quick Amp Labeling Kit: One-Color; Agilent). Labeled cRNA was once again purified with the RNeasy Mini Kit (Qiagen) and quantified using a NanoDrop ND-2000 spectrophotometer (Thermo Fisher Scientific).

The cRNA was fragmented and hybridized using an Agilent Gene Expression Hybridization Kit (Agilent): 0.6 [micro]g labeled cRNA was fragmented by adding 5.0 [micro]L 10x blocking agent and 1.0 [micro]L 25x fragmentation buffer, and then the mixture was heated at 60[degrees]C for 30 minutes. After that, 25 [micro]L 2x GEx Hybridization Buffer was added to stop the fragmentation reaction. Finally, 50 mL hybridization solution was dispensed into the gasket slide and assembled to the lncRNA expression microarray slide. The slides were incubated for 17 hours at 65[degrees]C in an Agilent Hybridization Oven. The hybridized arrays were washed, fixed, and scanned with using the Agilent DNA Microarray Scanner (part number, G2505C).

2.4. Data Analysis. Data were extracted with Agilent Feature Extraction software 11.7.1.1. GeneSpring GX 12.5 (Agilent Technologies) was used to normalize the quantiles of the raw data. The lncRNAs are carefully constructed using the quality-controlled, public transcriptome databases (RefSeq, UCSC Known Genes, lncRNAWiki, LNCipedia, NONCODE v4, fRNAdb v3.4, Broad lincRNA, GENCODE, etc.), as well as landmark publications. After that, lncRNAs and mRNAs with significant differential expression between the two groups were identified, and the volcano plot was drawn. Hierarchical clustering was performed using MeV 4.9.0 (http:// www.tm4.org/mev.html), and heat maps were obtained by this analysis. Gene Ontology (GO) analysis was performed based on Gene Ontology (www. geneontology.org), which provided three structured networks of defined terms that describe gene product functions. Kyoto Encyclopedia of Genes and Genomes (KEGG, http://www.genome.jp/kegg/) database was used for pathway analysis of the differentially expressed genes.

2.5. Quantitative Real-Time PCR (qRT-PCR). The total RNA was isolated using mirVana miRNA Isolation Kit (Applied Biosystems) and was then reverse-transcribed using Prime-Script RT reagent kit with gDNA Eraser (Perfect Real Time; TaKaRa). The expression of five upregulated lncRNAs and five downregulated lncRNAs was measured by qRT-PCR using SYBR Green assays (TaKaRa), and GAPDH was used as an internal control. The expression level of each lncRNA was represented as a fold change using 2- C methods. The expression levels of lncRNAs differentially expressed between earlobe keloid specimens and normal skin specimens were analyzed using Student's t-test with SPSS version 17.0 [13].

2.6. Statistics. Statistical analysis was performed with SPSS version 19.0. The differences in expression levels of tested lncRNAs and mRNAs between earlobe keloid and normal skin tissues were assessed using Student's t-test, and fold change [greater than or equal to] 2.0 and P < 0.05 were considered significant. Fisher's exact test was used for GO analysis and KEGG pathway analysis. P < 0.05 was considered significant.

3. Results

3.1. Differentially Expressed lncRNAs. The baseline data for the 3 patients (3 pairs of specimens) included in the study are shown in Table 1. In order to compare the distributions of intensities from all samples, we used a box plot to visualize the distributions of a dataset. Box-whisker plotting suggested similar distribution of the data from six RNA gene chips (Figure 1(a)). The expression profiles of 2068 lncRNAs indicated that they were differentially expressed (fold change [greater than or equal to] 2.0 and P < 0.05) between earlobe keloid specimens and normal skin specimens (shown in the lncRNA profiling). Variations in lncRNA expression among specimens were shown by volcano plotting and scatter plotting (Figures 1(b) and 1(c)). Among these lncRNAs, 1290 were upregulated more than twofold in the earlobe keloid specimens compared to the normal skin specimens, while 778 lncRNAs were downregulated more than twofold. lncRNA expression data are deposited at Gene Expression Omnibus under accession number GSE83286. The top 20 differentially expressed lncRNAs are listed in Tables 2 and 3. Finally, to infer the relationships among specimens, hierarchical clustering was performed to show distinguishable lncRNA expression patterns among samples (Figure 1(d)).

