IDENTIFICATION OF POTENTIAL KEY GENES ASSOCIATED WITH

Acta Medica Mediterranea, 2019, 35: 2315

IDENTIFICATION OF POTENTIAL KEY GENES ASSOCIATED WITH CARDIAC FIBROSIS BY RNA SEQUENCING DATA ANALYSIS

DanDan Liu, HaizHu Wang, Xiao Han, Caiping Han, Fengbo Ren

Department of Cardiology, Zhoukou Central Hospital, Zhoukou 466000, Henan, China

ABSTRACT

Introduction: Cardiac fibrosis is central to a broad constellation of cardiovascular diseases with similar pathophysiologic companions, and is associated with cardiac dysfunction, arrhythmogenesis, and adverse outcome. However, the option of effective treatment strategies is limited due to the insufficient understanding of the mechanisms for cardiac fibrosis.

Materials and methods: The RNA sequencing data (GSE97358) comprising 84 TGF-β1-stimulated samples and 84 paired unstimulated samples of cultured primary human cardiac fibroblast from GEO database was used to explore crucial genes and pathways involved in cardiac fibrosis. The differentially expressed genes (DEGs) were identified using edgeR package in R. Pro-tein-protein interaction (PPI) network and module analyses were performed and visualized using STRING and Cytoscape. GO (gene ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analyses were performed by clusterprofiler. The hub genes extracted from PPI were identified by the CytoHubba plug-in and the transcription factor(TF)-hub gene network was further constructed by the iRegulon plug-in.

Results: Totally, 647 DEGs were initially screened out in TGF-β1-stimulated primary human cardiac fibroblast. Twenty hub genes (9 up-regulated: S1PR5, F2RL3, GPR68, CXCR5, KISS1, GAL, LPAR5, HTR1D, PLCB4; 11 down-regulated: CXCL1, GPR65, CYSLTR2, EDNRA, CXCL6, F2R, GNG2 F2RL2, SSTR1, TAS2R1, HTR2B) were further identified. Wnt signaling and neu-roactive ligand-receptor interaction signaling pathways enriched were ultimately identified as the key pathways involved in cardiac fibrosis. Seven TFs (RELB, FOS, SREBF2, PURA, TBX21, IRF1 and IRF4) were identified for the TF-hub gene networks.

Conclusions: Our results may provide novel insights into the molecular mechanisms and treatments of cardiac fibrosis. How-ever, further molecular biological experiments are required to confirm these findings.

Keywords: cardiac fibrosis, differentially expressed genes, bioinformatics analysis, interaction network.

DOI: 10.19193/0393-6384_2019_5_360

Received November 30, 2018; Accepted February 20, 2019

Introduction

Cardiac fibrosis is characterized by the net ac-cumulation of extracellular matrix which involves unbalanced collagen turnover and excessive dif-fuse collagen deposition in the interstitial spaces of the myocardium(1). As documented by previous studies, cardiac fibrosis is central to a broad con-stellation of cardiovascular diseases with similar pathophysiologic companions, and is associated with cardiac dysfunction, arrhythmogenesis, and adverse outcome(2). In many cases, cardiac fibrosis is the result of a reparative process that is activat-

ed in response to some pathophysiologic stimuli, such as pressure and/or volume overload, metabol-ic disorder, ischemic insults or aging which may result in interstitial and perivascular fibrosis(3,4). Yet, activated myofibroblasts are the main effector cells in response to these pathophysiologic stimu-li in cardiac fibrosis(1). In this regard, some fibrot-ic factors, such as cytokines, chemokines, growth factors, hormones, and reactive oxygen species, are responsible for the activation of fibroblasts and the alteration of extracellular matrix(5). A growing of studies have revealed multiple signaling path-ways and biological processes involved in cardiac

2316 Dandan Liu, Haizhu Wang et Al

fibrosis, such as transforming growth factor-beta (TGF-β), Wnt/β-catenin, mitogen-activated protein kinase (MAPK) signaling, epithelial-mesenchymal transition (EMT), endothelial-mesenchymal transi-tion (EndMT), inflammation, oxidative stress pro-cesses, etc(1,6-8).

