Open Access

Gene expression profiling analysis of keloids with and without hydrocortisone treatment

  • Authors:
    • Hongyi Wang
    • Liangliang Quan
    • Jiulong Liang
    • Jie Shi
    • Tao Qiu
    • Ye Zhang
    • Yang Wang
    • Qiang Hui
    • Yu Zhang
    • Kai Tao
  • View Affiliations

  • Published online on: October 3, 2017     https://doi.org/10.3892/etm.2017.5263
  • Pages: 5283-5288
  • Copyright: © Wang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

The present study aimed to investigate the genetic effects of hydrocortisone (HC) treatment on keloids and screen medicines to be used in a combination therapy of keloids with HC. The dataset GSE7890 was downloaded from Gene Expression Omnibus. It contained data regarding 4 fibroblast samples from normal scar tissue and 5 samples from keloid tissue with HC treatment, as well as 5 samples from normal scar and 5 samples from keloids without HC treatment. Following the identification of differentially expressed genes (DEGs), the functions of these DEGs were analyzed by Gene Ontology (GO) and pathway enrichment analyses. Furthermore, adverse effects of HC were identified using WebGestalt. Additionally, candidate small molecule drugs associated with keloids were selected from a connectivity map database. A total of 166 and 41 DEGs, with and without HC treatment respectively, were only present in dermal fibroblasts from keloids (termed genesets A and B, respectively). A set of 26 DEGs was present following both treatments (geneset C). A number of DEGs in geneset B (COL18A1 and JAG1) were associated with endothelial cell differentiation. However, in genesets A and C, certain genes (CCNB1 and CCNB2) were involved in the cell cycle and p53 signaling pathways, and a number of genes (IL1R1 and COL1A1) were associated with bone loss. Additionally, numerous small molecule drugs (including acemetacin) were associated with keloids. Thus, it has been determined that HC may treat keloids by targeting genes associated to endothelial cell differentiation (COL18A1 and JAG1). However, HC has a number of adverse effects, including bone loss. Acemetacin may be applied in a combination therapy, along with HC, to treat keloids.

Introduction

Keloids are benign fibrotic tumors of the dermis that form during a prolonged wound healing process (1). Keloids exhibit aggressive dermal growth beyond the boundaries of the original margins of wounds, causing pain, pruritis and contractures. They are a cosmetic and psychological burden to patients (2).

The effect of one type of glucocorticoid, hydrocortisone (HC), on keloids has previously been investigated. HC is known to alter the chemistry and morphology of connective tissue cells and to hinder the production of intercellular substances, including collagenous fiber and glycosaminoglycan (3). It may also decrease the maximum density of keloid-derived fibroblasts (4), increase proline transport (5), lower prolyl hydroxylase activity, reduce the rate of collagen synthesis (6), enhance apoptosis rates (7) and diminish hyaluronan accumulation (8).

Microarray studies identify a broad spectrum of differentially regulated genes in biological samples under genomic sequencing, cloning, cDNA or PCR approaches (9). In 2008, Smith et al (10) conducted a bioinformatic analysis on RNA obtained from fibroblasts cultured from normal scars and keloids grown in the absence and presence of HC. The results indicated that there was elevated expression of a number of insulin-like growth factor (IGF)-binding and IGF-binding related proteins, in addition to decreased expression of a set of Wnt pathway inhibitors and numerous interleukin (IL)-1-inducible genes. Furthermore, it was observed that IGF binding protein (IGFBP)-3 and connective tissue growth factor (CTGF) were associated with the increase of fibroblast and collagen deposition and were overexpressed in keloid fibroblasts only in the presence of HC, suggesting that glucocorticoid resistance of HC is involved in the pathogenesis of keloids formation (10). However, the adverse effects of HC during its treatment on keloids and the drugs that may potentially be used to weaken or reverse these adverse effects, remain unknown.