3.2. Differentially Expressed mRNAs. A total of 1511 mRNAs were differentially expressed between the two tissues (fold change [greater than or equal to] 2.0 and P < 0.05). A total of 1092 of 1511 mRNAs were expressed significantly higher in earlobe keloid specimens and 419 mRNAs were expressed significantly lower compared to normal skin specimens (shown in the mRNA profiling). mRNA expression data are deposited at Gene Expression Omnibus under accession number GSE83286. The top 20 differentially expressed mRNAs are listed in Supplemental Tables 1 and 2 in Supplementary Material available online at http://dx.doi.org/10.1155/2016/5893481. Variations in the mRNA expression among specimens were shown by volcano plotting and scatter plotting (Figures 2(a) and 2(b)). Hierarchical clustering showed that mRNA expression modes among samples were distinguishable (Figure 2(c)).

3.3. GO Analysis. The GO project is a collaborative effort to construct and use ontologies to facilitate the biologically meaningful annotation of genes and their products in a wide variety of organisms [14]. We performed GO analysis for lncRNAs to determine molecular function, biological processes, and cellular components. For molecular function (Figure 3(a)), calcium ion binding (GO:0005509) had the highest transcriptional domain coverage (TDC, 17.2%) in upregulated transcripts, while oxidoreductase activity (GO:0016491; TDC, 16.4%) was highest in downregulated transcripts. In biological processes (Figure 3(b)), it was found that upregulated genes were enriched most in the process of cell adhesion (GO:0007155; TDC, 18.8%). In contrast, downregulated genes were enriched most in the process of transmembrane transport (GO:0007155; TDC, 16.9%). In the cellular components (Figure 3(c)), it was detected that integral to membrane (GO:0016021) had the highest enrichment of upregulated genes (TDC, 39.5%), and mitochondria had the highest enrichment of downregulated genes (GO:0005886; TDC, 27.7%).

3.4. KEGG Analysis. KEGG pathway enrichment analysis was used for differentially expressed genes to identify pathways represented among the lncRNAs identified in the earlobe keloid gene expression signature. KEGG analysis suggested that 24 pathways were significantly correlated with upregulated gene expression. The focal adhesion pathway had the highest enrichment of increased transcription (TDC, 27.8%) and comprised 35 targets genes. Pathway analysis also revealed that 11 pathways corresponded to downregulated transcripts and that the most enriched network was metabolic pathways (TDC, 49.2%), which comprised 30 target genes (Figure 3(d)). Many of these pathways are reported to be associated with keloid, including the gene category focal adhesion pathway [15], TGF-[beta] signaling pathway [16-18], mitogen-activated protein kinase (MAPK) pathway [19], and gap junction pathway [20, 21].

3.5. QRT-PCR Validation. To verify the microarray data, five upregulated lncRNAs (NONHSAT120157, NONHSAT062994, NONHSAT016933, NR.024360.1, and FR39263) and five downregulated lncRNAs (NONHSAT053431, FR244962, ENST00000601148, TCONS_ 00022478, and XR244388.1) were randomly selected from the differentially expressed lncRNAs. We detected the expression levels of these lncRNAs in 10 earlobe keloids tissues and normal skin samples (Supplemental Table 3) using qRT-PCR. As shown in Figure 4, the qRT-PCR results and microarray data are consistent.

4. Discussion

Emerging evidence shows that a set of noncoding RNAs (for example, miRNA) is involved in the mechanism of keloid formation [22-25]. lncRNAs are larger than miRNAs and have more complex structure. Deregulated expression of lncRNA disrupts cellular physiology and then leads to pathology [26-28]. Thus, we suggest that lncRNAs may play crucial roles in many biological processes and are vital to the formation of earlobe keloids. However, the profile and biological function of lncRNAs for earlobe keloid remain largely unknown. Thus, in the present study, we established the expression profile of lncRNAs in human earlobe keloids.

We analyzed lncRNA and mRNA expression profiles in the tissues of earlobe keloid and control tissues to reveal the potential roles of lncRNAs in the pathogenesis of earlobe keloid. High-throughput microarray techniques uncovered differential expression between 3 pairs of earlobe keloid and normal skin specimens. We identified that 1290 lncRNAs and 1092 mRNAs were upregulated and 778 lncRNAs and 419 mRNAs were downregulated in all 3 earlobe keloid and normal tissues (fold change [greater than or equal to] 2.0, P < 0.05). GO and KEGG pathway analysis were used to explore the possible biological functions and potential mechanisms of lncRNAs and mRNAs in earlobe keloids. In fact, Liang and colleagues have previously identified differential expression of lncRNAs and mRNAs between 3 pairs of keloid and normal skin tissue by microarray (32). Compared with their results, our study has several differences. First, tissues used here were earlobe keloid and normal specimens, and the expression profiles of lncRNAs were significantly different from the previous results. Second, to verify the microarray data, the expression levels of five upregulated lncRNAs and five downregulated lncRNAs were detected in 10 earlobe keloids tissues and normal skin samples using qRT-PCR, and the results were consistent with microarray data.