Although some conventional drugs, such as angiotensin-converting enzyme inhibitors (ACEIs), aldosterone antagonists, β-blocker, and statins, have been shown to alleviate cardiac fibrosis in clinical trials(9-13), most of these traditional therapies are not directed towards alleviating fibrosis but secondary to the correction of the underlying cardiac dysfunc-tion mechanisms and do not effectively hamper the progression of cardiac fibrosis(2). Despite the ad-vance in exploring the pathogenesis and treatment, the exact mechanisms of fibrosis accounting for the cardiac dysfunction and adverse outcome are not fully understood. Therefore, careful dissections of the cell biological mechanisms are of primary im-portance in the development of effective therapies.

In recent years, the advancement of microar-ray and high throughput sequencing technologies has provided an efficient tool to decipher critical genetic alternations in cardiac fibrosis and to iden-tify various key genes, molecular pathways, bio-logical processes, and cellular behaviors(14-16). In the present study, a large-scale RNA sequencing data (GSE97358) downloaded from Gene Expres-sion Omnibus (GEO) database were employed to acquire the differentially expressed genes (DEGs). We further explored the development of cardiac fi-brosis by a way of DEGs functional enrichment and interaction network analysis. The hub gene-tran-scription factor interaction network was also con-structed. The present study aimed to identify crucial genes and pathways involved in cardiac fibrosis by using bioinformatics analysis, which may result in a better understanding of the pathological mecha-nisms of cardiac fibrosis.

Materials and methods

Identification of differentially expressed genes

The public raw RNA sequencing data (GSE97358) was obtained from GEO data-base (https://www. ncbi.nlm.nih.gov/gds/?ter-m=GSE97358)(16). The dataset was deposit-ed by Schafer et al. in 2017 and comprised 84 TGF-β1-stimulated samples and 84 paired unstim-ulated samples of cultured primary human cardiac

fibroblast from patients receiving coronary artery bypass grafting(16). The RNA sequencing data were normalized and analyzed by the edgeR package in R. Differentially expressed genes (DEGs) were identified with the cut-off criteria |log2FC| ≥1, P-value < 0.05 and adjust P-value < 0.05.

Functional and pathway enrichment analysisTo elucidate potential biological processes,

molecular functions and signaling pathways cor-related with the DEGs, the Gene Ontology (GO, http://www.geneontology.org) and Kyoto Ency-clopedia of Genes and Genomes (KEGG, http://www.ge¬nome.ad.jp/kegg/) pathway enrichment analyses were performed(17,18), which were carried out with clusterProfiler for the up-regulated and down-regulated genes respectively(19). The enriched GO and KEGG terms were considered significant with the cut-off criteria of adjust P-value < 0.05

Protein-protein interaction network con-struction and module analysis

In order to interpret the molecular mecha-nisms of key cellular activities in cardiac fibrosis, the online Search Tool for the Retrieval of Interact-ing Genes (STRING, http://string-db.org/) database was used to construct a protein-protein interaction (PPI) network of the DEGs(20), which was selected and visualized with confidence score ≥0.4(medium confidence score). According to the degree of im-portance, significant modules of PPI network were screened out using the plug-in Molecular Complex Detection (MCODE) with the degree cutoff =2, node score cutoff=0.2, k-core=5 and max dept =100 in the Cytoscape (version 3.6). Moreover, the func-tion and pathway enrichment analyses were also performed for DEGs in the significant modules.