The present study used the microarray data collected by Smith et al (10) to identify differentially expressed genes (DEGs) in fibroblasts cultured from keloids treated with or without HC. A Gene Ontology (GO) enrichment analysis was performed on DEGs, which were potentially associated with the positive efficacy of HC, and a pathway enrichment analysis for DEGs that may be associated with adverse effects of HC was completed. Furthermore, the adverse effects of HC were analyzed and small molecule drugs that may reduce the occurrence of adverse effects were screened from the connectivity map (CMAP) database. The aim of the present study was to elucidate the molecular mechanisms of HC treatment on keloids and provide novel information for the clinical treatment of this disease.

Materials and methods

Affymetrix microarray data

The gene expression profile data of GSE7890 (10) was downloaded from the Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo/) database, which was based on the platform of GPL570 [HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array (Affymetrix Inc., Santa Clara, CA, USA). A total of 19 primary cultures of dermal fibroblast samples were included in this dataset, including 4 samples from normal scar tissue and 5 samples from keloids treated with 1.5 µM HC; as well as 5 samples from normal scar and 5 samples from keloids that did not undergo HC treatment.

Affymetrix CEL files and the probe annotation files were downloaded and the gene expression data of all samples were preprocessed via background correction, quantile normalization and probe summarization using the Affy software (version 1.30.0) package of Bioconductor (available at http://www.bioconductor.org/packages/2.8/bioc/html/affy.html) (11).

DEGs screening

Linear Models for Microarray Data package (version 3.22.7) (12) of Bioconductor (available at http://www.bioconductor.org/packages/3.0/bioc/html/limma.html) was used to identify genes that were differentially expressed in dermal fibroblasts from keloids and those from normal scars. The raw P-value was adjusted into False Discovery Rate (FDR) by the Bonferroni method (13) in a multtest package (version 2.20.0) of Bioconductor (http://www.bioconductor.org/packages/2.14/bioc/html/multtest.html). The |log2FC (fold change)|>1 and FDR <0.05 were selected as the cut-off criteria.

Functional classification of DEGs

GO functional enrichment analysis of DEGs was performed to interpret their biological significance, via the Database for Annotation, Visualization and Integrated Discovery (http://david.abcc.ncifcrf.gov/) (14). P<0.01 was used as the cut-off criterion.

Pathway enrichment analysis of DEGs was performed using a Kegg Orthology Based Annotation System, version 2.0 (http://kobas.cbi.pku.edu.cn) (15). P<0.05 was used as the cut-off criterion.

Identification of potential diseases associated with DEGs

Potential diseases associated with the DEG genesets A and C were identified using the WEB-based GEne SeT AnaLysis Toolkit (WebGestalt; www.webgestalt.org) (16) with a cut-off criterion of P<0.05.

Prediction of small molecule drugs

CMAP database (www.connectivitymap.org/cmap) (17) was used to predict candidate small molecule drugs targeting DEGs genesets A and C. An enrichment score between 0.9–1 was selected as the cut-off criterion. The closer to −1 the enrichment score was, the stronger the effect of the drug on the disease.

Results

Identification of DEGs

A total of 192 DEGs with HC treatment (50 upregulated and 142 downregulated) and 67 DEGs without HC treatment (15 upregulated and 52 downregulated) were screened from dermal fibroblasts in keloids and compared with normal scar tissue.

Among them, 166 DEGs were only present in the dermal fibroblasts from keloids treated with HC (geneset A), 41 DEGs were only present in dermal fibroblasts from keloids with no HC treatment (geneset B) and 26 DEGs were common in dermal fibroblasts from keloids with and without HC treatment (geneset C; Fig. 1).

Functional annotation of DEG

To investigate the potential molecular functions in keloid fibroblasts affected by HC, a GO functional enrichment analysis of the DEGs in geneset B, which were potentially associated with the positive efficacy of HC, was performed. According to the GO functional enrichment analysis, DEGs in geneset B were significantly enriched in 9 GO terms (all P<0.01), including endothelial cell differentiation (COL18A1, HOXB5 and JAG1) and regulation of cell proliferation (DLC1, COL18A1 and JAG1; Table I). Furthermore, 21.28% of DEGs were associated with the regulation of cell proliferation and 8.51% of DEGs with endothelial cell differentiation (Fig. 2).