An integrative method including pathway was developed to identify possible functional relationships between the different RNA molecules. Based on the differentially expressed mRNAs, pathway analysis revealed which biological functions and mechanisms were involved in earlobe keloid formation. Our results suggest that different biological processes, such as cell-cell adhesion, cell migration, cell death, cell junction formation, epithelial to mesenchymal transition (EMT), TGF-[beta], and MAPK, are among the significantly enriched mRNAs. Most of these pathways are involved in the process of tissue fibrosis. For example, studies in a wide range of experimental models have revealed that TGF-[beta] is a central mediator of keloid fibrogenesis. It is reported that Loureirin B attenuated the contraction of fibroblasts which was induced by TGF-[beta] in hypertrophic scar formation (33). Yan et al. have reported that EMT plays crucial roles in keloid formation [29]. Gobin et al. have shown that emodin-loaded liposomes decrease survival rate of keloids which express high levels of receptor tyrosine kinase (RTK) (included in the focal adhesion pathway) [30]. Among these related pathways, we found that focal adhesion, extracellular matrix receptor interaction, cell adhesion molecules, and gap junction-associated pathway showed significant changes in upregulated and downregulated mRNAs. For example, 35 differentially expressed mRNAs were involved in the focal adhesion pathway and 16 differentially expressed mRNAs were enriched in cell adhesion molecules. Otherwise, 7 of which were downregulated in the tight junction related pathway. These results indicated that cell adhesion and tight associated signaling may play an important role in the mechanism of earlobe keloid formation, which is not identified by other researches.

Our study used microarray data to analyze systematically and comprehensively differentially expressed lncRNAs and mRNAs between normal skin and earlobe keloid tissues. Many differentially expressed lncRNAs could play a vital role in regulating earlobe keloid formation through various pathways. In our present study, we found that TGF-[beta], MAPK, cell tight, and adhesion related signaling series mRNAs may interact with IncRNAs. Previous reports demonstrated that ADAM proteins are involved in cell adhesion, cell fusion, cell signaling, and proteolysis. ADAM33 is a member of ADAM family that is associated with keloid scars in the northeastern Chinese population (36). ADAM12 are reluctant to adhere to fibronectin, a key ECM protein in keloids (37). Patients suffering from collagen VI related myopathies caused by mutations in COL6A1, COL6A2, and COL6A3 often also display skin abnormalities, like formation of keloids or "cigarette paper" scars, dry skin, striae rubrae, and keratosis pilaris (follicular keratosis) (38). Keloid fibroblasts were propagated in culture and their proliferative behaviour and response to the epidermal growth factor (EGF) were studied (39). Our results found that NONHSAT016934, NONHSAT016933, NONHSAT016928, and NONHSAT077639 expressions were increased, whereas NONHSAT097800 expression was decreased in earlobe keloid and normal tissues. These lncRNAs were associated with the related genes of keloid (ADAM12, COL6A3, and EGF). We will carry out further studies of these differentially expressed lncRNAs to establish their functions in earlobe keloid formation.

In conclusion, we studied the differential expression profile of lncRNAs and mRNAs in earlobe keloid and normal skin tissues. Our microarray analysis indicated that lncRNAs are involved in the pathological process of earlobe keloid formation. Therefore, subgroup analysis of lncRNAs should be performed to explore this relationship in the future. In addition, we will select numbers of samples to deepen the research into the lncRNA molecular mechanism and biochemical function in order to provide a novel accurate method for therapy of earlobe keloid.

http://dx.doi.org/10.1155/2016/5893481

Competing Interests

All the authors declare that they have no competing interests to disclose.

Authors' Contributions

Liang Guo and Kai Xu contributed equally to this study.

Acknowledgments

This work was supported by a grant from the National Natural Science Foundation of China (Grant nos. 81301638 and 81301639) and a grant from the Natural Science Foundation ofHubei Province (Grant no. 2012FFB06808).