Construction of hub gene-transcription fac-tor interaction network

The hub genes were extracted from the PPI network and identified by using the Cytoscape plug-in CytoHubba which provides a user-friend-ly interface to explore important nodes in biolog-ical networks, and the Maximal Clique Centrality (MCC) method which has a better performance was used(21). The transcription factor (TF) which may target hub genes were predicted by using the Cyto-scape plug-in iRegulon. As reported, iRegulon can enrich TF motifs based on their direct targets with the position weight matrix method(22). The gene sets and TF-target pairs on iRegulon were derived from

Identification of potential key genes associated with cardiac fibrosis by rna sequencing data analysis 2317

ENCODE ChIP-seq data, and the TRANSFAC and JASPER databases. In the present study, the potential TFs corresponding to the hub genes were identified by the motif enrichment analysis with the criteria that the between orthologous genes ≥0.05 and false discovery rate (FDR) on motif similarity ≤ 0.001, and normalized enrichment score (NES) >5. Finally, the hub gene-transcription factor inter-action networks were visualized by the Cytoscape software.

Statistical analysisStatistical analyses were performed using R

software v3.4.3 (R Foundation for Statistical Com-puting, Vienna, Austria). As for DEGs, the genes were considered significant with the cut-off criteria |log2FC| ≥1, P-value < 0.05 and adjust P-value < 0.05. As for GO and KEGG terms, the terms were considered significant with the cut-off criteria of adjust P-value < 0.05.

Results

Identification of DEGsBased the cut-off criteria, a total of 647 DEGs

were identified in TGF-β1-stimulated primary hu-man cardiac fibroblast compared to the unstimu-lated, consisting of 341 down-regulated and 306 up-regulated genes. The heatmap for the DEGs are shown in Figure 1.

Gene ontology and pathway enrichment analysis

Through GO analysis, the enriched go terms were classified into biological process (BP) and molecular function (MF). As shown in Figure 1, 13 terms in BP ontology for up-regulated DEGs were enriched, such as extracellular matrix or-ganization (17 genes), extracellular structure or-ganization (17 genes), muscle system process (19 genes), cardiac muscle tissue development (19 genes) and muscle contraction (15 genes), etc. In the MF ontology, 6 terms for up-regulated DEGs were enriched, including receptor regulator activ-ity (22 genes), receptor ligand activity (21 genes), frizzled binding (6 genes), growth factor activity (9 genes), G-protein coupled receptor binding (11 genes) and hormone activity (7 genes). In term of the down-regulated DEGs, 58 terms concerning BP ontology were enriched, including response to mechanical stimulus (15 genes), cellular response to interferon-gamma (12 genes), primary alcohol metabolic process (8 genes), retinol metabolic pro-cess (6 genes), response to interferon-gamma (12 genes), chronic inflammatory response (5 genes), etc. For the MF ontology, 8 terms were significant-ly enriched including cytokine binding (9 genes), cytokine activity (13 genes), oxidoreductase activi-ty, acting on the aldehyde or oxo group of donors (6 genes), drug transmembrane transporter activity (4 genes), cytokine receptor binding (13 genes), drug

transporter activity (4 genes), substrate-specific channel activity (16 genes) and cation channel ac-tivity (13 genes).

According to the KEGG pathway enrichment analysis(Figure 1), up-regulated genes were signif-icantly enriched in Wnt signaling pathway(IGF1/LEFTY2/WNT2/WNT7B/WNT11/WNT9A/WNT4/WNT5B/INHBE), signaling pathways regulating pluripotency of stem cells (IGF1/LEFTY2/WNT2/WNT7B/ WNT11 /WNT9A/WNT4/WNT5B/INHBE), Cushing syndrome (CDKN2B/KCNK3/PLCB4/WNT2/ WNT7B/WNT11/WNT9A/WNT4/WNT5B), hippo sign-aling pathway (WNT2/ WNT7B/ WNT11/ WN-T9A/WNT4/WNT5B/NKD1/GDF7), mTOR signaling pathway (IGF1/WNT2/WNT7B/ WNT11/WNT9A/WNT4/WNT5B), basal cell carcinoma (WNT2/WNT7B/WNT11/WNT9A/ WNT4/WNT5B), melanogenesis (PLCB4/WNT2/WNT7B/WNT11/WNT9A/ WNT4/ WNT5B), breast cancer (IGF1/WNT2/WNT7B/WNT11/WNT9A/FGF21/WNT4/WNT5B), gas-