Table I.

Enriched GO terms for differentially expressed genes in geneset B.

Table I.

Enriched GO terms for differentially expressed genes in geneset B.

TermDescriptionCountP-valueGenes
GO:0045446Endothelial cell differentiation4 P<0.001aCOL18A1, HOXB5, JAG1, NR2F2
GO:0042127Regulation of cell proliferation10 P<0.001aDLC1, COL18A1, NCK2, TBX3, NKX3-1, PTN, JAG1, PPAP2A, CLEC11A, IGFBP5
GO:0008285Negative regulation of cell proliferation6 0.001937aDLC1, COL18A1, NCK2, NKX3-1, PPAP2A, IGFBP5
GO:0060429Epithelium development5 0.002412aDLC1, COL18A1, HOXB5, JAG1, NR2F2
GO:0001568Blood vessel development5 0.003177aCOL18A1, TBX3, MMP19, JAG1, NR2F2
GO:0001944Vasculature development5 0.003465aCOL18A1, TBX3, MMP19, JAG1, NR2F2
GO:0030855Epithelial cell differentiation4 0.004833aCOL18A1, HOXB5, JAG1, NR2F2
GO:0009952Anterior/posterior pattern formation4 0.005134aTBX3, HOXB5, NKX3-1, NR2F2
GO:0030334Regulation of cell migration4 0.008627aDLC1, COL18A1, JAG1, IGFBP5

a P<0.01. Geneset B represents the differentially expressed genes specifically present in dermal fibroblasts from keloids without hydrocortisone treatment, specifically, genes that were not differentially expressed following HC treatment. GO, Gene Ontology.

To identify the potential dysregulation pathways associated with HC treatment and those that were unaffected by HC, a pathway enrichment analysis of the DEGs in geneset A (specifically, novel DEGs following HC treatment) and genes in geneset C (namely, genes that were not affected by HC), was performed. Based on this pathway enrichment analysis, the DEGs in genesets A and C were significantly enriched in two pathways: Cell cycle (CCNB1, MAD2L1 and BUB1) and p53 signaling pathway (CCNB1, RRM2 and PERP; Table II; P<0.05).

Table II.

Results of pathway enrichment analysis for differentially expressed genes in genesets A and C.

Table II.

Results of pathway enrichment analysis for differentially expressed genes in genesets A and C.

TermDescriptionCountP-valueGenes
hsa04110Cell cycle9 4.29E-05aCCNB1, MAD2L1, CCNB2, DBF4, BUB1, TTK, CDC20, CDC25C, CCNA2
hsa04115p53 signaling pathway5 0.005598aCCNB1, CCNB2, RRM2, PERP, PTEN

a P<0.01. Geneset A represents the differentially expressed genes present in dermal fibroblasts from keloids with hydrocortisone treatment, specifically, novel differentially expressed genes following hydrocortisone treatment. Geneset C represents the differentially expressed genes that were not affected by hydrocortisone treatment.

Potential diseases associated with DEGs in genesets A and C

To investigate the adverse effects of HC during its treatment on keloids, potential diseases associated with DEGs in genesets A and C were identified. It was determined that the newly added DEGs in dermal fibroblasts from keloids following HC treatment and genes that were not altered by HC were associated with two diseases: Bone loss (IL1R1, HSPA2 and COL1A1) and osteoarthritis (IL1R1, IGFBP7 and COL1A1; Table III).

Table III.

Potential diseases associated with differentially expressed genes in genesets A and C.

Table III.

Potential diseases associated with differentially expressed genes in genesets A and C.