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Liang Guo, (1) Kai Xu, (1) Hongbo Yan, (1) Haifeng Feng, (1) Linlin Chai, (2) and Guozheng Xu (3)

(1) Department of Plastic Surgery, Wuhan General Hospital of Guangzhou Military Command of Chinese PLA, Wuhan, Hubei, China

(2) Department of Plastic and Reconstructive Surgery, Southwestern Hospital, Third Military Medical University, Chongqing, China

(3) Department of Neurosurgery, Wuhan General Hospital of Guangzhou Military Command of Chinese PLA, Wuhan, Hubei, China

Correspondence should be addressed to Linlin Chai; 442160153@qq.com and Guozheng Xu; xuguozhenboss@sina.com

Received 8 July 2016; Revised 14 September 2016; Accepted 1 November 2016

Academic Editor: Kui Li

Caption: Figure 1: Expression profiles of lncRNAs in earlobe keloid and normal skin specimens. (a) Box-whisker plots of lncRNAs showed the distributions of intensities from all samples. (b) Volcano plots showed variation in lncRNA expression. The vertical lines correspond to 2.0-fold upregulation and downregulation and the horizontal line represents a P value of 0.05. (c) Scatter plots show variation in lncRNA expression. (d) Hierarchical clustering shows lncRNA expression profiling. Cluster analysis arranges samples into groups based on their expression levels, which allows us to hypothesize the relationships among samples. "Red" indicates highly relative expression, and "green" indicates lowly relative expression.

Caption: Figure 2: Expression profiles of mRNAs in earlobe keloid and normal skin specimens. (a and b) Volcano and scatter plots show differences in expression. The vertical green lines delimit 2.0-fold upregulation and downregulation. Red plots represent mRNAs with >2.0-fold change and corrected P value < 0.05. (c) Hierarchical clustering shows mRNA expression profiling. Cluster analysis arranges samples into groups based on their expression levels, which allows us to hypothesize the relationships among samples. "Red" indicates highly relative expression, and "green" indicates lowly relative expression.

Caption: Figure 4: Quantitative RT-PCR validation of 10 differentially expressed lncRNAs. (a) Comparison of fold change [[log.sub.10](S/N)] oflncRNAs between microarray and quantitative RT-PCR results (S: earlobe keloid specimens; N: normal skin specimens). (b) Relative expression levels of lncRNAs in 10 other pairs of earlobe keloid and normal skin specimens (P < 0.05).
Table 1: Baseline data of included patients.

Case   Age       Gender   Reason of     Size of keloid    History of
       (years)            skin injury   (cm x cm x cm)    keloid
                                                          (months)

1      21        Female   Earlobe       2.0 x 1.3 x 0.8   10
                          piercing
2      34        Female   Earlobe       1.8 x 1.5 x 1.2   14
                          piercing
3      24        Female   Earlobe       2.7 x 2.0 x 1.5   17
                          piercing

Table 2: The top 20 upregulated lncRNAs.

Seq. name            Source       Fold change   Chrom.   Strad.

NONHSAT120157      NONCODE v4       302.566      chr7      --
NONHSAT062994      NONCODE v4       198.76      chr19      --
ENST00000424523      Ensembl        1878763      chr7      +
NONHSAT016934      NONCODE v4      121.1942     chr10      --
NONHSAG007229      NONCODE v4      98.20973     chr10      --
NONHSAT135001      NONCODE v4      85.73119      chr9      +
NONHSAT016933      NONCODE v4      66.81899     chr10      --
NONHSAT033754      NONCODE v4      59.65379     chr13      +
NONHSAT102388      NONCODE v4      57.30576      chr5      +
NONHSAT016928      NONCODE v4      56.89644     chr10      --
NONHSAT076769      NONCODE v4      55.34357      chr2      +
NONHSAT033252      NONCODE v4      45.90168     chr13      --
NONHSAG013256      NONCODE v4       45.0158     chr13      --
ENST00000557618      Ensembl       40.71083     chr14      +
ENST00000597626      Ensembl       37.49051     chr21      +
NONHSAG030448      NONCODE v4      36.29881      chr2      --
NONHSAT056875      NONCODE v4      34.17572     chr18      +
NONHSAG052055      NONCODE v4      32.53344      chr9      +
NONHSAT100815      NONCODE v4      31.91256      chr5      +
NONHSAT077639      NONCODE v4      30.05823      chr2      --

Seq. name          txStrat      txEnd     Associated
                                           gene name