Figure 1: The heatmap, protein-protein interaction(PPI), GO (gene ontology) and KEGG(Kyoto Encyclopedia of Genes and Genomes) enrichment analyses for the differentially expressed genes (DEGs). A. heatmap for the DEGs(341 down-regulated and 306 up-regulated). Red: up-regulation; Green: down-regu-lation. B. PPI network for the DEGs with confidence score ≥0.4, the disconnected nodes were hidden. C. GO(biological process and molecular function) and KEGG enrichment analyses for up-regulated DEGs. D. GO(biological process and molecular function) and KEGG enrichment analyses for down-regulated DEGs.


tric cancer (CDKN2B/WNT2/WNT7B/WNT11/WNT9A/FGF21/WNT4/WNT5B). Down-regu-late genes were mainly enriched in retinol metab-olism (ADH1B/ADH4/ALDH1A1/AOX1/RDH5/DHRS9/ CYP26B1/CYP27C1), tyrosine metab-olism (ADH1B/ADH4/ALDH1A3/AOX1/HPD/MAOA), cytokine-cytokine receptor interaction (TNFRSF8/CXCL1/IL1B/IL1R1/IL1RN/IL6R/INHBB/ CXCL6/CX3CL1/TNFRSF1B/IL1R2/GDF5/TNFSF14/ACKR4/IL20RA/IL26/IL34), drug metabolism- cytochrome P450 (ADH1B/ADH4/ALDH1A3/AOX1/FMO2/GSTA1/GSTA2/ MAOA), calcium signaling pathway (ADORA2B/ADRB2/ATP2B4/CAMK2B/CD38/EDNRA/ F2R/HTR2B/P2RX7/PDE1A/CYSLTR2).

PPI network construction and module analysisPPI network was constructed on the basis of

the STRING database and are displayed in Figure 1. Of which, the disconnected nodes were hidden. Subsequently, the network complex was further analyzed, and the most significant module was screened out according to the cut-off criteria by us-ing MCODE.

As a result, four most significant modules containing 42 nodes were identified (Figure 2). Then we performed GO and KEGG pathway en-richment analyses for these genes in the selected modules. The results showed that these genes were mainly associated with, in term of BP ontology, G-protein coupled receptor signaling pathway, coupled to cyclic nucleotide second messenger, positive regulation of cytosolic calcium ion con-centration involved in smooth muscle contraction, regulation of tube diameter; while G-protein cou-

pled receptor binding, frizzled binding, G-protein coupled peptide receptor activity, peptide receptor activity, G-protein coupled amine receptor activi-ty were enriched in MF ontology. Neuroactive li-gand- receptor interaction (ADORA2B/ ADRA2A/ADRB2/CYSLTR2/DRD1/EDNRA/F2R/F2RL2/ F2RL3/HTR1D/ HTR2B/LHB/ MC4R/RXFP1/S1PR5/SSTR1/VIPR1) and Wnt signaling path-way (PLCB4/ WNT11/WNT2/ WNT2B/WNT4/WNT5B/WNT7B/WNT9A) were enriched in the KEGG pathway analysis.

Hub genes selection and gene-transcription

factor interaction networkThe top 20 genes higher degrees selected

by the MCC method of CytoHubba plug-in were identified as the hub genes and sequentially or-dered as follows: GNG2, LPAR5, KISS1, PLCB4, F2R, HTR2B, GPR65, GPR68, CYSLTR2, F2RL2, F2RL3, EDNRA, CXCL1, CXCR5, CXCL6, GAL, HTR1D, TAS2R1, S1PR5 and SSTR1 (Figure 3A).

The mircoarray-based expressions of the hub genes were displayed in Table 1. Using the iReg-ulon plug-in, sixteen of twenty hub genes may be targeted by seven TFs (identity between orthol-ogous genes ≥ 0.05, FDR on motif similarity ≤ 0.001, and NES > 5). The TF-hub genes networks were illustrated as Figure 3B, of which the seven TFs(RELB, FOS, SREBF2, PURA, TBX21, IRF1 and IRF4) were listed.