DiseaseP-valueGenes
Bone loss 0.002593aIL1R1, HSPA2, COL1A1
Osteoarthritis 0.033811aIL1R1, IGFBP7, COL1A1, CALM1

a P<0.05. Geneset A represents the differentially expressed genes present in dermal fibroblasts from keloids with hydrocortisone treatment, specifically, novel differentially expressed genes following hydrocortisone treatment. Geneset C represents the differentially expressed genes that were not affected by hydrocortisone treatment.

Small molecule drugs targeting DEGs in genesets A and C

To further investigate potential drugs that are able to weaken or eliminate the adverse effects of HC, small molecule drugs targeting DEGs in genesets A and C were identified. A total of 9 small molecule drugs were selected from the CMAP database, including acemetacin, scriptaid and alsterpaullone. Among them, acemetacin has a negative score and the lowest P-value (P=0.00002), indicating it had the strongest effect on the adverse effects of HC on gene expression (Table IV).

Table IV.

Small molecule drugs potentially used to treat the diseases associated with differentially expressed genes in genesets A and C.

Table IV.

Small molecule drugs potentially used to treat the diseases associated with differentially expressed genes in genesets A and C.

Small molecule drugEnrichmentP-value
Acemetacin−0.925 0.00002a
Scriptaid0.912 0.00142a
Alsterpaullone0.923 0.00094a
Mycophenolic acid0.9570.0001a
MG-2620.962 0.00008a
Trifluridine0.975<0.001
Camptothecin0.975 0.00004a
Ciclopirox0.987<0.001
MS-2750.998 0.00002a

a P<0.05. Geneset A represents the differentially expressed genes present in dermal fibroblasts from keloid with hydrocortisone treatment, specifically, novel differentially expressed genes following hydrocortisone treatment. Geneset C represents the differentially expressed genes that are not affected by hydrocortisone. The closer to −1 the enrichment score is, the stronger the effect of the drug on the diseases.

Discussion

Keloids are benign fibrotic tumors of the dermis and are a cosmetic and psychological burden to patients (2). In the present study, 192 and 67 DEGs were screened from dermal fibroblasts in keloids with and without HC treatment, respectively, and compared with gene expression in normal scar tissue. According to the GO functional enrichment analysis for DEGs only present in dermal fibroblasts from keloids without HC treatment, namely those expressed normally following HC treatment, a set of genes (COL18A1 and JAG1) were significantly associated with endothelial cell differentiation and regulation of cell proliferation (P<0.001).

COL18A1 encodes the alpha chain of type XVIII collagen, which is an inhibitor of angiogenesis (18). It has demonstrated that collagen XVIII levels are downregulated in keloid patients compared with normal controls (19). Inhibition of collagen synthesis was observed following the addition of higher concentrations of HC (20). JAG1 is one of Notch ligands from the Notch family (21). Increased expression of JAG1 and Notch receptors has been observed in keloid fibroblasts and the inhibition of Notch signaling via JAG1 knockdown led to the inhibition of proliferation, migration and invasion properties of keloid fibroblasts (22). Furthermore, the endothelial cells within blood vessels in keloids are somewhat rounded and projected into the lumen of the vessel (23); this has been speculated as critical to facilitate the development and maintenance of keloids (24). Vascular endothelial growth factor, which promotes angiogenesis and enhances endothelial cell survival (25), is abundantly produced in keloids (26,27). As DEGs in geneset B were not present in the samples following HC treatment, these genes were considered to be potentially associated with the positive efficacy of HC. Therefore, HC may serve a key role in the treatment of keloids by targeting genes associated with endothelial cell differentiation and regulation of cell proliferation (COL18A1 and JAG1).