NONHSAT120157     37946864    37949441       SFRP4
NONHSAT062994     18896928    18897844       COMP
ENST00000424523   92484223    92546465
NONHSAT016934     127823937   127843874     ADAM12
NONHSAG007229     134634754   134637851      TTC40
NONHSAT135001     131745793   131747541     NUP188
NONHSAT016933     127779305   127798357     ADAM12
NONHSAT033754     50191636    50192101
NONHSAT102388     79377827    79379011       THBS4
NONHSAT016928     127700956   127703336     ADAM12
NONHSAT076769     216476099   216669548    LINC00607
NONHSAT033252     38137358    38144948       postn
NONHSAG013256     38136835    38145672       postn
ENST00000557618   60981837    61021634
ENST00000597626   35287852    35341659
NONHSAG030448     216232403   216237205       FN1
NONHSAT056875      907552      909671       ADCYAP1
NONHSAG052055     34084331    34096676      DCAF12
NONHSAT100815     28524293    28602803
NONHSAT077639     238241611   238243429     COL6A3

Table 3: The top 20 downregulated lncRNAs.

Seq. name             Source       Fold change Chrom.     Strad.

NONHSAT053431       NONCODE v4     22.78803    chr17        +
NONHSAT030286       NONCODE v4     17.52123    chr12        +
FR244962            fRNAdb v3.4    16.8388      chr7        +
ENST00000601148       Ensembl      15.31924    chr19        +
TCONSJ2.00026076   Broad lincRNA   13.31326     chr7        +
FR193036            fRNAdb v3.4    12.53563    chr19        --
NONHSAT125631       NONCODE v4     12.31555     chr8        +
TCONSJ2.00016248   Broad lincRNA   12.02637    chr20        +
NONHSAT030224       NONCODE v4     12.02533    chr12        --
NONHSAT076673       NONCODE v4     11.6689      chr2        --
NONHSAT137402       NONCODE v4     11.66708     chrX        +
ENST00000580420       Ensembl      11.61363    chr18        +
FR174595            fRNAdb v3.4    11.10483     chr6        +
NONHSAT077942       NONCODE v4     11.03293     chr2        --
NONHSAT060814       NONCODE v4     10.87916    chr19        +
NONHSAT097800       NONCODE v4     10.56074     chr4        +
NONHSAT070090       NONCODE v4     10.32572     chr2        +
TCONS_00022478     Broad lincRNA   10.21703    chr14        +
ENST00000556024       Ensembl      9.802968    chr14        --
NONHSAT102735       NONCODE v4     9.773005     chr5        +

Seq. name          txStrat      txEnd     Associated
                                           gene name

NONHSAT053431      37395854   37400623      FBXL20
NONHSAT030286      101988749  102021958     MYBPC1
FR244962           31551811   31552010
ENST00000601148    51843949   51847370
TCONSJ2.00026076   80804833   80828289
FR193036           56526608   56527152
NONHSAT125631      25398695   25408293
TCONSJ2.00016248   37230676   37256614
NONHSAT030224      100560001  100562998    GOLGA2P5
NONHSAT076673      211074313  211081443      ACADL
NONHSAT137402      69454505   69457167       AWAT1
ENST00000580420    29522538   29524119
FR174595           118888744  118889041
NONHSAT077942      242455829  242457154
NONHSAT060814      7410710     7411049
NONHSAT097800      110897243  110898692       EGF
NONHSAT070090      36991437   36993016        vit
TCONS_00022478     38205181   38208450
ENST00000556024    38025363   38036300
NONHSAT102735      90142207   90144638       GPR98

Figure 3: (a) Top 12 enriched GO terms for differentially expressed
mRNAs for molecular function. The bar plot shows the
transcriptional domain coverage. (b) Top 12 enriched GO terms for
differentially expressed mRNAs for biological processes. The bar
plot shows the transcriptional domain coverage. (c) Top 12 enriched
GO terms for differentially expressed mRNAs for cellular
components. The bar plot shows the transcriptional domain coverage.
(d) The results of KEGG pathway enrichment analysis. The bar plot
shows the transcriptional domain coverage of the enrichment
pathway.