Discussion

Cardiac fibrosis is frequently observed in pa-tients with hypertension, adriamycin-related, is-chemic, dilated, diabetic and hypertrophic cardio-

Figure 2: Top 4 modules from the PPI network by MCO-DE plug-in. (module 1, module 2, module 3, module 4). Red: up-regulated genes; Green: down-regulated genes.

Figure 3: The network for hub genes and transcription factors. A. The first 20 DEGs of the MMC method were chosen using CytoHubba plug-in to construct the hub ge-nes network. The more forward ranking is represented by a redder color. B. The network of transcription factors and hub genes by iRegulon plug-in. Yellow: transcription fac-tors; White: hub genes


myopathy particularly evident in the progression to heart failure. Implementation of anti-fibrotic strat-egies has been proposed as a promising therapeutic approach for patients with these diseases.

However, the rationale for these approach-es remains poorly developed due to the lack of a comprehensive understanding of the etiology and pathogenesis. Therefore, it is of vital importance to explore the etiological and molecular mechanisms of cardiac fibrosis for therapy and prevention. In the present study, we investigated potential genes correlated with cardiac fibrosis using bioinformat-ics analysis. A total of 647 DEGs including 341 down-regulated and 306 up-regulated genes were initially identified. Furthermore, results from GO analysis indicated that the up-regulated DEGs were mostly involved in extracellular matrix organiza-

tion, extracellular structure organization, and mus-cle contraction at the level of BP and receptor regu-lator activity, receptor ligand activity and G-protein coupled receptor binding at the level of MF.

The down-regulated DEGs were mainly en-riched in response to response to mechanical stim-ulus and cellular response to interferon-gamma at the level of BP and cytokine binding, cytokine activity and oxidoreductase activity at the level of MF. Meanwhile, KEGG pathway enrichment analysis showed that the up-regulated DEGs were mostly involved in Wnt signaling pathway, signal-ing pathways regulating pluripotency of stem cells, Cushing syndrome and hippo signaling pathway, while the down-regulated DEGs were significantly enriched in cytokine-cytokine receptor interaction, retinol metabolism, drug metabolism- cytochrome P450 and calcium signaling pathway.

Finally, Wnt signaling pathway and neuroac-tive ligand-receptor interaction signaling pathway were identified as the major pathways by the im-portant module analyses of DEGs. Also, twenty hub genes and a network with potential TFs were predicted. These enriched pathways and hub genes may provide insights into the molecular mechanism of cardiac fibrosis, and can therefore be beneficial for the development of new therapeutic strategies.

In recent years, multiple potential mecha-nisms accounting for the cardiac fibrosis have been proposed by many individuals in-vivo and in-vit-ro studies, while most studies lack systematization and large- scale samples. RNA-sequencing profile provides a global view of gene expression and ena-bles identification of critical genes and pathways in cardiac fibrosis with a comprehensive perspective. As suggested by the current study with 84 human cardiac fibroblast samples treated with or without TGF-β1 stimulating, Wnt signaling pathway was demonstrated to be a major pathway associated with cardiac fibrosis, which was in line with the findings by previous studies. The Wnt/β-catenin axis is known to promote fibroblast activation and proliferation during cardiac fibrosis via multiple downstream effectors such as T-cell factor (TCF)/lymphocyte enhancing factor (LEF) group of tran-scription factors, stem cell factor, accreted Friz-zled-related proteins, GSK-3β,Wnt1-induced se-creted protein-1, Rho/ROCK and Rac/JNK, planar cell polarity and Hippo pathway(23). Activation of Wnt signaling pathway has been shown to be caus-al to epicardial fibrosis in pediatric failed heart al-lografts with diastolic dysfunction(24).