The pathway enrichment analysis for the DEGs in genesets A and C revealed that certain DEGs (CCNB1 and CCNB2) were significantly enriched in the cell cycle and p53 signaling pathways (P<0.05). Keloids are characterized by aggressive dermal growth beyond the boundaries of the original margins of a wound (2), which is dependent on the ectopic cell cycle. A previous study demonstrated that mRNAs associated with cell cycle suppression, such as cyclin B1, were detected in the bottom region of keloids (28). Furthermore, CCNB1 gene expression is reduced by low-dose 5-fluorouracil in treated keloid fibroblasts (29). The p53 tumor suppressor acts as a transcription factor and has a central function in controlling apoptosis (30). p53 levels are higher in keloids compared with normal scar tissues (31). Therefore, the current study demonstrated that CCNB1 and CCNB2 are involved in the cell cycle and p53 signaling pathways may be essential in the development of keloids. However, the current results indicated that the expression of these genes was altered following HC treatment, and did not change in the samples without HC treatment. Thus, it is speculated that the alterations of CCNB1 and CCNB2 may contribute to keloids via dysregulation of cell cycle and p53 signaling pathways.

A number of diseases, such as bone loss, were predicted to be associated with DEGs in keloid fibroblasts treated with HC (IL1R1 and COL1A1). Bone loss is one of the most devastating adverse effects of glucocorticoids as it results in the inhibition of calcium transport and the impairment of osteoblast function (32). A previous study has reported that long-term treatment of secondary hypocortisolism with a high replacement dose of hydrocortisone (30 mg/day) induces bone loss (33). IL1R1 encodes the type I interleukin 1 receptor. It has been demonstrated that IL-1 production may accelerate bone loss in postmenopausal women (34). The interleukin-1 receptor antagonist (IL-1ra) may decrease bone loss and bone resorption in ovariectomized rats (35) and it has been reported that a gene polymorphism of IL-1ra is associated with bone mineral density and osteoporosis in postmenopausal women (36). Additionally, it has been demonstrated that COL1A1 (encoding collagen, type I, alpha 1) Sp1 alleles are associated with a modest reduction in bone mineral density and a markedly increased risk of osteoporotic fracture, particularly vertebral fracture (37). Previously, it was demonstrated that the crosslinking process of collagen is important in bone strength, osteogenesis imperfecta and osteoporosis (38). Therefore, the present study hypothesized that HC may contribute to bone loss during treatment with keloids, through certain genes including IL1R1 and COL1A1.

Although HC has been successfully used to treat keloids, it also induces certain adverse effects, such as arthralgia (39). In the present study, 9 small molecule drugs were identified by the CMAP database and acemetacin was predicted to be the most effective drug at reducing the adverse effects of HC. It has previously been demonstrated that acemetacin may treat arthralgia effectively (40). Therefore, combining acemetacin with HC may be a novel therapeutic method of treating keloids, thus reducing the adverse effects of HC treatment.

Despite the aforementioned results, there were a number of limitations in the present study. Confirmation by experiment of these predictions is necessary. Future in vivo studies are required to detect the expression of genes associated with endothelial cell differentiation and regulation of cell proliferation. Furthermore, the efficacy of acemetacin-HC combination treatment compared with HC treatment alone requires evaluation.

In conclusion, the present study suggests that HC treats keloids effectively by targeting COL18A1 and JAG1, which are associated with endothelial cell differentiation. However, the cell cycle and p53 signaling pathways in keloids do not return to normal following treatment with HC. A number of adverse effects such as bone loss, which involves IL1R1 and COL1A1, may occur during the therapeutic process of HC treatment. Additionally, it was predicted that acemetacin may be used in combination with HC to treat keloids, although further studies are required to demonstrate its efficacy. These findings may contribute to the understanding of mechanisms involved in HC treatment on keloids and provide candidates for subsequent validation and further study.