Transcriptional domain coverage (%)

(a) GO molecular function

Upregulated transcript

Cytokine activity                                         4.1%
Collagen binding                                          4.4%
Integrin binding                                          4.7%
Metalloendopeptidase activity                               5%
Sugar binding                                             5.5%
Heparin binding                                           5.5%
GTPase activity                                           5.5%
Receptor binding                                          6.1%
Extracellular matrix structural constituent               6.7%
GTP binding                                               8.5%
Peptidase activity                                       11.7%
Calcium ion binding                                      17.2%

Downregulated transcripts

Alpha-tubulin binding                                     1.8%
Hydrolase activity                                        2.7%
ATPase activity                                           2.7%
Calcium channel activity                                  2.7%
Oxygen binding                                            2.7%
Aromatase activity                                        3.6%
Monooxygenase activity                                    3.6%
Flavin adenine dinucleotide binding                       5.5%
GTPase activator activity                                 6.4%
Structural constituent of ribosome                        9.1%
Binding                                                  14.5%
Oxidoreductase activity                                  16.4%

Transcriptional domain coverage (%)

(b) GO biological process

Upregulated transcript

Small GTPase mediated signal transduction                 5.4%
Platelet activation                                       5.6%
Positive regulation of cell proliferation                 6.5%
Negative regulation of cell proliferation                 6.7%
Skeletal system development                               6.7%
Axon guidance                                             8.1%
Nervous system development                                8.1%
Blood coagulation                                         8.7%
Proteolysis                                                 9%
Multicellular organismal development                     13.9%
Signal transduction                                      15.9%
Cell adhesion                                            18.8%

Downregulated transcripts

Response to hypoxia                                       5.1%
Cellular nitrogen compound metabolic process              5.9%
Endocrine pancreas development                            7.6%
Viral transcription                                       7.6%
Viral infectious cycle                                    7.6%
Translational elongation                                  7.6%
Translational termination                                 8.5%
Viral reproduction                                        9.3%
Translation                                              10.2%
Gene expression                                            11%
Cellular protein metabolic process                         11%
Transmembrane transport                                  16.9%

Transcriptional domain coverage (%)

(c) GO cellular component

Upregulated transcripts

Golgi membrane                                            5.1%
Cell surface                                              5.6%
Extracellular matrix                                      6.8%
Proteinaceous extracellular matrix                        7.8%
Endoplasmic reticulum                                    11.3%
Integral to plasma membrane                              11.6%
Golgi apparatus                                          11.9%
Extracellular space                                      13.8%
Extracellular region                                     29.2%
Membrane                                                   35%
Plasma membrane                                          35.5%
Integral to membrane                                     39.5%

Downregulated transcripts

Synaptic vesicle                                          2.7%
Spectrin                                                  2.7%
Cytosolic small ribosomal subunit                         3.6%
Keratin filament                                          4.5%
Nucleosome                                                4.5%
Tight junction                                            4.5%
Cell cortex                                               6.2%
Mitochondrial matrix                                      7.1%
Microsome                                                 8.9%
Endoplasmic reticulum membrane                           14.3%
Integral to plasma membrane                              23.2%
Mitochondrion                                            27.7%

Transcriptional domain coverage (%)

(d) KEGG

Upregulated transcript

TGF-beta signaling pathway                                9.5%
Arrhythmogenic right ventricular cardiomyopathy (ARVC)    9.5%
Axon guidance                                            10.3%
Hypertrophic cardiomyopathy (HCM)                        11.1%
Protein digestion and absorption                         11.1%
Gap junction                                             11.1%
Amoebiasis                                               11.9%
Dilated cardiomyopathy                                   11.9%
Cell adhesion molecules (CAMs)                           12.7%
Phagosome                                                14.3%
ECM-receptor interaction                                 18.3%
Focal adhesion                                           27.8%

Downregulated transcripts

Butirosin and neomycin biosynthesis                       3.3%
Glyoxylate and dicarboxylate metabolism                   3.3%
Aldosterone-regulated sodium reabsorption                 4.9%
Carbohydrate digestion and absorption                     4.9%
Linoleic acid metabolism                                  4.9%
Fructose and mannose metabolism                           6.6%
Long-term depression                                      6.6%
Tight junction                                           11.5%
Ribosome                                                 14.8%
Systemic lupus erythematosus                             16.4%
Metabolic pathways                                       49.2%

Note: Table made from bar graph.
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Article Details
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Title Annotation:Research Article
Author:Guo, Liang; Xu, Kai; Yan, Hongbo; Feng, Haifeng; Chai, Linlin; Xu, Guozheng
Publication:BioMed Research International
Article Type:Clinical report
Date:Jan 1, 2017
Words:5258
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