Gene symbol Log2FC adj.P.Val

Up-regulated

S1PR5 2.28 1.45×10-17

F2RL3 1.86 5.44×10-14

GPR68 1.56 8.00×10-16

CXCR5 1.42 6.69×10-6

KISS1 1.42 1.61×10-3

GAL 1.33 5.15×10-9

LPAR5 1.24 2.05×10-6

HTR1D 1.12 2.84×10-13

PLCB4 1.01 2.94×10-14

Down-regulated

CXCL1 -1.00 2.54×10-2

GPR65 -1.03 2.25×10-9

CYSLTR2 -1.05 2.68×10-4

EDNRA -1.12 1.62×10-11

CXCL6 -1.13 7.30×10-3

F2R -1.20 6.84×10-18

GNG2 -1.22 1.08×10-12

F2RL2 -1.24 1.13×10-6

SSTR1 -1.27 1.23×10-5

TAS2R1 -1.29 1.67×10-8

HTR2B -1.85 1.03×10-8

FC, fold change

Table 1: The 20 hub up-regulated and down-regulated genes.


Studies have also confirmed an essential role for Wnt/β-catenin signaling in mediating cardiac fibrosis of hypertensive heart disease(25-27). Moreo-ver, the neuroactive ligand-receptor interaction sig-naling pathway was also demonstrated to be signif-icantly associated with cardiac fibrosis. Although few study have systematically reported a role of the pathway in the pathogenesis of cardiac fibrosis, there was evidence showing a cardioprotection ef-fect of neuroactive ligand-receptor interaction sig-naling pathway induced by sevoflurane in patients undergoing coronary artery bypass graft surgery(28).

Moreover, transcriptomic study revealed that te activation of neuroactive ligand-recep-tor interaction signaling pathway mediated by a herb compound danhong injection was found to have a neuroprotective effect against cerebral is-chemia/reperfusion-induced injury(29), while mi-croRNAs-mediated inhibition of neuroactive li-gand-receptor interaction signaling pathway was implicated in α-synuclein toxicity in early stage of drosophila parkinson's disease model(30). In the present study, most differentially expressed genes in the neuroactive ligand-receptor interaction sig-naling pathway were down-regulated following TGF-β1 stimulating, suggesting a possible role of the inhibition of this pathway in the TGF-β1-in-duced cardiac fibrosis. Therefore, the current study provided a potential new insight into the molecular mechanism of cardiac fibrosis. Nevertheless, this finding was only based on the bioinformatics anal-ysis, which required further in-depth verification by well-designed in-vivo and in-vitro experiments.

We also constructed the PPI network with DEGs to illustrate the overview of their function-al connections, and constructed the hub gene-TF network to explore the molecular mecha-nism of cardiac fibrosis. Twenty DEGs including GNG2, LPAR5, KISS1, PLCB4, F2R, HTR2B, GPR65, GPR68, CYSLTR2, F2RL2, F2RL3, ED-NRA, CXCL1, CXCR5, CXCL6, GAL, HTR1D, TAS2R1, S1PR5 and SSTR1 were identified as the hub genes. Of which, S1PR5(sphingosine-1- phosphate receptor 5) was an important member of endothelial differentiation gene receptor family which were described as an important mediator in the balance between the production of extracellular matrix (ECM) and its degradation(31).

Studies have also demonstrated a role for endothelial differentiation gene receptors in cyst-ic fibrosis(32), however, the exact role of S1PR5 in the fibrosis remains unclear. Noteworthily, S1PR5

is the most up-regulated hub gene in response to TGF-β1 stimulating, further investigation seems necessary to clarify underlying biological links between S1PR5 and cardiac fibrosis. F2RL3 (F2R like thrombin or trypsin receptor 3), also known as PAR4 (pro-apoptotic WT1 regulator), was reported to play a role in blood coagulation and inflamma-tion, and its hypomethylation was a strong predic-tor of mortality from cardiovascular diseases in smoking populations(33). The expression of PAR4 was also found elevated with in fibrosis diabetic cardiomyopathy but subsequently reduced with ar-gatroban treatment(34). Moreover, the activation of PAR4 has been shown to contribute to the patho-genesis of various pulmonary diseases including fibrosis caused by serine proteinases(35).