References

1 

Marneros AG, Norris JE, Watanabe S, Reichenberger E and Olsen BR: Genome scans provide evidence for keloid susceptibility loci on chromosomes 2q23 and 7p11. J Invest Dermatol. 122:1126–1132. 2004. View Article : Google Scholar : PubMed/NCBI

2 

Fong CY, Biswas A, Subramanian A, Srinivasan A, Choolani M and Bongso A: Human keloid cell characterization and inhibition of growth with human Wharton's jelly stem cell extracts. J Cell Biochem. 115:826–838. 2014. View Article : Google Scholar : PubMed/NCBI

3 

Asboe-Hansen G, Brodthagen H and Zachariae L: Treatment of keloids with topical injections of hydrocortisone acetate. AMA Arch Derm. 73:162–165. 1956. View Article : Google Scholar : PubMed/NCBI

4 

Russell JD, Russell SB and Trupin KM: Differential effects of hydrocortisone on both growth and collagen metabolism of human fibroblasts from normal and keloid tissue. J Cell Physiol. 97:221–229. 1978. View Article : Google Scholar : PubMed/NCBI

5 

Russell SB, Russell JD and Trupin JS: Alteration of amino acid transport by hydrocortisone. Different effects in human fibroblasts derived from normal skin and keloid. J Biol Chem. 257:9525–9531. 1982.PubMed/NCBI

6 

Trupin JS, Russell SB and Russell JD: Variation in prolyl hydroxylase activity of keloid-derived and normal human fibroblasts in response to hydrocortisone and ascorbic acid. Coll Relat Res. 3:13–23. 1983. View Article : Google Scholar : PubMed/NCBI

7 

Ladin DA, Hou Z, Patel D, McPhail M, Olson JC, Saed GM and Fivenson DP: p53 and apoptosis alterations in keloids and keloid fibroblasts. Wound Repair Regen. 6:28–37. 1998. View Article : Google Scholar : PubMed/NCBI

8 

Meyer LJ, Russell SB, Russell JD, Trupin JS, Egbert BM, Shuster S and Stern R: Reduced hyaluronan in keloid tissue and cultured keloid fibroblasts. J Investig Dermatol. 114:953–959. 2000. View Article : Google Scholar : PubMed/NCBI

9 

Mantripragada KK, Buckley PG, de Ståhl Diaz T and Dumanski JP: Genomic microarrays in the spotlight. Trends Genet. 20:87–94. 2004. View Article : Google Scholar : PubMed/NCBI

10 

Smith JC, Boone BE, Opalenik SR, Williams SM and Russell SB: Gene profiling of keloid fibroblasts shows altered expression in multiple fibrosis-associated pathways. J Invest Dermatol. 128:1298–1310. 2008. View Article : Google Scholar : PubMed/NCBI

11 

Seo J and Hoffman EP: Probe set algorithms: Is there a rational best bet? BMC Bioinformatics. 7:3952006. View Article : Google Scholar : PubMed/NCBI

12 

Smyth GK: Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol. 3:Article32004. View Article : Google Scholar : PubMed/NCBI

13 

Bland JM and Altman DG: Multiple significance tests: The Bonferroni method. BMJ. 310:1701995. View Article : Google Scholar : PubMed/NCBI

14 

Huang da W, Sherman BT and Lempicki RA: Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 4:44–57. 2009. View Article : Google Scholar : PubMed/NCBI

15 

Xie C, Mao X, Huang J, Ding Y, Wu J, Dong S, Kong L, Gao G, Li CY and Wei L: KOBAS 2.0: A web server for annotation and identification of enriched pathways and diseases. Nucleic Acids Res. 39:W316–W322. 2011. View Article : Google Scholar : PubMed/NCBI

16 

Wang J, Duncan D, Shi Z and Zhang B: WEB-based GEne SeT AnaLysis Toolkit (WebGestalt): Update 2013. Nucleic Acids Res. 41:W77–W83. 2013. View Article : Google Scholar : PubMed/NCBI

17 

Lamb J: The Connectivity Map: A new tool for biomedical research. Nat Rev Cancer. 7:54–60. 2007. View Article : Google Scholar : PubMed/NCBI

18 

Pufe T, Petersen WJ, Miosge N, Goldring MB, Mentlein R, Varoga DJ and Tillmann BN: Endostatin/collagen XVIII-an inhibitor of angiogenesis-is expressed in cartilage and fibrocartilage. Matrix Biol. 23:267–276. 2004. View Article : Google Scholar : PubMed/NCBI

19 

Mogili NS, Krishnaswamy VR, Jayaraman M, Rajaram R, Venkatraman A and Korrapati PS: Altered angiogenic balance in keloids: A key to therapeutic intervention. Transl Res. 159:182–189. 2012. View Article : Google Scholar : PubMed/NCBI

20 

Deshpande M, Papp S, Schaffer L and Pouyani T: Hydrocortisone and triiodothyronine regulate hyaluronate synthesis in a tissue-engineered human dermal equivalent through independent pathways. J Biosci Bioeng. 119:226–236. 2015. View Article : Google Scholar : PubMed/NCBI

21 

Bolós V, Grego-Bessa J and de la Pompa JL: Notch signaling in development and cancer. Endocr Rev. 28:339–363. 2007. View Article : Google Scholar : PubMed/NCBI

22 

Syed F and Bayat A: Notch signaling pathway in keloid disease: Enhanced fibroblast activity in a Jagged-1 peptide-dependent manner in lesional vs. Extralesional fibroblasts. Wound Repair Regen. 20:688–706. 2012. View Article : Google Scholar : PubMed/NCBI

23 

Ehrlich HP, Desmoulière A, Diegelmann RF, Cohen IK, Compton CC, Garner WL, Kapanci Y and Gabbiani G: Morphological and immunochemical differences between keloid and hypertrophic scar. Am J Pathol. 145:105–113. 1994.PubMed/NCBI

24 

Kischer CW, Thies AC and Chvapil M: Perivascular myofibroblasts and microvascular occlusion in hypertrophic scars and keloids. Hum Pathol. 13:819–824. 1982. View Article : Google Scholar : PubMed/NCBI

25 

Nör JE, Christensen J, Mooney DJ and Polverini PJ: Vascular endothelial growth factor (VEGF)-mediated angiogenesis is associated with enhanced endothelial cell survival and induction of Bcl-2 expression. Am J Pathol. 154:375–384. 1999. View Article : Google Scholar : PubMed/NCBI

26 

Gira AK, Brown LF, Washington CV, Cohen C and Arbiser JL: Keloids demonstrate high-level epidermal expression of vascular endothelial growth factor. J Am Acad Dermatol. 50:850–853. 2004. View Article : Google Scholar : PubMed/NCBI

27 

Fujiwara M, Muragaki Y and Ooshima A: Upregulation of transforming growth factor-beta1 and vascular endothelial growth factor in cultured keloid fibroblasts: Relevance to angiogenic activity. Arch Dermatol Res. 297:161–169. 2005. View Article : Google Scholar : PubMed/NCBI

28 

Javad F, Marriage F, Bayat A and Day PJ: Perturbation of cell cycle expression in keloid fibroblast. Skinmed. 10:152–159. 2012.PubMed/NCBI

29 

Huang L, Wong Y, Cai Y, Lung I, Leung C and Burd A: Low-dose 5-fluorouracil induces cell cycle G2 arrest and apoptosis in keloid fibroblasts. Br J Dermatol. 163:1181–1185. 2010. View Article : Google Scholar : PubMed/NCBI

30 

Lane DP: The regulation of p53 function: Steiner Award Lecture. Int J Cancer. 57:623–627. 1994. View Article : Google Scholar : PubMed/NCBI

31 

Tanaka A, Hatoko M, Tada H, Iioka H, Niitsuma K and Miyagawa S: Expression of p53 family in scars. J Dermatol Sci. 34:17–24. 2004. View Article : Google Scholar : PubMed/NCBI

32 

Lukert BP and Raisz LG: Glucocorticoid-induced osteoporosis. Rheum Dis Clin North Am. 20:629–650. 1994.PubMed/NCBI