Therefore, it is biologically plausible to spec-ulate the role of F2RL3 (PAR4) in the cardiac fi-brosis. For the most down-regulated hub gene HTR2B(5-hydroxytryptamine (serotonin) recep-tor 2B), also known as 5-HT2B, the protein and mRNA expression was ever found to be enhanced in the pulmonary fibrosis in rats(36), while an-other study have demonstrated a cardioprotective function of the HTR2B in an integrated model of hypertensive diastolic dysfunction with preserved ejection fraction by inhibiting cardiac fibrosis and remodeling(37). The inconsistence may be due to a tissue-specific effect with unknown mechanism. In line with the previous study(37), our results also indicated that cardiac fibrosis may be associated with TGF-β1-induced inhibition of HTR2B. There were also some studies focusing on the association between other hub genes concerned and cardiac fi-brosis, but less information was provided. Molec-ular biology experiments are required to determine the functions of these hub genes in cardiac fibrosis the future.

Furthermore, the TF-hub gene regulatory network has presented several potentially impor-tant TFs (RELB, FOS, SREBF2, PURA, TBX21, IRF1 and IRF4) in cardiac fibrosis. RELB (RELB proto-oncogene, NF-kB subunit) is one of the five family members of the dimeric transcription fac-tor nuclear factor kappa B (NFκB)(38). Previous study have indicated that RELB was involved in TAX1BP1-mediated cardioprotective effect against cardiac hypertrophy and fibrosis by regulating au-tophagy in STZ-induced diabetic cardiomyopathy in mice, while RELB knockdown disrupted the protective effect(39). The role of FOS (Fos proto-on-cogene, AP-1 transcription factor subunit) in car-


diac fibrosis has been frequently reported particu-larly in angiotensin II-induced cardiac hypertrophy and fibrosis(40). Angiotensin II was able to induce the activation and growth of cardiac fibroblast via c-FOS-mediated activation of Rho-kinase, MAPK, PARP-1 pathways, resulting cardiac fibrosis(41).

IRF1 (interferon regulatory factor-1), a critical member of the IRF family, was previously shown to be implicated in interleukin 18-mediated cardiac fibrosis and diastolic dysfunction in mice(42). Re-cently, the pro-fibrotic effect of IRF1 was further confirmed by a research group who demonstrat-ed that specific IRF1 overexpression exacerbated aortic banding-induced cardiac hypertrophy, ven-tricular dilation, fibrosis and dysfunction, whereas IRF1- deficient (knockout) mice exhibited a signifi-cant reduction in the hypertrophic response, and the prohypertrophic effects was elicited by IRF1-me-diated transcriptional activation of inducible nitric oxide synthase (iNOS)(43). These three TFs were the most extensively studied genes associated with car-diac fibrosis in the seven TFs, there were some but less studies concentrating on the role of other four TFs in cardiac fibrosis to date, more experiments are therefore needed to fully uncover their biolog-ical functions in the cardiac fibrosis. Collectively, the intricate interaction between TFs and hub genes may provide biological and theoretical basis for the exploration of mechanisms and therapy of cardiac fibrosis.

In summary, the present study identified a se-ries of potential crucial genes, important modules, key pathways and networks, which may affect the cardiac fibrosis, for future investigation. Of which, twenty hub genes and seven TF-hub gene networks were identified. Two pathways including Wnt sig-naling and neuroactive ligand-receptor interaction signaling pathways enriched were speculated as the key pathways involved in cardiac fibrosis. Collec-tively, our results may provide novel insights into the molecular mechanisms and treatments of cardi-ac fibrosis.

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–––––––––Corresponding Author: Fengbo Ren, MDDepartment of Cardiology, Zhoukou Central HospitalEastern Renmin Road,Zhoukou 466000, Henan Email: [email protected](China)

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