33 

Wichers M, Springer W, Bidlingmaier F and Klingmüller D: The influence of hydrocortisone substitution on the quality of life and parameters of bone metabolism in patients with secondary hypocortisolism. Clin Endocrinol (Oxf). 50:759–765. 1999. View Article : Google Scholar : PubMed/NCBI

34 

Langdahl BL, Løkke E, Carstens M, Stenkjær LL and Eriksen EF: Osteoporotic Fractures Are Associated with an 86-Base Pair Repeat Polymorphism in the Interleukin-1-Receptor Antagonist Gene But Not with Polymorphisms in the Interleukin-1beta Gene. J Bone Miner Res. 15:402–414. 2000. View Article : Google Scholar : PubMed/NCBI

35 

Kimble RB, Vannice JL, Bloedow DC, Thompson RC, Hopfer W, Kung VT, Brownfield C and Pacifici R: Interleukin-1 receptor antagonist decreases bone loss and bone resorption in ovariectomized rats. J Clin Invest. 93:1959–1967. 1994. View Article : Google Scholar : PubMed/NCBI

36 

Chen HY, Chen WC, Wu MC, Tsai FJ and Lin CC: Interleukin-1beta and interleukin-1 receptor antagonist gene polymorphism in postmenopausal women: Correlation to bone mineral density and susceptibility to osteoporosis. Maturitas. 44:49–54. 2003. View Article : Google Scholar : PubMed/NCBI

37 

Mann V and Ralston SH: Meta-analysis of COL1A1 Sp1 polymorphism in relation to bone mineral density and osteoporotic fracture. Bone. 32:711–717. 2003. View Article : Google Scholar : PubMed/NCBI

38 

Viguet-Carrin S, Garnero P and Delmas P: The role of collagen in bone strength. Osteoporos Int. 17:319–336. 2006. View Article : Google Scholar : PubMed/NCBI

39 

Sun Y, Sun Q, Fan C, Shen J, Zhao W, Guo Y, Su T, Wang W, Ning G and Bian L: Diagnosis and therapy for Cushing's disease with negative dynamic MRI finding: A single-centre experience. Clin Endocrinol (Oxf). 76:868–876. 2012. View Article : Google Scholar : PubMed/NCBI

40 

Bori Segura G, Rubio Torres y Gutierrez A, Herrera Gómez LE and Olguín Uribe J: Efficacy and tolerability of acemetacin, a non-steroidal anti-inflammatory drug, in Mexican patients: Result of the ETAPAM Study. Proc West Pharmacol Soc. 45:pp. 104–107. 2002, PubMed/NCBI

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Spandidos Publications style
Wang H, Quan L, Liang J, Shi J, Qiu T, Zhang Y, Wang Y, Hui Q, Zhang Y, Tao K, Tao K, et al: Gene expression profiling analysis of keloids with and without hydrocortisone treatment. Exp Ther Med 14: 5283-5288, 2017
APA
Wang, H., Quan, L., Liang, J., Shi, J., Qiu, T., Zhang, Y. ... Tao, K. (2017). Gene expression profiling analysis of keloids with and without hydrocortisone treatment. Experimental and Therapeutic Medicine, 14, 5283-5288. https://doi.org/10.3892/etm.2017.5263
MLA
Wang, H., Quan, L., Liang, J., Shi, J., Qiu, T., Zhang, Y., Wang, Y., Hui, Q., Zhang, Y., Tao, K."Gene expression profiling analysis of keloids with and without hydrocortisone treatment". Experimental and Therapeutic Medicine 14.6 (2017): 5283-5288.
Chicago
Wang, H., Quan, L., Liang, J., Shi, J., Qiu, T., Zhang, Y., Wang, Y., Hui, Q., Zhang, Y., Tao, K."Gene expression profiling analysis of keloids with and without hydrocortisone treatment". Experimental and Therapeutic Medicine 14, no. 6 (2017): 5283-5288. https://doi.org/10.3892/etm.2017.5263